Peritoneal dialysis system

Abstract

To provide a peritoneal dialysis system capable of adjusting therapy parameters and providing feedback to a patient regarding the effectiveness of his / her therapies.SOLUTION: A peritoneal dialysis system includes: an automated peritoneal dialysis ("APD") machine 104 configured to remove ultrafiltrate UF from a patient and record how much UF has been removed; and a logic implementer configured to (i) form a first moving average UF removed trend, (ii) determine a trending range around the first moving average UF removed trend, (iii) determine at least one of upper and lower UF removed limits from the trending range, (iv) form a second moving average UF removed trend, and (v) alert if the second moving average UF removed trend moves outside of the at least one UF removed limit.SELECTED DRAWING: Figure 1

Description

[Technical field]

[0001] The percentage of patients undergoing automated peritoneal dialysis ("APD") is increasing worldwide, due in part to the ability of APD to be tailored to the specific needs of the patient regarding their personal life and their therapeutic needs. The two primary goals of dialysis, solute clearance and ultrafiltration ("UF"), depend on the modality and type of APD being performed (e.g., nocturnal intermittent peritoneal dialysis ("NIPD"), continuous cycling peritoneal dialysis ("CCPD"), and high-dose CCPD), the type of solution, the duration of treatment, and the fill volume. Prescription of APD treatment constitutes the choice of each one of these. Thus, there are many combinations and possibilities from which to choose. [Background technology]

[0002] APD devices typically do not have the ability to provide feedback to the patient regarding the effectiveness of the recent treatment. Also, APD devices typically run open loop so as not to adjust treatment parameters (e.g., modality, solution type, treatment time, and fill volume) based on actual measured clearance and UF. Thus, some patients perform below target and develop adverse conditions such as over-infusion, and in some cases hypertension. Current methods for adjusting treatment typically involve the patient reporting to a center, often to be evaluated. These methods place the burden of treatment adjustment solely on the physician or clinician and do not occur frequently enough to adequately accommodate the patient's weekly, monthly, seasonal, or other lifestyle changes.

[0003] The systems and methods of the present disclosure seek to rectify the above problems. Summary of the Invention [Means for solving the problem]

[0004] The disclosed system includes multiple prescription optimization modules. One of the modules is the Advanced Peritoneal Equilibration Test or ("PET"). The PET allows the patient to perform the ultrafiltration ("UF") portion of the PET automatically at home using the patient's Automated Peritoneal Dialysis ("APD") machine. The automated test collects more UF data point samples than in the past, which helps establish a more accurate UF patient characteristic curve. The UF samples and blood tests are then used to generate physiological data for the patient.

[0005] The second module of the prescription optimization system of the present disclosure uses the above patient physiological data in conjunction with specific treatment targets (e.g., UF, clearance) and ranges of treatment inputs (e.g., number of exchanges, cycle times, solution selection) to calculate or deliver all possible dosing regimens that fall within the ranges provided.

[0006] A third aspect or module of the present disclosure is the use of one or more filters identifying patient preferences or physician performance requirements to reduce the number of regimens to a manageable few: the physician or patient agrees on a certain number of regimens, e.g., three to five regimens, to be prescribed by the physician for treatment.

[0007] Another feature of the present disclosure is an inventory tracking module that tracks the different solutions and other supplies used over a delivery cycle in making different prescriptions selected by the patient. The APD machine has the ability to mix dialysis solutions of different dextrose concentrations to produce a hybrid dextrose dialysate mixture, which further allows the patient's treatment to be optimized. The inventory tracking feature records the concentration of dextrose used and replaces the associated dialysate concentration consumed.

[0008] The fifth module of the present disclosure is trending of the prescriptions that the patient is taking. Trending can track any one or more of UF removal, weight, blood pressure, and prescriptions used. The sixth module controls how different prescriptions are recalled for use and adjusted or substituted if necessary. Trending can also trend and show averages such as a 7-day rolling average UF and / or a 30-day rolling average.

[0009] In one embodiment, the patient at the start of treatment weighs himself (e.g., after an initial drain) and takes his blood pressure. As discussed in detail herein, the system includes a weighing scale and a blood pressure taker that output weight and blood pressure information, respectively, wirelessly to the APD machine using wireless technology such as Bluetooth™, WiFi™, or Zigbee™ technology. In one embodiment, a wireless link is provided via radio frequency transmission. In an alternative embodiment, the weight and blood pressure information is provided via a wired connection between the weighing scale and blood pressure taker and the APD machine. Alternatively, the patient types in the weight and blood data.

[0010] The APD machine provides multiple treatment prescriptions from which the patient or the APD machine selects one for that day's treatment. For example, the APD machine can provide five doctor-approved prescriptions for the patient, one of which is selected based on the patient's weight, blood pressure, and UF removed over the last 24 hours. Because a prescription does not need to be selected before the initial discharge (which may occur in any of the possible treatments), the patient or the machine can obtain the final UF information from the previous day's treatment before determining which prescription to select. The machine, in one embodiment, provides a prompt at the start of treatment to remind the patient to obtain the patient's weight and blood pressure.

[0011] Five possible prescriptions are analytically determined. One possibility is to develop an algorithm and store it on the APD machine itself or on a server computer that communicates with the APD machine, for example, via an Internet connection. The algorithm can employ, for example, a three-pore model that adds predicted clearance across three different sizes of pores in the patient's peritoneum. The flux of toxins through large, small, and micropores of the peritoneum's blood vessels is summed. For example, urea and creatinine are removed from the patient's blood through the small pores. The large pores allow larger protein molecules to move from the patient's blood to the dialysate. In each case, an osmotic gradient drives the toxins from the patient's blood to the dialysate. Using the predicted clearance and the three-pore model, the system of the present disclosure outputs multiple acceptable dosing regimens for the patient. From these dosing regimens, for example, five prescriptions can be selected. Alternatively, the algorithm uses a two-pool model as discussed in detail below.

[0012] In one embodiment, the regimen generation portion of the system is stored and used in a dialysis center or nephrologist's office. A patient enters the office or center, a doctor or clinician examines the patient, and inputs patient data into the regimen generation software located in the office or center, which outputs a suitable regimen from which, for example, five different prescriptions are selected. These different prescriptions are expected to address the patient's fluctuating APD needs for the foreseeable future, for example, over the next six months to a year. New patients may have residual renal function ("RRF"), and therefore partially functional kidneys. These patients do not require as aggressive treatment as patients without renal function. However, the need for adjustments for these patients may become greater as the RRF worsens. Here, multiple prescriptions may need to be upgraded more frequently, for example, every three months.

[0013] The three-pore model is very good at predicting clearance values ​​such as removed urea, Kt / V, pKt / V, removed creatinine, CCr, pCCr, glucose absorption, and total effluent. The system of the present disclosure also uses advanced peritoneal effectiveness testing ("PET") to help accurately predict UF removal. Advanced PET also includes chemical analysis performed on blood samples and dialysate samples to better and more accurately predict the patient's clearance for removed urea, Kt / V, pKt / V, removed creatinine, CCr, pCCr, glucose absorption, and total effluent.

[0014] With respect to the advanced PET module of the present disclosure, the advanced PET includes samples taken in two treatments. In the first treatment, UF is measured after, for example, 30-minute dwells, 60-minute dwells, 120-minute dwells, and 240-minute dwells totaling 7.5 hours. In the second treatment, UF is measured after 8 hours of dwell, providing a total of 5 data points. At each time interval, the patient is completely drained to accurately determine UF. UF can be measured by an APD machine, or alternatively or additionally, via a meter if more accuracy is desired. The actual UF duration may differ slightly from the intended UF duration because the patient must completely drain and then refill each time. For example, a 2-hour UF period may actually take 2 hours and 10 minutes. The system of the present invention records the actual duration and uses the actual time as an input to the kinetic modeling.

[0015] Blood and dialysate samples can be taken at intervals whenever and wherever blood can be drawn. The first and second treatments can be done continuously or over two nights. In one embodiment, the patient does a 30 minute, 1 hour, and 4 hour fill / dwell / drain before going to bed. The patient then does the final fill, sleeps, and wakes up in time to do an 8 hour drain. The UF and actual dwell time are recorded for each dwell period. The data can be recorded on a data card that the patient takes to the laboratory or center the next day. The data can alternatively be transferred to the laboratory or center via the internet using the data communication module discussed herein.

[0016] The patient then goes to the dialysis center. The patient is filled an additional time. Blood and dialysate samples are taken, for example, at 2 hours and 4 hours. A second 4 hour discharge UF data point can be taken and compared to the first 4 hour discharge UF data point for additional accuracy.

[0017] Using a particular dialysate concentrate, such as 2.5% dextrose, five data UF points, blood test, and dialysate test data are acquired. The data points are used to estimate kinetic parameters including mass transfer area coefficient ("MTAC") of solutes and ultrafiltration parameters (hydraulic conductivity and fluid absorption rate) and classify the patient's transport and UF characteristics. Based on the estimated kinetic parameters, kinetic modeling using a modified three-pore model can then be physiologically applied to other types of dialysate concentrates, such as 1.5% dextrose and Extraneal® dialysate.

[0018] With respect to the dosing regimen generation module of the present disclosure, a predictive algorithm uses the above calculated patient transport and UF characteristics, target information, and other treatment input information to generate a dosing regimen. Target and other treatment information includes, for example, (i) clinical targets such as (a) minimum urea clearance, (b) minimum urea Kt / V, (c) minimum creatinine clearance, (d) maximum glucose absorption, and (e) target UF, (ii) treatment parameters such as (a) treatment time, (b) treatment volume, (c) loading volume, (d) dextrose percent, and (e) solution type, and (iii) available solutions. Many of these inputs are expressed as ranges, leading to many possible dosing regimen outcomes. In one embodiment, the software using a three-pore or two-pool model equation generates all possible dosing regimens using (i) each input within each range, and (ii) the patient's transport and UF characteristics, that meet the above targets and treatment information.

[0019] With respect to the prescription filtering module, the system allows the user to specify certain filtering information to pair the combinations of medication regimens into a manageable number of combinations from which to select and approve as a set prescription. Filtering information can include, for example, filtering out all medication regimens with aKt / V, creatinine clearance, and UF below certain values ​​and absorbed glucose above certain values. The clinician and patient then agree on some of the possible paired prescriptions, which are stored as a prescription on the patient's APD machine or, alternatively, on a server computer with a communication link to the APD machine.

[0020] The prescriptions can be stored on the patient's data card and physically loaded into the APD machine when the patient returns home. Alternatively, the dialysis center downloads the prescriptions to the APD machine via the Internet or other data communication network. The set of prescriptions can include, for example, (i) a standard UF prescription, (ii) a high UF prescription, and (iii) a low UF prescription. If the patient is able to, the APD system can be set up to allow the patient to run a prescription tailored to the day's activities. If the patient exercises hard one day and loses a lot of fluids through sweat, the patient can run a lower UF treatment that evening, perhaps saving the patient the trouble of having to do a mid-day exchange the next day. If the patient dined out on a given night and consumed more fluids than normal, the patient can run a high UF treatment. On all other days, the patient runs the standard UF prescription.

[0021] One companion component to the instant system is an inventory distribution and tracking module. If the selected prescription requires different types of dialysate concentrates, the different dialysate types need to be delivered in the correct quantities. In the present system, either the APD machine or the clinician's server tracks the patient's current inventory and ensures that the required supply of the appropriate solution is delivered to the patient's home.

[0022] As discussed herein, one of the treatment parameters is the dextrose percentage of the solution, which affects the amount of UF removed and the amount of calories absorbed by the patient. More dextrose results in more UF removed, which is generally desirable. However, more dextrose results in more caloric intake and weight gain by the patient, which is undesirable. Thus, dextrose profiling is an important factor in selecting possible treatments for a patient. Different solutions are provided with different dextrose percentages, such as 1.5%, 2.5%, and 4.25% dextrose. The APD machine described in connection with the present system has the ability to connect to multiple solution bags with different glucose percentages and draw solutions from the different bags to form a mixed or hybrid solution, for example, in a warming bag or in the patient's peritoneum if in-line heating is used, with a desired glucose percentage different from the rated percentage, for example, 2.0%, 2.88%, 3.38%, and 3.81% dextrose. When mixed in the warming bag, the warming bag can be fitted with one or more conductive strips that allow temperature compensated conductivity measurements to be taken of the mixed solution to ensure that the solution is properly mixed.

[0023] In one embodiment, the APD machine tracks the different bags used during treatment over the delivery cycle. Before the courier arrives with a new solution bag, the inventory used is sent to the solution distribution facility. This inventory is subtracted from the patient's total home inventory so the solution distribution facility knows how much of which solution to deliver to the patient's home. In one embodiment, when the courier arrives at the patient's home, the courier scans the patient's remaining inventory to compare with what is expected to remain. The APD machine does not automatically account for destroyed, lost, or unused solution bags for treatment. However, it is contemplated that such a procedure would provide more accurate advanced inventory information, allowing the patient to input the amount of bags lost or destroyed (or the actual total amount of bags remaining) into the APD machine tracking system. The courier's scan of the remaining product resets the patient's inventory with each delivery, in either case, so that errors do not accumulate.

[0024] With regard to the trend and alert generation module, the APD system of the present disclosure tracks or trends certain treatment parameters, such as daily UF, blood pressure, and weight. Trends can be viewed on the display device of the APD machine between treatments, for example, at the beginning of treatment, in one embodiment. Trends can also be viewed by the clinician and / or physician. At the beginning of treatment, the patient can view, for example, the patient's weight, blood pressure, and UF removed over the last 24 hours. The patient can know the previous day's UF after the patient's initial drain, which is from the last fill of the previous night's treatment. That is, the end of the first initial drain to the end of the second initial drain sets the UF cycle to be recorded. The patient weighs himself after the initial drain and provides the data to be entered into the machine via cable, or wirelessly, or alternatively via patient input. The trend data in combination with a set of filters or criteria is used to allow the treatment to be performed under the current set of prescriptions, or via a new prescription. The machine, in one embodiment, automatically alerts the clinician if an alarm condition occurs or if a prescription change is required.

[0025] The trend screen can show, for example, daily UF trend, 7-day moving average trend, and 30-day moving average trend. The moving average trend smooths out the daily highs and lows, more easily showing the rising and falling trends of UF. For example, if the actual UF removed falls below the low threshold UF removed over a period of time, or in combination with a patient implementing a high UF prescription to avoid substandard UF, the system of the present disclosure causes the APD machine to send an alarm or warning signal to the dialysis center and / or physician. Different methods or algorithms are discussed herein to prevent the system from overreacting or being too sensitive. Besides the periodic UF average, the system also uses algorithms that accumulate errors and look for other physiological patient parameters, such as weight and blood pressure, in an attempt to view the patient more generally, instead of just looking at UF removal.

[0026] With respect to the prescription recall and adjustment module, the clinician or physician responds to the prescription alarm in an appropriate manner, such as by calling the patient into the clinic, making suggestions via phone or email regarding the use of the currently existing prescription, prescribing a new PET, and / or modifying the patient's prescription, etc. Thus, the system is configured to remove the burden of detecting poorly performing prescriptions from the clinician or physician, and to alert about such poorly performing prescriptions as far as is reasonably possible without overreacting to one or more days of poor performance.

[0027] If an alert condition occurs and the APD machine is unable to communicate the alert condition to the clinic or center, e.g., internet service is not available or accessible, the system is configured to have the APD machine prompt the patient to contact the clinic or center. To that end, the system includes a handshaking procedure in which the clinician's server sends an electronic acknowledgment message to the APD machine so the APD knows that the alert has been received.

[0028] The APD system can be set to respond to consistent substandard treatment in a closed-loop manner. Here, the APD machine stores a database of acceptable prescriptions, e.g., the five prescriptions prescribed by the physician above. The machine automatically selects the prescription approved by the physician in an attempt to improve the results. For example, the machine can select a higher UF prescription if the patient's UF is substandard. Or, the machine presents several prescription options to the patient to select one or more prescriptions approved by the physician. It should be understood that in one embodiment, the system only allows the patient to follow prescriptions approved by the physician.

[0029] In another alternative embodiment, multiple approved prescriptions, e.g., five, are loaded onto the patient's APD machine, but only a portion, e.g., three of the five, are enabled. When the enabled therapy is found to be substandard, the physician or clinician enables a previously unenabled therapy that may, for example, increase the patient's UF. In this manner, the physician or clinician can select from a set of pre-approved prescriptions and not have to go back through the regimen generation and prescription filtering prescription sequence described above. The system can also provide the above-mentioned alert responses to blood pressure and weight alert conditions.

[0030] Besides modifying the patient's prescription, the system can respond to the alert in other ways. Trends show which prescriptions were administered on which days, so the doctor or clinician can see if the patient is administering sufficient and / or correct therapy. Trends also show patient weight, allowing the doctor or clinician to recommend that the patient reduce food and drink intake if the patient is gaining too much weight. Patient blood pressure can also be trended and considered in the condition. Several algorithms and examples are discussed herein that illustrate possible ramifications from patient alerts.

[0031] When the patient's treatment is functioning properly, the system can operate to allow the patient to select the prescription to run on a given day. The machine or system can alternatively select the daily prescription to run, or some combination thereof. Several prescription adjustment algorithms or methods are discussed herein that attempt to balance patient flexibility and lifestyle concerns with treatment performance concerns.

[0032] Thus, an advantage of the present disclosure is to provide an APD system that analyzes patient treatment data and communicates the results to a physician or clinician, who can then spend more time talking to the patient rather than manually performing the analysis.

[0033] Another advantage of the present disclosure is to provide a peritoneal dialysis system that seeks to optimize a treatment regimen for a patient.

[0034] Still further, advantages of the disclosed system are that it tracks or trend various patient PD physiological parameters, provides periodic averaging of the same, and responds quickly but does not overreact to apparent substandard therapy.

[0035] A further advantage of the disclosed system is that it provides a closed-loop PD system that is responsive to substandard UF, patient weight gain, and / or hypertension.

[0036] Yet another advantage of the system of the present disclosure is that it provides a system for tracking patient solution usage in order to efficiently deliver multiple required solutions to the patient.

[0037] A still further advantage of the system of the present disclosure is to provide a dialysis system that mixes standard dextrose solutions to achieve a dialysate with a desired blended dextrose concentration.

[0038] A further advantage of the system of the present disclosure is that it provides a dialysis system with multiple approved prescriptions from which the patient can choose to suit their daily needs.

[0039] Yet another advantage of the system of the present disclosure is that it provides a dialysis system that uses a more accurate peritoneal equilibration test.

[0040] Additional features and advantages are described herein, and will be apparent from, the following detailed description and drawings. (Item 1) an automated peritoneal dialysis ("APD") machine (104, 104a, 104b); a server computer (114, 118) in communication with the APD machines (104, 104a, 104b), the server computer (114, 118) and the APD machines (104, 104a, 104b) being programmed to enable the APD machines (104, 104a, 104b) to transmit patient ultrafiltration ("UF") clearance data to the server computer (114, 118) and to output the UF clearance data in a form including a moving average UF clearance trend suitable for a physician / clinician (110, 120) to review the data and make therapy adjustments if necessary; A peritoneal dialysis system (10). (Item 2) 2. The peritoneal dialysis system (10) of item 1, wherein the configuration includes a daily UF removal trend. (Item 3) 3. The peritoneal dialysis system (10) of item 2, wherein the daily UF removal trend includes at least one of an upper and lower UF limit, and the at least one limit is used together with the trend UF removal data to determine whether a therapy adjustment is necessary. (Item 4) 4. The peritoneal dialysis system (10) of item 3, wherein the APD machines (104, 104a, 104b) are programmed to send an alert to the server computer (114, 118) when an alert condition is met, the alert condition being based at least in part on a comparison of the daily UF removal data to the at least one limit. (Item 5) 4. The peritoneal dialysis system of claim 3, wherein the server computer is programmed to generate an alert when an alert condition is met, the alert condition being based at least in part on a comparison of the daily UF removal data to the at least one limit. (Item 6) 4. The peritoneal dialysis system (10) of item 3, wherein the at least one limit is determined by either (i) adding or subtracting the product of a factor and a UF range to (ii) the running UF removal average over a given day. (Item 7) The peritoneal dialysis system (10) of item 1, wherein the server computer (114, 118) and the APD machines (104, 104a, 104b) are further configured to enable the APD machines (104, 104a, 104b) to transmit at least one of blood pressure and patient weight data to the server computer (114, 118). (Item 8) 8. The peritoneal dialysis system (10) of item 7, comprising a wireless interface receiver (122) operable with a logic implementer (94, 104, 112, 114, 118), wherein at least one of the scale (126) and the blood pressure monitor (124) comprises a wireless interface transmitter, and at least one of the blood pressure and patient weight data is wirelessly transmitted from at least one of the scale (126) and the blood pressure monitor (124) to the wireless interface receiver (122). (Item 9) 2. The peritoneal dialysis system (10) of item 1, wherein the moving average UF removal trend is a daily, 5-day, 7-day, 30-day, or 90-day trend. (Item 10) 2. The peritoneal dialysis system (10) of item 1, wherein the trend includes at least one of an upper and lower UF limit, and the at least one limit is used together with the moving average UF removal trend to determine whether a therapy adjustment is necessary. (Item 11) Item 11. The peritoneal dialysis system (10) of item 10, wherein the APD machines (104, 104a, 104b) are programmed to send an alert to the server computer (114, 118) when an alert condition is met, the alert condition being based at least in part on a comparison of the moving average UF removal trend to the at least one limit. (Item 12) Item 11. The peritoneal dialysis system (10) of item 10, wherein the server computer (114, 118) is programmed to generate an alert when an alert condition is met, the alert condition being based at least in part on a comparison of the moving average UF removal trend to the at least one limit. (Item 13) Item 11. The peritoneal dialysis system (10) of item 10, wherein the moving average UF removal trend is a first trend and the at least one limit is determined by either (i) adding or subtracting a product of a factor and a UF range to (ii) a second moving average trend. (Item 14) Item 14. The peritoneal dialysis system (10) of item 13, wherein the second moving average trend is of longer duration than the first moving average trend. (Item 15) an automated peritoneal dialysis ("APD") machine (104, 104a, 104b); a server computer (114, 118) in communication with the APD machines (104, 104a, 104b), wherein the server computer (114, 118) and the APD machines (104, 104a, 104b) are programmed to generate peritoneal dialysis data trends that can be used by a physician / clinician (110, 120) to determine if therapy adjustments need to be made, the peritoneal dialysis data trends including a moving average UF removal trend; A peritoneal dialysis system (10). (Item 16) Item 16. The peritoneal dialysis system (10) of item 15, wherein the peritoneal dialysis trend data is of a type selected from the group consisting of: (i) ultrafiltrate removal data, (ii) blood pressure data, and (iii) patient weight data. (Item 17) Item 16. The peritoneal dialysis system (10) of item 15, wherein the APD machines (104, 104a, 104b) are programmed to collect / generate the data regarding the trends, and the server computer (114, 118) is programmed to generate the trends of the data. (Item 18) Item 16. The peritoneal dialysis system (10) of item 15, wherein the APD machines (104, 104a, 104b) are programmed to collect / generate the data about the trends and generate the trends of the data. (Item 19) Item 19. The peritoneal dialysis system (10) of item 18, wherein the APD machine (104, 104a, 104b) is further configured to send an alert to the server computer (114, 118) when the data trends indicate that a therapy adjustment is likely to need to be made. (Item 20) Item 16. The peritoneal dialysis system (10) of item 15, wherein the therapy adjustment is of a type selected from the group consisting of: (i) changing the type of dialysate, (ii) changing the dextrose concentration of the dialysate, (iii) changing the treatment time, (iv) changing the fill volume, (v) changing the number of nighttime fill exchanges, and (vi) whether a diurnal change is made. (Item 21) an automated peritoneal dialysis ("APD") machine (104, 104a, 104b) configured to remove ultrafiltrate ("UF") from a patient (102, 102a, 102b) and record how much UF has been removed; a logic implementer (94, 104, 112, 114, 118) configured to: (i) form a first moving average UF removal trend; (ii) determine a trend range around said first moving average UF removal trend; (iii) determine at least one of an upper and lower UF removal limit from said trend range; (iv) form a second moving average UF removal trend; and (v) alert when the second moving average UF removal trend moves outside of at least one removal UF limit; A peritoneal dialysis system (10). (Item 22) 22. The peritoneal dialysis system (10) of item 21, wherein the logic implementer (94, 104, 112, 114, 118) is stored in one of the APD machine (104, 104a, 104b) and a server computer (114, 118) in communication with the APD machine (104, 104a, 104b). (Item 23) 22. The peritoneal dialysis system (10) of claim 21, wherein the first moving average UF removal trend is of longer duration than the second moving average UF removal trend. (Item 24) 22. The peritoneal dialysis system (10) of claim 21, wherein the upper limit is formed by adding a factor multiplied by the trend range to the first moving average UF removal trend, and the lower limit is formed by subtracting the factor multiplied by the trend range to the first moving average UF removal trend. (Item 25) 22. The peritoneal dialysis system (10) of claim 21, wherein the alert is provided if (i) the UF removal trend moves outside of the at least one UF removal limit for a number of consecutive days, or (ii) the UF removal trend moves outside of the at least one UF removal limit and the patient's blood pressure rises above the limit. [Brief description of the drawings]

[0041] [Figure 1]FIG. 1 is a schematic diagram of one embodiment of the prescription optimization system of the present disclosure, including an improved peritoneal equilibration test ("PET") module, a dosing regimen generation module, a prescription filtering and selection module, a dialysate inventory management module, a communications module, a data entry module, a trend and alert generation module, and a prescription recall and adjustment module. [Figure 2A] FIG. 2A is a perspective view of a peritoneal vessel showing the different sizes of pores used in a three-pore model for predicting peritoneal dialysis treatment outcome. [Figure 2B] FIG. 2B is a schematic diagram of the kinetic transport properties of a two-pool model for predicting peritoneal dialysis treatment outcome. [Diagram 3] FIG. 3 illustrates a sample plot of UF removed versus residence time from data collected by a home dialysis device for use with the improved peritoneal equilibration test ("PET") of the present disclosure. [Figure 4A] 4A-4D are sample screens displayed on a clinician's or physician's computer as part of the system of the present disclosure illustrating the enhanced PET module and the additional data associated therewith. [Figure 4B] 4A-4D are sample screens displayed on a clinician's or physician's computer as part of the system of the present disclosure illustrating the enhanced PET module and the additional data associated therewith. [Figure 4C] 4A-4D are sample screens displayed on a clinician's or physician's computer as part of the system of the present disclosure illustrating the enhanced PET module and the additional data associated therewith. [Figure 4D] 4A-4D are sample screens displayed on a clinician's or physician's computer as part of the system of the present disclosure illustrating the enhanced PET module and the additional data associated therewith. [Diagram 5] FIG. 5 is a sample screen displayed on a clinician's or physician's computer as part of the system of the present disclosure illustrating the dosing regimen generation module and associated data. [Figure 6A]6A-6C are sample screens displayed on a clinician's or physician's computer as part of the system of the present disclosure illustrating filtering criteria used to filter the generated dosing regimens into possible prescriptions for treatment. [Figure 6B] 6A-6C are sample screens displayed on a clinician's or physician's computer as part of the system of the present disclosure illustrating filtering criteria used to filter the generated dosing regimens into possible prescriptions for treatment. [Figure 6C] 6A-6C are sample screens displayed on a clinician's or physician's computer as part of the system of the present disclosure illustrating filtering criteria used to filter the generated dosing regimens into possible prescriptions for treatment. [Figure 7A] 7A and 7B are sample screens displayed on a clinician's or physician's computer as part of the system of the present disclosure illustrating the selection of a prescription from a list of filtered medication regimens. [Figure 7B] 7A and 7B are sample screens displayed on a clinician's or physician's computer as part of the system of the present disclosure illustrating the selection of a prescription from a list of filtered medication regimens. [Figure 8A] 8A-8C are sample screens displayed on a clinician's or physician's computer as part of the system of the present disclosure illustrating agreement to high UF, standard UF, and low UF prescriptions, respectively. [Figure 8B] 8A-8C are sample screens displayed on a clinician's or physician's computer as part of the system of the present disclosure illustrating agreement to high UF, standard UF, and low UF prescriptions, respectively. [Figure 8C] 8A-8C are sample screens displayed on a clinician's or physician's computer as part of the system of the present disclosure illustrating agreement to high UF, standard UF, and low UF prescriptions, respectively. [Figure 9A]9A-9E illustrate another example of a filtering process according to the present disclosure resulting in a final filter of three prescribed medication regimens for a patient. [Figure 9B] 9A-9E illustrate another example of a filtering process according to the present disclosure resulting in a final filter of three prescribed medication regimens for a patient. [Figure 9C] 9A-9E illustrate another example of a filtering process according to the present disclosure resulting in a final filter of three prescribed medication regimens for a patient. [Figure 9D] 9A-9E illustrate another example of a filtering process according to the present disclosure resulting in a final filter of three prescribed medication regimens for a patient. [Figure 9E] 9A-9E illustrate another example of a filtering process according to the present disclosure resulting in a final filter of three prescribed medication regimens for a patient. [Figure 10] 10-13 are sample screens that are displayed on a clinician's or physician's computer as part of the system of the present disclosure illustrating one embodiment of the inventory control module. [Figure 11] 10-13 are sample screens that are displayed on a clinician's or physician's computer as part of the system of the present disclosure illustrating one embodiment of the inventory control module. [Figure 12] 10-13 are sample screens that are displayed on a clinician's or physician's computer as part of the system of the present disclosure illustrating one embodiment of the inventory control module. [Figure 13] 10-13 are sample screens that are displayed on a clinician's or physician's computer as part of the system of the present disclosure illustrating one embodiment of the inventory control module. [Figure 14] FIG. 14 is a perspective view of one embodiment of a dialysis apparatus and disposable pump cassette illustrating one suitable apparatus for performing dextrose mixing for use with the prescription optimization system of the present disclosure. [Figure 15A]15A and 15B are schematic diagrams illustrating embodiments of wireless and wired communication modules, respectively, for the prescription optimization system of the present disclosure. [Figure 15B] 15A and 15B are schematic diagrams illustrating embodiments of wireless and wired communication modules, respectively, for the prescription optimization system of the present disclosure. [Figure 16A] FIG. 16A is a schematic diagram illustrating another embodiment of a communication module and an embodiment of a data collection module that includes wireless weight and blood pressure data input to the prescription optimization system of the present disclosure. [Figure 16B] FIG. 16B is a schematic diagram illustrating a further embodiment of a communications module in which a central clinical server is located at or associated with a particular dialysis center. [Figure 17] Figures 17-21 are sample screens displayed on a patient's dialysis machine illustrating various trend data available for the patient. [Figure 18] Figures 17-21 are sample screens displayed on a patient's dialysis machine illustrating various trend data available for the patient. [Figure 19] Figures 17-21 are sample screens displayed on a patient's dialysis machine illustrating various trend data available for the patient. [Figure 20] Figures 17-21 are sample screens displayed on a patient's dialysis machine illustrating various trend data available for the patient. [Figure 21] Figures 17-21 are sample screens displayed on a patient's dialysis machine illustrating various trend data available for the patient. [Figure 22] 22 and 23 are sample screens displayed on a patient's dialysis machine or a clinician's and / or physician's computer as part of the trend module of the present disclosure illustrating various trend data including rolling UF average, target UF, daily UF, UF limits, and prescriptions used. [Figure 23]22 and 23 are sample screens displayed on a patient's dialysis machine or a clinician's and / or physician's computer as part of the trend module of the present disclosure illustrating various trend data including rolling UF average, target UF, daily UF, UF limits, and prescriptions used. [Figure 24] FIG. 24 is a schematic diagram illustrating one possible alert generation algorithm for the trend and alert generation module of the prescription optimization system of the present disclosure. [Diagram 25] FIG. 25 is a logic flow diagram illustrating another possible alert generation / prescription modification algorithm for the trend and alert generation module of the prescription optimization system of the present disclosure. [Figure 26] FIG. 26 is a sample screen displayed on a patient's dialysis instrument or clinician's and / or physician's computer as part of the system of the present disclosure illustrating various trend data, including running UF averages and UF limits determined via statistical process control. [Figure 27] FIG. 27 is a sample screen displayed on a patient's dialysis instrument or clinician's and / or physician's computer as part of the system of the present disclosure illustrating various trend data including running UF average, target UF, prescription used, and UF limit determined via statistical process control. [Figure 28] FIG. 28 is a schematic diagram of one embodiment of a forwarding function used in the prescription recall and adjustment module of the prescription optimization system of the present disclosure. [Figure 29] FIG. 29 is a sample screen displayed on a patient's dialysis instrument illustrating one possible prescription recall embodiment of the prescription recall and adjustment module of the prescription optimization system of the present disclosure. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0042] Referring now to the drawings, and specifically to FIG. 1, a schematic diagram of a peritoneal dialysis ("PD") system 10 having an automated peritoneal dialysis ("APD") machine 104 is illustrated. The system 10 provides and uses an improved peritoneal equilibrium test ("PET") 12 that samples and employs multiple data points to determine a patient's ultrafiltration ("UF") curve over the course of treatment. The PET 12 improves UF predictions used to characterize an individual's response to PD treatment and helps clinicians generate optimized prescriptions for patients. In one embodiment, the PET 12 is performed as a fixed treatment at home using the APD machine 104. The PET 12 also requires laboratory testing and analysis as described below.

[0043] The system 10 also provides automatic dosing regimen generation 14. Known dosing regimen generation is performed manually by the physician 110 or clinician 120 using haphazard strategies, is time-consuming, and relies on scientific guesswork by the nurse or physician. The automatic dosing regimen generation feature 14 allows the physician 110 or clinician 120 to use the PET 12 results, treatment input parameters, and entered treatment target parameters to generate a dosing regimen, saving time and increasing the likelihood that one or more dosing regimens will be generated that meet treatment targets for clearance and UF, minimize glucose exposure, and meet lifestyle needs.

[0044] The system 10 further includes a prescription filtering module 16 that reduces the many medication regimens generated by the automatic medication regimen generation feature 14 to a manageable number of prescriptions that are then selected by the patient and the physician / clinician to provide a set of approved prescriptions that are loaded onto the patient's APD machine 104 at home. In one embodiment, the APD machine 104 supports up to five prescriptions that are transferred to the APD machine 104 via a data card, the Internet, or other types of data communication. The different prescriptions can include, for example, two primary (or standard) prescriptions, one reduced volume (low UF) prescription, and two over-infusion (high UF) prescriptions, totaling five. Not all prescriptions must be activated by the physician. However, once activated by the physician, multiple prescriptions provide flexibility to the patient, allowing the APD machine 104 and treatment to better fit the patient's lifestyle needs while providing the right treatment.

[0045] Prescription filtering 16 naturally leads to an inventory tracking feature or module 18. Different prescriptions may require the patient to store different types of PD solutions at home. For example, one type of solution may be used for overnight exchanges while a second type of solution is used for the last fill or daytime exchange. The same type of solution may also be provided with different dextrose portions. The system 10 determines what type and variety of solution is needed, the amount of such type and variety, and what associated disposable components are needed to execute the enabled prescription. The APD machine 104 tracks how much of each type and variety of solution is used over a delivery cycle and communicates the usage to the clinician's server. The clinician's server then determines how much of which supply needs to be delivered to the patient for the next delivery cycle. When the delivery person arrives at the patient's home, the delivery person can scan the patient's actual remaining inventory and compare it against the clinician's server's expected remaining inventory. The patient's delivery can be adjusted if necessary. The patient's post-delivery inventory is now known and transmitted to the clinician's server. Communication is accomplished using a communication module, discussed below.

[0046] The system 10 as described includes a prescription download and treatment data upload communication module 20 that transfers data between the APD software and the doctor / clinician software, for example, via any one or more of the Internet, modem, and cellular phone. The dialysis center can use the communication module 20, for example, to send updated prescriptions to the patient's APD machine. Treatment data, logs, and trend data can be uploaded to the doctor / clinician data center so the doctor or clinician can access the patient information from anywhere, anytime.

[0047] The system 10 also includes an automatic, e.g., 24-hour UF, blood pressure, and weight data collection feature 22. The APD machine, in one embodiment, determines the patient's 24-hour UF and obtains blood pressure and weight daily and automatically. A remote exchange system ("RES") collects the patient's circadian exchange data and provides such data daily to the APD machine, e.g., via bluetooth or other wireless communication. The blood pressure and weight device can also transmit the patient's blood pressure and weight daily and wirelessly to the APD machine. The data collection feature 22 also includes the collection and input of therapeutic range and target information, e.g., into the regimen generation feature 14.

[0048] The system 10 further includes trending and alert generation features 24. The APD machine provides up to 90 days of trends of 24-hour UF, blood pressure, heart rate, weight, and prescriptions used. The patient, clinician, and / or physician can view these curves on the display of the APD machine, clinician computer, or physician computer. The APD machine acquires the data required for trending and transmits the data to a server computer, which in turn generates and monitors the trends. The APD machine and / or clinical software monitors the patient treatment trend data and generates alerts when any of the key parameters fall outside of the physician's pre-set ranges (or fall outside of ranges combined with other alert filtering criteria described herein).

[0049] The system 10 further includes a prescription recall and modification feature 26. Based on data from the trend feature 24, the patient 102, the physician 110, and / or the dialysis center 120 may recall one approved prescription for daily use in preference to another prescription. For example, if the patient's UF results for the past few days have been less than expected, the patient 102, the physician 110, and / or the dialysis center 120 may decide to use a higher UF prescription as opposed to a standard UF prescription. The system 10 may store, for example, three or five different prescriptions, all approved by the physician. The five prescriptions may include, for example, (i) low UF, (ii) standard UF with shorter duration and higher dextrose, (iii) standard UF with longer duration and lower dextrose, (iv) high UF with shorter duration and higher dextrose, and (v) high UF with longer duration and lower dextrose.

[0050] If the patient 102, the physician 110, and / or the dialysis center 120 know that the patient has recently gained weight, a lower dextrose prescription may be selected to reduce the calorie input from the treatment. Otherwise, the patient may wish to run a shorter treatment or a treatment without daytime exchanges for lifestyle reasons. The system 10 may be configured to allow the patient to choose which prescription to run on a given day. Alternatively, the dialysis instrument 104 runs a prescription downloaded from the dialysis center 120. Additionally, alternatively, the dialysis instrument 104 runs a prescription downloaded from the physician 110. The system 10 may, for example, run a hybrid control that allows the patient to choose which prescription to run on a given day, as long as the patient makes a responsible choice, and if the patient does not make a responsible choice, the system 10 switches to a prescription to run that is set by the machine for the patient. Alternatively, if the patient does not make a responsible choice, the system 10 may, for example, remove less aggressive options from a list of possible prescriptions, but still allow the patient to choose from the remaining prescriptions.

[0051] Many PD patients lose residual renal function ("RRF") over time, so PD therapy requires the removal of more UF. Also, loss of RRF may cause the patient's transport properties to decline. When trending function 24 indicates that the patient's UF is substandard, regardless of which prescription the patient is following, and the patient is gaining too much weight, the patient's blood pressure is too high, or a combination of these conditions is occurring, system 10 according to module 26 will automatically alert that the patient's prescription likely needs to be modified. Several measures are discussed herein that system 10 can take to ensure that the patient is not overly sensitive and tolerates natural fluctuations in the patient's UF, for example, due to instrument error or residual amounts of fluid left in the patient's peritoneum. However, when the patient exhibits a substandard pattern sufficient to indicate that it is not the result of normal fluctuations, system 10 will enact several procedures to improve the patient's PD capabilities. For example, system 10 can call for a new PET to be performed, a new dosing regimen to be generated accordingly, and a new prescription to be filtered from the generated dosing regimen. Alternatively, perhaps as an initial trial, the system 10 invokes a new set of filtering criteria (e.g., stricter treatment criteria) that are applied to the previously generated dosing regimen to filter out the new set of prescriptions. The new prescriptions are downloaded to the patient's dialysis machine 104 via a data memory card or via an Internet link from the doctor's office 110 or dialysis clinic 120.

[0052] (Peritoneal Equilibration Test ("PET")) Referring now to FIG. 2A, a cross-sectional view from a peritoneal vessel illustrates three pores of the vessel. Each of the three pores has its own toxin and UF clearance, which leads to one kinetic model called the three-pore model. The three-pore model is a mathematical model that represents, correlates, and predicts the relationship between the time course of solution removal, fluid transfer, treatment variables, and physiological properties. The three-pore model is a predictive model that can be used for different types of dialysis fluids, such as Dianeal®, Physioneal®, Nutrineal®, and Extraneal® dialysis fluids, which are commercially available by the applicant of the present disclosure.

[0053] The three-pore model is based on the algorithm expressed as follows:

[0054]

number

[0055] Studies have shown that the three-pore model and the modified two-pool model are essentially equivalent with respect to UF and small solute clearance. The modified two-pool model is easier to implement than the three-pore model because it requires fewer calculations and therefore less computer time. Studies have also shown that the correlation between predicted outcomes derived from the predictive software versus actual outcomes measured from actual treatment is, for the most part, good. Table 1 below shows the results of one study (E. Vonesh et al., 1999). The correlations (rc) are accurate for urea removed, weekly urea clearance (pKt / V), total urea clearance (Kt / V), creatinine removed, weekly creatinine clearance (pCCr), total creatinine clearance (CCr), glucose absorption, and total wastewater (excretion). However, the UF correlation is not very accurate, possibly due to the UF volume precision of the APD device, the patient's residual solution volume, the variability of the patient's transport properties, and the finite input points for estimating the key kinetic parameters.

[0056] [Table 1] It has been found that certain APD devices can measure the fill and drain fluid volumes very accurately. For example, the HomeChoice® / HomeChoicePRO® APD machines provided by the applicant of the present disclosure report a total fill and drain volume accuracy of 1% or + / - 10 mL. APD machines employing multiple exchange cycles increase the data points required to estimate key kinetic parameters while simultaneously reducing the possibility of introducing errors due to the patient's residual solution volume. Thus, a novel PET is proposed to improve the accuracy of UF prediction while maintaining or improving the current good prediction of small solutes (or toxins).

[0057] Figure 2B illustrates an alternative (two-pool PD) kinetic model that system 10 can use for PET 12. The two-pool PD kinetic model of Figure 2B, like Figure 2A, is used to predict fluid and solute removal in PD to (i) aid clinicians in caring for and managing patients, (ii) assist clinicians in understanding the physiological mechanisms governing peritoneal transport, and (iii) simulate treatment outcomes. A set of differential equations that collectively represent both diffusive and convective mass transport in both the body and dialysate compartments relative to an "equivalent" membrane core is as follows: (Body Compartment)

[0058]

number

[0059]

number

[0060]

number

[0061] Using an approximation to the above equation, the ultrafiltration rate Q u An analytical solution for is obtained, which gives the dialysis volume V at time t. D is analytically solved as follows: (dialysate capacity)

[0062]

number

[0063] For the modified version of the above equation, the permeability (L PA , mL / min / mmol / L) and lymph flow rate (Q L , mL / min) for two V D A value is required. V DThe (fill volume + UF) value is difficult to measure due to incomplete drainage (circulation device) and the resulting UF measurement error. PET12 as shown in Figure 3 has a L PA and Q L To improve the accuracy of the estimation and therefore the UF prediction accuracy, multiple, e.g., five, residence volumes (V) at multiple (five) different corresponding residence times, e.g., overnight, 4 hours, 2 hours, 1 hour, and 30 minutes, are measured. D ) measurements are used.

[0064] In one embodiment, the PET 12 of the present disclosure begins with a UF versus dwell time assessment performed over the course of two treatments (e.g., two nights or consecutively) by directly estimating the patient's fluid transport parameters and correlating the measured parameters with other PET results. The UF removed for a particular type of dialysate is measured by filling the patient with fresh dialysate, allowing the solution to dwell in the patient's peritoneum for a prescribed time, allowing the patient to drain, and subtracting the fill volume from the drain volume to determine the UF volume over that particular dwell time.

[0065] In one implementation, on the first night, using a standard dialysis fluid such as 2.5% dextrose Dianeal® dialysis fluid, the APD machine performs four separate 2-liter fill / drain cycles: a first cycle with a 30-minute dwell, a second cycle with a 60-minute (1-hour) dwell, a third cycle with a 120-minute (2-hour) dwell, and a fourth cycle with a 240-minute (4-hour) dwell. The total of all dwell times is about 7 hours and 30 minutes, consuming a typical total treatment time of about 9 and a half hours, including the time required for filling and draining. The APD machine records the fill volume, drain volume, and actual dwell time for each cycle. The fill volume may be slightly less than or more than 2 liters, depending, for example, on how much unused dialysate is actually present in the bag initially and how much the APD machine is able to empty the bag. In either case, the fill and drain volumes are accurately recorded so that the resulting calculated UF is also accurate.

[0066] In an alternative embodiment, to increase accuracy, the patient weighs the dialysate bag before filling and after draining. The weight values ​​can be wirelessly transmitted from the scale to the APD machine (as discussed in detail below). Alternatively, the patient manually enters the weight data. The APD machine subtracts the pre-fill weight from the post-drain weight to accurately determine the UF value that matches the actual dwell time.

[0067] The residence time can be (i) the time between the end of the fill and the start of the corresponding drain, (ii) the time between the start of the fill and the end of the corresponding drain, and (iii) in one preferred embodiment, the time between the end of the fill and the end of the corresponding drain. In any of the scenarios, the actual residence time will likely be slightly more or less than the specified residence time. For example, in scenarios (ii) and (iii), a kinked line during draining will lengthen the drain time and therefore the recorded residence time. In scenario (ii), a kinked line during filling will lengthen the fill time and therefore the recorded residence time. The APD machine records the actual residence time for use as shown below. The actual time rather than the specified time is used so that the difference between the actual residence time and the specified residence time does not introduce error into the UF prediction model.

[0068] On the next or second night, using standard (e.g., 2.5% dextrose Dianeal®) dialysate, the patient on the APD machine performs a single fill volume with a dwell of 480 minutes or 8 hours. The APD machine records the actual dwell time (according to any of scenarios (i) to (iii) above) and matches the actual dwell time with the actual UF recorded on the APD machine (e.g., via the APD or meter).

[0069] At the end of the two days, the APD machine will have recorded five UF / dwell time data points (more or fewer data points can be achieved, but the five dwell times above are acceptable and achievable over two standard eight-hour treatments). In one embodiment, the APD machine transmits the UF / dwell time data points to a server computer (FIGS. 15A, 15B, 16A, and 16B) located at the dialysis clinic 120 or doctor's office 110 where the remainder of the PET 12 will take place. Various embodiments for linking the APD machine to the server computer are illustrated herein, for example, an email link can be used to transport the data. In another embodiment, the APD machine records the five (or other number) data points on a patient data card that the patient inserts into the APD machine. The patient then takes the data card and attached data to the dialysis center 120 or doctor's office 110 to complete the PET 12.

[0070] The patient then goes to the dialysis center or doctor's office, for example, the next day. The patient is filled an additional time and typically drained after 4 hours. Blood and dialysate samples are taken, for example, at 2 hours and 4 hours. A second 4 hour dwell UF data point can be taken and compared to the first 4 hour dwell UF data point for additional accuracy. Alternatively, a second blood sample is taken at 4 hours, but the patient is drained, for example, at 5 hours, providing an additional UF dwell data point.

[0071] 3 illustrates a plot of UF data points for different actual dwell times. A server computer or other clinical software computer is programmed to fit a curve 30 to the five data points. Curve 30 fills in the gaps between the different recorded dwell periods (e.g., at 0.5 hours, 1 hour, 2 hours, 4 hours, and 8 hours) and thus predicts the UF removed for the particular dialysate and dextrose concentration used for any dwell period within and beyond the 8 hour range.

[0072] The osmotic gradient created by dextrose in the dialysis solution decreases over time as dextrose is absorbed by the body. Thus, the patient's ultrafiltration rate starts at a high level and decreases over time to the point where the rate actually becomes negative, so the patient's body begins to reabsorb fluid. Thus, the UF capacity as shown in the graph may actually decrease after a certain dwell time. One of the goals of this disclosure is to know the patient's optimal UF dwell time, which is dextrose concentration dependent, and may incorporate the optimal dwell time into the formulation, which is discussed in detail below.

[0073] In the illustrated embodiment, curve 30 predicts the UF removed for 2.5% dextrose. Once the curve is fitted to a particular patient, the kinetic model can be used to calculate the curve to predict the UF / dwell time for other dialysates and other dextrose concentrations, for example, for 1.5% and 4.25% dextrose concentrations. As shown in FIG. 3, for 2.5% dextrose, curve 30 has a maximum UF removal dwell time of about 300 minutes or 5 hours. Although 5 hours is probably too long a dwell time, the UF for a dwell time of 2 hours or 2.5 hours comes very close to the maximum UF dwell time. A dwell time of 2 hours comes even closer to the maximum for 1.5% dextrose. 4.25% dextrose is suitable for a longer dwell, as seen in FIG. 3. For example, a one-day exchange is a good application for 4.25% dextrose.

[0074] In addition to predicting the optimal UF, five or six UF data points, blood test, and dialysate test data are taken using a particular dialysate, such as 2.5% dextrose Dianeal® dialysate. Each of the UF, blood, and dialysate data is used to generate mass transfer area coefficient ("MTAC") data and hydraulic conductivity data to classify the patient's transport and UF characteristics. The MTAC and hydraulic conductivity data can then also be physiologically applied to other types of dialysates, such as 1.5 or 4.5% dextrose solutions, and to other different formulations, such as Extraneal® and Nutrineal® dialysates, offered by the applicant of the present disclosure. That is, curve 30 is shown for one concentration. However, once the kinetic model and L PA and Q L Once the V (from the PET test results) is known, the system 10 calculates the V according to the above algorithm for each solution type, dextrose concentration, residence time, and fill volume. D It is possible to calculate L of 1.0 (mL / min / mmol / L). PA value and Q of 0.8 ml / min L The values ​​were used to simulate curve 30 (2.5% dextrose) in FIG. 3 as well as the curves for 1.5% dextrose and 4.25% dextrose.

[0075] Dialysate volume V D Using the above algorithm for , kinetic modeling simulations were performed to generate the following data shown in Table 2, which shows a comparison of UF estimation and associated error using known PET and PET12. The data showed that PET12 significantly improved UF prediction accuracy compared to known PET.

[0076] [Table 2] (Automatic Dosage Plan Generation) As seen in FIG. 1, the system 10 includes a treatment dosing plan generation module 14. The dosing plan generation module 14 includes a number of predictive algorithms. The predictive algorithms use the above calculated patient transport and UF characteristics from the PET 12, target information, and other treatment input information to generate a dosing plan. In one embodiment, the dosing plan generation module 14 uses the treatment input information and the calculated patient transport and UF characteristics to generate all possible treatment dosing plans that meet the input target requirements. The dosing plans generated are numerous, as shown below. A prescription generation module 16 then filters the dosing plans generated in module 14 to produce a finite number of optimized prescriptions that can be performed on the APD machine for a specific patient.

[0077] FIG. 4A illustrates one data entry screen for the regimen generation module 14. The data entered into the screen of FIG. 4A is obtained from the PET 12. FIG. 4A provides PET 12 data entry for a clinical nurse at a dialysis center. The data includes dialysate UF measurements, dialysate lab test results (urea, creatinine, and glucose), and blood test results (serum urea, creatinine, and glucose). Specifically, the "Night Exchange" module of FIG. 4A provides night exchange data entry including: (i) % dextrose, (ii) solution type, (iii) volume of solution infused, (iv) volume of solution drained, (v) dwell time (s), (vi) dialysate urea concentration (lab test result from drained dialysate), and (vii) dialysate creatinine concentration (lab test result from drained dialysate). The "4 Hour Equilibration" module of FIG. 4A provides 4 hour exchange data input, typically obtained from a patient blood sample taken at the clinic, including (i) % dextrose, (ii) solution type, (iii) volume of solution infused, (iv) volume of solution drained, (v) infusion time, and (vi) drain time. The "Data" module of FIG. 4A provides 4 hour exchange data input, including (i) clinician inputs for serum #1 sample time (usually 120 minutes after dialysate infusion), urea, creatinine, and glucose concentrations, along with "Corrected Crt," which is the corrected creatinine concentration calculated by the software algorithm, and (ii), (iii), and (iv) for dialysates #1, #2, and #3, clinician inputs for sample time, urea, creatinine, and glucose concentrations, along with "Corrected Crt" and "CRT D / P" (Dialysate Creatinine / Plasma Creatinine) calculated by the software.

[0078] In FIG. 4B, the "Serum Concentration" module involves a blood test that is typically performed after regular APD treatment, preferably in the morning, leading to results being sent to a laboratory for analysis of creatinine, urea, glucose, and albumin. Serum concentrations (sometimes called plasma concentrations) are laboratory test results of blood urea, creatinine, and glucose concentrations. Patients with end-stage renal disease have much higher blood urea and creatinine concentrations than people with functioning kidneys. Glucose concentrations are important because they measure how much glucose the patient's body absorbs when using a dextrose-based solution. The "24-Hour Dialysate and Urine Collection" module in FIG. 4B shows that the patient has no residual renal function and therefore does not produce urine. Overnight collection data is used to calculate the patient's residual renal function ("RRF"), the results of APD treatment (fill, drain, and laboratory test results), as well as to measure the patient's height and weight to calculate the patient's body surface area ("BSA"). As seen in the example for day 2 of PET12 (8 hour dwell), 8000 milliliters of dialysate were infused into the patient and 8950 milliliters of dialysate were removed from the patient, resulting in a net UF volume of 950 milliliters. The dialysate is sent to the laboratory for analysis of urea, creatinine, and glucose. The "Weekly Clearance" module calculates the weekly urea Kt / V and weekly creatinine clearance ("CCL"), parameters used by physicians to analyze whether a patient has adequate clearance.

[0079] FIG. 4C of the Generate Dosage Plan feature 14 shows a sample screen where, using the data of screens 4A and 4B and stored algorithms, the system 10 calculates the mass transfer coefficient ("MTAC") and water transport parameters. RenalSoft™ software provided by the assignee of the present disclosure is one known software for calculating the data shown in FIG. 4C from the input data of FIG. 4A and 4B. Some of the data calculated and shown in FIG. 4C is used in the algorithm for the Generate Dosage Plan feature 14. Specifically, the Generate Dosage Plan algorithm uses the MTAC for urea, creatinine, and glucose, and hydraulic conductivity to generate a dosing plan.

[0080] FIG. 4D of the regimen generation feature 14 shows the clinician or physician the predicted drainage volume determined based on the hydraulic conductivity of FIG. 4C versus the actual UF measured from the PET 12. Results are shown for an overnight exchange (e.g., nights 1 and 2 of PET 12) and a 4-hour dwell test performed at the dialysis center 120 or physician's office 110. The difference between the actual drainage volume UF and the predicted drainage volume is calculated so that the clinician or physician can view the accuracy of the PET 12 and the prediction routines of FIGS. 4A-4D for drainage volume and UF. To generate the predicted drainage volume, the operator inputs the fluid absorption rate. The machine also calculates a fluid absorption value that is used in predicting the drainage volume. As seen in FIG. 4D, the software of the system 10 has calculated the fluid absorption rate to be 0.1 ml / min based on the values ​​entered from the patient's PET. As seen at the top of FIG. 4D, the actual drainage volume vs. predicted drainage volume for the overnight exchange was 2200 ml vs. 2184 ml. The 4 hour (daytime) predicted vs. actual output was 2179 ml vs. 2186 ml. The bottom of Figure 4D shows the actual vs. predicted output values ​​for the more common fluid absorption rate of 1.0 ml / min, which are not as close to each other as the values ​​for the 0.1 ml / min fluid absorption rate. The system can then request the clinician to enter the fluid absorption rate they would like to use for this patient when predicting UF, which will usually be somewhere in between, including 0.1 ml / min and 1.0 ml / min.

[0081] 5 illustrates one possible regimen calculation input table for the regimen generation feature 14. The regimen calculation input table inputs clinical target data including: (a) minimum urea clearance, (b) minimum urea Kt / V, (c) minimum creatinine clearance, (d) maximum glucose absorption, and (e) target UF (e.g., over a 24 hour period).

[0082] The table of FIG. 5 also inputs overnight treatment parameter data, such as (i) treatment time, (ii) total treatment volume, (iii) fill volume, (iv) dextrose percent for the selected solution type, and possibly (v) solution type, where dwell time and number of exchanges are calculated from (ii) and (iii). Dwell time can alternatively be set according to the results of PET 12 as discussed above, which can be used in combination with at least one other input, such as total time, total volume, and fill volume, to calculate remaining total time, total volume, and fill volume inputs. For example, if dwell time, total volume, and total time are set, system 10 can calculate fill volume per exchange and number of exchanges. The overnight treatment parameter inputs also include inputs for last fill, such as (i) dwell time, (ii) last fill volume, and (iii) dextrose percent for the selected solution type.

[0083] 5 also inputs diurnal treatment parameter data such as (i) treatment time, (ii) fill volume, (iii) number of cycles, (iv) dextrose percentage for the selected solution type, and possibly (v) solution type. Diurnal exchanges may or may not be performed.

[0084] The type of solution for nighttime and daytime therapy is selected from the solutions portion of the input table of FIG. 5, which inputs available dextrose concentrations, solution formulations (e.g., Dianeal®, Physioneal®, Nutrineal®, and Extraneal® dialysis solutions marketed by the applicant of the present disclosure). Bag size can be a weight concern, especially for elderly patients. Smaller bags may be required for regimens that use different last fill and / or daytime exchange solutions or dextrose levels. Smaller bags may also be required for regimens that require blending from two or more bags of standard dextrose concentrations (e.g., 2.0%, 2.88%, 3.38%, or 3.81% dextrose concentrations) listed under the solutions portion of the table of FIG. 5. Blending to produce customized dextrose concentrations is discussed below with respect to FIG. 14. Solution bag inventory management is also discussed below with respect to FIGS. 10 through 13.

[0085] The dosing regimen calculation input table of FIG. 5 also illustrates that many of the inputs have ranges, such as plus / minus ranges for clinical target data, and max / min / increment ranges for certain overnight and daytime treatment parameter data. Once the clinician or physician begins to complete the table of FIG. 5, the system 10 automatically fills in many of the other cells with suggested values ​​to minimize the amount of input. For example, the solutions available under solution data can be automatically filled in based on the solutions indicated as available by the dialysis center, which in turn is based on the portfolio of available solutions approved in a particular country. In another example, the system 10 can automatically adjust the fill volume increments of the overnight treatment parameter data to use all of the available solutions (e.g., when a 12 liter treatment is being evaluated, the number of cycles and fill volumes can range as follows: four 3000 mL fills, five 2400 mL fills, six 2000 mL fills, and seven 1710 mL fills). The system 10 allows the operator to change any of the suggested values ​​if desired.

[0086] The software of the system 10 calculates predicted outcomes for all possible combinations of parameters based on the ranges entered for each parameter. As seen in FIG. 5, some regimens have “suitable” predicted outcomes for urea clearance, creatinine clearance, and UF that meet or exceed the minimum criteria selected by the clinician. Other regimens do not. Selecting “Show only suitable regimens” speeds up the regimen generation process. Some patients may have hundreds of suitable regimens. Other patients may have only a few, or perhaps none at all. When none are suitable, it may be necessary to display all regimens so that a regimen that nearly meets the target requirements can be identified for filtering. Filtering when starting from all displayed regimens provides the clinician / physician maximum flexibility when trying to find the best prescription for a patient.

[0087] System 10 can feed all of the treatment combinations into the outcome prediction software, tabulate the results, and then system 10 can filter the table as described below in connection with prescription filtering module 16. One suitable software is RenalSoft™ software provided by the applicant of the present disclosure. The combinations take into account different ranges that are entered above into the dosage regimen calculation input table of FIG.

[0088] Table 3 below shows the first 10 results (out of a total of 270 results) for the set of data entered into the system software. Here, a 1.5% overnight dextrose solution is selected. No daytime exchanges are allowed. Results generated for standard PD therapy are shown, but can alternatively or additionally be generated for other types of PD therapy, such as cyclic therapy. Figure 5 has a checkbox that allows for either or both of continuous cycling peritoneal dialysis ("CCPD") or cyclic therapy (both APD therapies) to be included in the regimen generation process.

[0089] [Table 3] As stated, Table 3 illustrates 10 of the 270 valid combinations possible with a 1.5% overnight dextrose concentration. The same 270 combinations also exist for overnight dextrose concentrations of 2% dextrose, 2.5%, etc. As daytime fills are added, an equal number of valid combinations are created for each possible dextrose concentration. Additionally, the final fill dwell time can be varied to create even more valid combinations. (Prescription filtering) As indicated above, system 10 allows the physician / clinician to prescribe values ​​for clinical targets and treatment inputs such as patient fill volume, total treatment volume, total treatment time, etc., and generates a table, such as Table 3, containing all therapies that meet all of the clinical requirements. The table of treatments that meet all of the clinical requirements can then be automatically filtered and sorted based on parameters such as total nightly treatment time, treatment solution cost, treatment weight, etc.

[0090] The software uses one or more algorithms in combination with treatment combinations (e.g., of Table 3) and patient physiological data generated via PET 12 as shown in connection with Figures 4A through 4D to generate a predicted treatment outcome. Treatment combinations (e.g., of Table 3) that meet the clinical targets of Figure 5 are presented to a clinician, nurse, or physician as candidates to become a prescribed dosing regimen.

[0091] 6A and 6B illustrate examples of filters that a physician or clinician can use to eliminate a dosing regimen. In FIG. 6A, the minimum urea Kt / V removal is increased from 1.5 in FIG. 5 to 1.7 in FIG. 6A. In one embodiment, the range of +0 to -0.2 in FIG. 5 is automatically applied to the new minimum value set in FIG. 6A. Alternatively, the system 10 prompts the user to enter a new range or keep the same range. A Boolean "And" operator is applied to the new minimum urea Kt / V to specify that the values ​​covered by the applied range must be met in combination with other clinical targets.

[0092] In FIG. 6B, the minimum 24-hour UF clearance has been increased from 1.0 in FIG. 5 to 1.5 in FIG. 6B. In one embodiment, the range of +0 to -0.2 in FIG. 5 is again automatically applied to the new minimum value set in FIG. 6B. Alternatively, the system 10 prompts the user to enter a new daily UF range or keep the same UF range. Again, a Boolean "And" operator is applied to the new minimum 24-hour UF clearance, in combination with other clinical targets, to specify that the values ​​covered by the applied range must be met. Clinicians and patients are free to impose additional clinical and non-clinical requirements, such as solution cost, solution bag weight, glucose absorbed, overnight treatment time, daytime fill volume, overnight fill volume, etc.

[0093] Referring now to Figure 7A, there are shown dosing regimens that meet the clinical targets and other inputs of Figure 5, as well as the additional filtering of Figures 6A and 6B. Thus, each of the dosing regimens is predicted to remove at least 1.5 liters of UF daily and has a minimum urea Kt / V removal of greater than 1.5.

[0094] Regimen 36 is highlighted because it has the smallest daytime fill volume (patient comfort), the lowest solution weight (patient convenience), and the second lowest glucose absorption value (least food effect). Therefore, regimen 36 is selected and prescribed by the physician as the standard UF regimen.

[0095] The patient, clinician, and / or physician may also choose to approve one or more additional prescriptions that also fit the patient's lifestyle needs. For example, assume that the patient is a member of a bowling team during the winter months that competes in a league on Saturday nights. The patient drinks a little more than normal while socializing. The patient and his / her physician / clinician therefore agree that a treatment regimen that removes approximately 20% more UF should be administered on Saturday nights. Also, on bowling nights, the patient only has 7 hours to administer the treatment, let alone the standard 8 hour treatment. Thus, filtered potential prescription 34, highlighted in FIG. 7A, is approved as a higher UF prescription that uses a higher dextrose concentration to remove the excess UF, and does so in the required 7 hours.

[0096] Assume further that the patient lives in a southern state and does yard work on weekends during the summer months (no bowling leagues) and therefore loses significant amounts of fluid through sweating. The doctor / clinician and patient agree that on such days, less than 1.5 liters of UF should be removed. Because FIG. 7A shows only regimens that remove 1.5 liters or more of UF, further filtering is used to provide low UF regimens for possible selection as the low UF prescription.

[0097] The physician or clinician uses additional filtering on the 24 hour UF screen in FIG. 6C to restrict the previous range of daily UF that the regimen must meet. Here, the physician / clinician looks for regimens that have daily UF clearance of 1.1 liters or greater and 1.3 liters or less. The Boolean "And" operator is selected so that the treatment meets all of the other clinical requirements in FIGS. 5 and 6A.

[0098] Referring now to Figure 7B, there are shown dosing regimens that meet the clinical targets and other inputs of Figure 5, as well as the additional filtering of Figures 6A and 6C. Thus, each of the dosing regimens is predicted to remove between 1.1 and 1.3 liters of UF daily while meeting a minimum urea Kt / V removal above 1.5 and other clinical targets. The physician / clinician and patient then determine a cyclical treatment regimen 58 (highlighted) that requires no daytime changes and the shortest overnight treatment time. The physician then prescribes the treatment.

[0099] 8A-8C, three agreed upon high UF, standard UF, and low UF prescriptions are illustrated, respectively. The prescriptions are named (see upper right corner) so as to be easily recognizable by the patient 102, the physician 110, and the clinician 120. Although three prescriptions are illustrated in this example, the system 10 can store any other suitable number of prescriptions as discussed herein. The system 10, in one embodiment, downloads the prescription parameters to a data card that is inserted into the APD machine 104 and transfers the prescription to the non-volatile memory of the APD machine. Alternatively, the prescription is transferred to the APD machine 104 via a wired data communication link, such as the Internet. In one embodiment, the patient is free to choose which prescription is to be performed on a given day. In an alternative embodiment, a data card or data link transfer of the prescription is entered into the memory of the dialysis instrument so that the instrument automatically performs the prescribed treatment each day. These embodiments are discussed in more detail below in connection with the prescription recall and adjustment module 26. In either case, when the patient begins any of the treatments, the system 10 provides instructions as to which solution bag to connect to the disposable cassette for delivery, since the treatments may use different solutions.

[0100] 9A to 9E illustrate another filtering embodiment of module 16. FIG. 9A illustrates the filtered settings on the left and the corresponding results on the right resulting in 223 possible dosing regimens. In FIG. 9B, the clinician further filters the dosing regimens by limiting the daytime fill volume (patient comfort) to 1.5 liters. Such filtering reduces the possible dosing regimens to 59. In FIG. 9C, the clinical software further filters the dosing regimens by reducing the dosing regimens to 19. In FIG. 9D, the clinical software further filters the available dosing regimens by reducing the absorbed glucose to 500 Kcal / day. Such action reduces the available dosing regimens to 3.

[0101] Figure 9E shows three filtered regimens that can be prescribed by the physician or abandoned to allow another filtering run to be performed. The runs of Figures 9A to 9D show that expedient prescription optimization occurs once the patient's physiological characteristics are known. Figures 9A to 9D also show a preferred list of possible filtering criteria.

[0102] (Inventory Tracking) 10-13, one embodiment of the inventory tracking subsystem or module 18 of the system 10 is illustrated. As discussed herein, the system 10 generates agreed upon prescriptions, such as high UF, standard UF, and low UF prescriptions, as shown in connection with FIGS. 8A-8C. Different prescriptions require different solutions, as seen in FIG. 10. FIG. 10 shows that the standard UF prescription uses 12 liters of 1.5% Dianeal® dialysate and 2 liters of Extraneal® dialysate. The high UF prescription uses 15-18 liters of 1.5% Dianeal® dialysate and 2 liters of Extraneal® dialysate (depending on the dialysis alternative used). The low UF prescription uses 12 liters of 1.5% Dianeal® dialysate and 3 liters of 2.5% Dianeal® dialysate.

[0103] FIG. 11 shows an example screen that the server of the dialysis center 120 may display for a patient with the three prescriptions described above. The screen of FIG. 11 shows the minimum base supply inventory required for the three prescriptions over a delivery cycle. The screen of FIG. 11 shows that the patient will be provided with the solution required to perform 32 standard UF prescription treatments. The patient will be provided with the solution required to perform six high UF prescription treatments. The patient will also be provided with the solution required to perform six low UF prescription treatments. The patient will also be provided with one "Ultrabag" case (six 2.5 liter bags). The stem of the Y-shaped Ultrabag tubing set can be connected to the patient's transfer set. An empty bag is attached to one leg of the Y and a full bag is pre-attached to the other leg of the Y. Ultrabags are used to perform CAPD exchanges when the APD machine breaks down, when power is lost and the APD machine cannot operate, or when the patient is traveling and supplies do not arrive on time.

[0104] In addition, the patient is also provided with 45 disposable sets (one to be used for each treatment) that include a disposable pump cassette, bag lines, patient lines, drain lines, heater bags, and associated clamps and connectors. Patients are provided with dialysis solutions in low (1.5%), medium (2.5%), and high (4.25%) dextrose concentrations, allowing the patient to remove more or less fluid by switching which dextrose concentration is used. The versatility of the formulation (including mixing) can increase the total number of bags needed in a given month to approximately 45 days worth of solution.

[0105] The patient is also provided with 45 caps or flexicaps, which are used to fit over the patient's transfer set when the patient is not connected to a circulatory system. The flexicaps contain a small amount of povidone-iodine to minimize the chance of bacterial growth from touch contamination.

[0106] Figure 12 shows an example screen that the dialysis center 120 may display for a patient with the three prescriptions listed above. The screen in Figure 12 shows the expected and actual patient inventory when a new delivery of inventory is made. That is, the screen in Figure 12 shows the inventory that the server computer believes will be in the patient's home when the delivery person arrives. In an embodiment, the server computer expects that when the courier arrives at the patient's home, the patient will already have (i) five cases (two bags per case) of 1.5% Dianeal® dialysis solution containing 6 liter bags, (ii) one case (four bags per case) of 2.5% Dianeal® dialysis solution containing 3 liter bags, (iii) one case (six bags per case) of Extraneal® dialysis solution containing 2 liter bags, (iv) 24 cases (out of a case of 30) of disposable sets, each containing the device described above, (v) two (out of a case of 6) 2.5 liter Ultrabags of 1.5% dialysis solution, and six (out of a case of 30) caps or flexicaps.

[0107] FIG. 13 shows an example screen that the server of the dialysis center 120 may display for a patient with the three prescriptions described above. The screen of FIG. 13 shows the actual inventory that will be delivered to the patient. That is, the screen of FIG. 13 shows the inventory difference between what the server computer thinks the patient will have at the start of the inventory cycle and what the server computer thinks the patient will have at their home when the courier arrives. In the example, the patient needs: (i) 88 6-liter bags of 1.5% Dianeal® dialysate, 10 at home, translating to a need of 78 bags or 39 cases (2 bags per case), (ii) 6 3-liter bags of 2.5% Dianeal® dialysate, 4 at home, translating to a need of 2 bags or 1 case (4 bags per case, 2 extra bags delivered), (iii) 38 2-liter bags of Extraneal® dialysate, 6 at home, translating to a need of 32 bags or 6 cases (6 bags per case, 4 extra bags delivered), and (iv) 10 2-liter bags of Extraneal® dialysate, 10 at home, translating to a need of 10 bags or 10 cases (10 bags per case, 1 extra bag delivered). (iv) 45 disposable sets, 24 at home, translating to a need of 21 or 1 case (30 per case, 9 extra Flexicaps delivered); (v) 6 2.5 liter 1.5% Ultrabags, 2 at home, translating to a need of 4 bags or 1 case (6 bags per case, 2 extra Ultrabags delivered); and (vi) 45 Flexicaps, 36 at home, translating to a need of 9 or 1 case (36 per case, 27 extra Flexicaps delivered).

[0108] In one embodiment, the dialysis center server database of inventory tracking module 18 maintains and knows (a) how much of each dialysate and other supplies the patient should have at the beginning of a delivery cycle, (b) the patient's different prescriptions, the solutions used with each, and the number of times each prescription is used over the delivery cycle, and (c) therefore how much of each dialysate the patient should use over the delivery cycle. Knowing the above, the inventory tracking server can calculate how much of each dialysate and other supplies needs to be delivered on the next delivery date. It is possible that the patient has consumed more or less of one or more solutions than other items than expected. For example, the patient may have punctured a solution bag and had to discard it. The patient may leave a solution bag or other item behind. Both cases will consume more inventory than expected. On the other hand, the patient may skip one or more treatments during the delivery cycle, resulting in less inventory being consumed than expected.

[0109] In one embodiment, the inventory tracking module or subsystem 18 of the system 10 expects that the estimated amount of solution and other supplies is close to the actual amount needed. If too much inventory is delivered (the patient uses less than prescribed), the courier can scan or otherwise note the additional inventory so that it can be delivered to the patient and stored in the inventory server memory. For the next cycle, the system 10 updates (e.g., increases) how much of each dialysate and other supply the patient should have at the beginning of the delivery cycle, as per (a) above. Alternatively, the courier delivers only the amount of inventory needed to make the patient's actual inventory at the beginning of the delivery cycle equal to the expected inventory in (a) above. If insufficient inventory is scheduled for delivery (e.g., the patient loses or damages solution or related supplies), the courier takes extra inventory to make the patient's actual inventory at the beginning of the delivery cycle equal to the expected inventory in (a) above.

[0110] The inventory subsystem 18 of the system 10, in one embodiment, maintains additional information such as the individual cost of the supplies, the weight of the supplies, and substitutes for the required supplies if the patient runs out of the required supplies during a delivery cycle. As shown above in Figures 7A and 7B, the dosing regimen generation software, in one embodiment, uses or generates the weight and cost data as a factor or potential factor in determining which dosing regimen is selected as the prescription. The server at the dialysis center 120 downloads (or transfers via a data card) the substitute solution data to the patient's APD circulation machine. In one implementation, when the patient begins treatment, the patient is notified of the specific solution bag required for that particular prescription for that day. If the patient runs out of a type of solution, the system can provide a substitute based on the solution held in the current inventory.

[0111] (mixed with dextrose) As shown above in FIG. 5, the system 10 contemplates using multiple different dextrose concentrations for each of the different brands or types of dialysate available, which increases the doctor / clinician's options in optimizing the prescription for the patient. The tradeoff with dextrose is generally that a higher concentration of dextrose removes more UF, but has a higher caloric input, making patient weight control more difficult. The reverse is also true. Dialysis fluids (at least some types) are provided with different standard dextrose concentrations, including 0.5%, 1.5%, 2.5%, and 4.25%. As seen in FIG. 6, the night dextrose, last fill dextrose, and day dextrose can be selected to have any of the standard percentages listed above, or to have a blended dextrose concentration of 2.0%, 2.88%, 3.38%, or 3.81%. The system 10 uses a dialysis instrument 104 to blend the standard percentages to create the blended percentages. Each of the standard dextrose concentration dialysates is approved by the Federal Drug Administration ("FDA"), and since the blended dextrose concentrations are within the approved concentrations, it is believed that such blends would readily meet FDA approval.

[0112] [Table 4] Using the 1:1 or 1:3 mixes shown in Table 4 produces more dextrose solution and provides more treatment options for clinicians. At the same time, these mix ratios use all of the solution in the container and do not create waste.

[0113] Referring now to FIG. 14, a dialysis instrument 104 illustrates one device capable of producing a mixed dextrose concentration dialysate. The dialysis instrument 104 is illustrated as a HomeChoice® dialysis instrument marketed by the present dialysate applicant. The operation of the HomeChoice® dialysis instrument is described in a number of patents, including U.S. Pat. No. 5,350,357 ("the '357 patent"), the entire contents of which are incorporated herein by reference. Generally, the HomeChoice® dialysis instrument receives a disposable fluid cassette 50 that includes a pump chamber, a valve chamber, and fluid flow paths that interconnect and fluidly communicate with various tubes, such as a shuttle heater bag tube 52, a drain tube 54, a patient tube 56, and dialysate supply tubes 58a and 58b. Although FIG. 14 illustrates two supply tubes 58a and 58b, the dialysis instrument 104 and cassette 50 can support three or more supply tubes, and thus three or more supply bags. Additionally, as seen in the '357 patent, one or both supply tubes 58a and 58b can be Y-connected to two bags if more supply bags are needed.

[0114] In one embodiment, the system 10 pumps fluid from a supply bag (not shown) through one of the tubing 58a or 58b and the cassette 50 to a warming bag (not shown) located on a heater tray of the APD 104. The warming bag provides an area for mixing the solution before delivery to the patient. In such a case, the warming bag may be fitted with one or more conductive strips that allow temperature compensated conductivity measurements of the mixed solution to be taken to ensure that the solution is properly mixed. Alternatively, the APD 104 uses in-line heating, where mixing occurs within the tubing and the patient's peritoneum.

[0115] To operate cassette 50, the cassette is compressed between a cassette actuation plate 60 and a door 62. The '357 patent describes a flow management system ("FMS") that calculates the amount of fluid pumped from each pump chamber (of which cassette 50 includes two in one embodiment) after each pump stroke. The system adds the individual volumes determined via the FMS to calculate the total amount of fluid delivered to and removed from the patient.

[0116] The system 10 considers using the FMS to balance pump strokes from different standard dextrose supplies to achieve the desired blended dextrose. As seen in Table 4 above, a 1.5% standard dextrose supply bag can be connected to supply line 58a while a 4.25% standard dextrose supply bag is connected to supply line 58b. The dialysis machine 104 and cassette 50 use the FMS to pump dialysate from each supply bag in a 50 / 50 ratio to achieve a 2.88% blended dextrose ratio. In another embodiment, a 2.5% standard dextrose supply bag is connected to supply line 58a while a 4.25% standard dextrose supply bag is connected to supply line 58b. The dialysis machine 104 and cassette 50 use the FMS to pump dialysate from each supply bag in a 50 / 50 ratio to achieve a 3.38% blended dextrose ratio. In a further embodiment, a 2.5% standard dextrose supply bag (e.g., a 2 L bag) is connected to supply line 58a, while a 4.25% standard dextrose supply bag (e.g., a 6 L bag) is connected to supply line 58b. Dialysis machine 104 and cassette 50 use the FMS to pump dialysate from each supply bag in a 25 / 75 (2.5% to 4.25%) ratio to achieve a 3.81% blended dextrose ratio.

[0117] The first two examples include the connection of a 6 liter bag of dialysate to each of lines 58a and 58b. In a third example, a 3 liter 2.5% standard dextrose supply bag is connected to supply line 58a while a 3 liter 4.25% supply bag is Y-connected to the 4.25% supply bag, which in turn is connected to supply line 58b. The dialysis machine 104 and cassette 50, in one embodiment, deliver dialysate from each supply bag to a heater bag, which allows the two different dextrose dialysates to mix thoroughly before being delivered from the heater bag to the patient. Thus, the system 10 can achieve the mixed dialysate ratio shown in FIG. 6 and other ratios by delivering different standard dextrose concentrations in different ratios using the FMS. The dialysis instrument 104, in one embodiment, is configured to read the bag identifiers to ensure that the patient connects the right dialysate and the right amount of dialysate. Systems and methods for automatically identifying the type and volume of dialysate in a supply bag are described in commonly assigned U.S. patent application Ser. No. 11 / 773,822, entitled "Radio Frequency Auto-Identification System," filed Jul. 5, 2007 (the "'822 Application"), the entire contents of which are incorporated herein by reference. The '822 Application discloses one preferred system and method for ensuring that the correct supply bag is connected to the correct port of the cassette 50. The system 10 may alternatively use a barcode reader that reads a barcode located on the bag or container to identify the type / volume of solution. If a wye connection is required, the APD machine 104 may prompt the patient to ensure that a wye connection to an additional bag is made.

[0118] U.S. Patent No. 6,814,547 ("the '547 patent"), assigned to the assignee of the present disclosure, discloses a pump mechanism and volume control system using a combination of pneumatic and mechanical actuation, in conjunction with Figures 17A and 17B and the associated written description incorporated herein by reference, where volume control is based on precision control of a stepper motor actuator and a known volumetric pump chamber. It is contemplated to use this system in place of the FMS of the '357 patent to achieve the blended dextrose concentrations described above.

[0119] (Prescription download and treatment data upload communication module) 15A, network 100a illustrates one wireless network or communications module 20 (FIG. 1) for communicating PET, regimen generation, prescription filtering, inventory tracking, trending, and prescription modification information (below) between patient 102, physician 110, and dialysis center 120. Here, patient 102 operates dialysis equipment 104, which communicates wirelessly with router 106a, which is in wired communication with modem 108a. Physician 110 operates physician's (or nurse's) computer 112a (which may also be connected to a physician's network server), which communicates wirelessly with router 106b, which is in wired communication with modem 108b. Dialysis center 120 includes multiple clinician's computers 112b through 112d connected to clinician's network server 114, which communicates wirelessly with router 106c, which is in wired communication with modem 108c. Modems 108a through 108c communicate with each other via the Internet 116, a wide area network ("WAN"), or a local area network ("LAN").

[0120] FIG. 15B illustrates an alternative wired network 100b or communications module 20 (FIG. 1) for communicating PET, regimen generation, prescription filtering, inventory tracking, trending, and prescription modification information (below) between a patient 102, a physician 110, and a dialysis center 120. Here, the patient 102 includes a dialysis instrument 104 in wired communication with a modem 108a. The physician 110 operates a physician's (or nurse's) computer 112a (which may also be connected to a physician's network server), which is in wired communication with a modem 108b. The dialysis center 120 includes multiple clinician's computers 112b through 112d, which are in wired communication with a modem 108c. The modems 108a through 108c again communicate with each other via the Internet 116, a WAN, or a LAN.

[0121] In one embodiment, the data points of curve 30 of FIG. 3 are generated at instrument 104 and sent to physician 110 or dialysis center 120 (likely dialysis center 102), which stores software that fits curve 30 to the data points. The patient then goes to dialysis center 120 to have blood work done and to complete a PET as discussed herein. Software configured to execute the PET and dosing regimen generation screens of FIGS. 4A, 4B, 5A, 5B, and 6 can be stored on clinician's server 114 (or individual computers 112b-112d) of clinic 120 of system 100a or 100b or on physician's 110's computer 112a (likely clinic 120). Similarly, software configured to execute the filtering and prescription optimization screens of Figures 6A to 6C, 7A, 7B, 8A to 8C, and 9A to 9E can be stored on the clinician's server 114 (or individual computers 112b to 112d) or physician's 110's computer 112a at the clinic 120 of systems 100a and 100b.

[0122] In one embodiment, the dialysis center 120 performs a PET, generates a dosing regimen, and filters the prescription. The dialysis center 120 via the network 100 (referring to one or both of the networks 100a and 100b) sends the prescription to the doctor 110. Filtering can be done with input from the patient via the network 100, a phone call, or a personal visit. The doctor reviews the prescription and approves or disapproves. If the doctor disapproves, the doctor can send additional or alternative filtering criteria back to the dialysis center 120 via the network 100 to perform additional filtering to optimize the new set of prescriptions. Finally, the dialysis center 120 or doctor 110 sends the approved prescription to the device 104 of the patient 102 via the network 100. Alternatively, the dialysis center 120 or doctor 110 stores the approved prescription, and the device 104 queries the dialysis center 120 or doctor 110 over the network 100 on a given day to determine which prescription to execute. The prescription may also alternatively be transferred via a data card.

[0123] In an alternative embodiment, the dialysis center 120 performs the PET and generates a dosing regimen. The dialysis center 120 transmits the dosing regimen to the physician 110 over the network 100. The physician reviews the dosing regimen and filters it to approve or disapprove until a set prescription arrives. Filtering can again be done with input from the patient over the network 100, a phone call, or a personal visit. If the physician disapproves, the physician can do additional filtering to optimize a new set prescription. The physician 110 now transmits the approved prescription to the device 104 and the patient 102 over the network 100. Alternatively, the physician 110 stores the approved prescription and the device 104 queries the physician 110 over the network 100 on a given day to determine which prescription to execute. Further alternatively, the physician 110 transmits the approved prescription to the dialysis center 120 over the network 100, the dialysis center stores the approved prescription, and the device 104 queries the dialysis center 120 over the network 100 on a given day to determine which prescription to dispense.

[0124] As discussed above, the dialysis center 120 is likely in a better position than the physician 110 to handle the inventory tracking module or software 18. Thus, in one embodiment, the dialysis center 120 stores software configured to execute the inventory tracking screens of Figures 10 through 13. The dialysis center 120 communicates with the dialysis equipment 104 and the patient 102 via the network 100 and controls inventory for the patient's approved prescriptions.

[0125] 16A, network 100c illustrates a further alternative network or communication module 20 (FIG. 1). Network 100c also illustrates patient data collection module 22 of FIG. 1. It should be understood that the principles of patient data collection discussed with respect to network 100c are also applicable to networks 100a and 100b. Network 100c includes a central clinical server 118, which may be stored in a separate location, such as one of the dialysis centers 120, one of the physician offices 110, or a facility operated by the provider of system 10. Each of patients 102a and 102b, physicians 110a and 110b, and dialysis centers 120a and 120b communicate with clinical server 118 via Internet 116. The clinical server 118 stores and executes software associated with any of the PET, regimen generation, prescription filtering, inventory tracking, trending, and prescription modification (below) modules and facilitates communication between patients 102a / 102b, physicians 110a / 110b, and dialysis centers 120a / 120b.

[0126] The clinical server 118, in one embodiment, receives PET data from one of the dialysis centers 120 (referred to as either center 120a or 120b) and transmits it to the clinical server 118. The UF data points in FIG. 3 can be transmitted to the clinical server 118 either directly from the patient 102 (referred to as either patient 102a or 102b) or from the dialysis center 120 via the patient 102. The clinical server 118 fits a curve 30 (FIG. 3) to the data points, generates a dosing regimen, and (i) filters the regimen (possibly with patient input) into an optimized prescription for the physician 110 (referred to as either physician 110a or 110b) to approve or disapprove, or (ii) transmits the regimen to the physician 110 to filter the regimen (possibly with patient input) into an optimized prescription.

[0127] In either case, the approved prescription may or may not be sent to the associated dialysis center 120. For example, if the associated dialysis center 120 runs the inventory tracking module 18 of the system 10, the dialysis center 120 needs to know the prescription in order to know what solutions and supplies are needed. Also, if the system 10 is operated such that the patient's dialysis equipment 104 (referring to either equipment 104a or 104b) queries the dialysis center 120 as to which prescription it will run on a given day, the dialysis center 120 needs to know the prescription. Alternatively, the patient's dialysis equipment 104 queries the clinical server 118 daily as to which prescription it will run. It is also possible for the clinical server 118 to run the inventory tracking module 18 of the system 10, in which case it can delegate the acquisition of PET data to the associated dialysis center 120.

[0128] The clinical server 118 may be a single server, for example a national server, since different countries have different sets of approved dialysis solutions. However, the clinical server 118 may serve more than one country if two or more countries have the same set of dialysis solutions and a common language. The clinical server 118 may be a single server or may have spoke or hub links between multiple servers.

[0129] 16B, network 100d includes a central clinical server 118 stored at or near one of the dialysis centers 120. Dialysis centers 120 store physician offices 110 and patient service areas 90, each of which includes one or more computers 112a through 112d. Patient service areas 90, in one embodiment, include a server computer 114, which communicates with the clinical server 118 via a local area network ("LAN") 92 for dialysis centers 120. Clinical server 118, in turn, includes a clinical web server in communication with the Internet 116 and LAN 92, a clinical data server in communication with LAN 92, and a clinical database in communication with the clinical data server.

[0130] Each of the patients 102a and 102b communicates with a clinical server 118, for example, via the Internet 116. The clinical server 118 stores and executes software associated with any of the PET, regimen generation, prescription filtering, inventory tracking, trending, and prescription modification (below) modules, and facilitates communication between the patients 102a / 102b, the physicians 110, and the dialysis centers 120. Other dialysis centers 120 can communicate with the center-based clinical server 118 over the Internet 116. Any of the systems 100a-100d can also communicate with an APD machine manufacturer's service center 94, which can include, for example, a service database, a database server, and a web server. The manufacturer's service center 94 tracks machine problems, delivers new equipment, etc.

[0131] (Data collection features) The PET module 12, the dosing regimen generation module 14, and the prescription optimization or filtering module 16 output data that is used by the network 100 (which here additionally refers to networks 100c and 100d) to perform dialysis treatment. In this regard, the networks 114 and 118 of the system 10 use the results from the analysis already performed. As seen in the network 100c, the system 10 also generates real-time daily patient data that is fed to the server 114 or 118 (at the center 120) for tracking and analysis. This real-time data, together with the treatment parameter inputs and the treatment target inputs, constitute the data collection module 22 (FIG. 1) of the system 10.

[0132] Each dialysis machine 104 (referring to one or both of machines 104a and 104b) includes a receiver 122 as illustrated in FIG. 16A. Each receiver 122 is coded with an address and a personal identification number ("PIN"). The patient is equipped with a blood pressure monitor 124 and a weight scale 126. The blood pressure monitor 124 and the weight scale 126 are each provided with a transmitter that wirelessly transmits patient blood pressure data and patient weight data, respectively, to the receiver 122 of the dialysis machine 104.

[0133] The address and PIN ensure that information from the blood pressure monitor 124 and weight scale 126 reaches the correct dialysis machine 104. That is, if machines 104a and 104b and associated blood pressure monitors 124 and weight scales 126 are within range of each other, the address and PIN ensure that dialysis machine 104a receives information from the blood pressure monitor 124 and weight scale 126 associated with dialysis machine 104a, while dialysis machine 104b receives information from the blood pressure monitor 124 and weight scale 126 associated with dialysis machine 104b. The address and PIN also ensure that dialysis machine 104 does not receive unrelated data from an unwanted source. That is, if data from an unwanted source is somehow transmitted using the same frequency, data rate, and communication protocol of receiver 122, but the data fails to provide the correct device address and / or PIN, receiver 122 will not receive the data.

[0134] The wireless link between the blood pressure monitor 124, the weight scale 126, and the dialysis machine 104 allows the devices to be conveniently located relative to each other in the patient's room or home; that is, they are not coupled to each other via cords or cables. Alternatively, the blood pressure and weight data are manually entered into the instrument 104. However, the wireless link also ensures that the blood pressure and weight data are automatically transferred to the dialysis machine 104 as they are taken. It is contemplated that the patient takes his or her blood pressure and weighs himself or herself before (during or immediately after) each treatment to provide blood pressure and weight data points for each treatment. The data collection module 22 is alternatively configured to have a wired connection between the blood pressure monitor 124 and the instrument 104, and between the weight scale 126 and the instrument 104.

[0135] Another data point generated for each treatment is the amount of ultrafiltration ("UF") removed from the patient. All three data points for each treatment, blood pressure, patient weight, and UF removal, can be stored in the memory of the dialysis machine 104 or on a data card and / or transmitted to a remote server 114 or 118. The data points are used to generate performance trends, as will now be described.

[0136] Any one or combination of processing and memory associated with any of the dialysis equipment 104, the doctor's (or nurse's) computer 112, the clinician's server 114, the clinical web server 118, or the manufacturer's service center 94 may be referred to as a "logic implementer."

[0137] (Trend and Condition Generation) The trending and statistics module 24 (FIG. 1) of the system 10 as seen herein calculates short-term and long-term running averages of daily UF as well as other patient data as shown below. Only monitoring the actual measured daily UF introduces too much noise due to dialysis instrument 104 residuals and measurement errors. Therefore, the trending regime of the module or feature 24 looks at and trends daily data, as well as data averaged over one or more time periods.

[0138] (Trend and condition generation using multiple patient parameters) The trend module 24, in one embodiment, uses the following equations to form the short-term and long-term moving averages: UF ma (n)=1 / k*(UF(n)+UF(n-1)+UF(n-2)···+UF(nk)). For short-term moving averages, typical values ​​of k can be 3-14 days, e.g., 7 days. For long-term moving averages, typical values ​​of k can be 15-45 days, e.g., 28 days.

[0139] The difference between the target UF and the actual measured UF is described as follows: ΔUF=UF target -UF ma UF target is a UF prescribed by a doctor, UF ma is the moving average of the actual daily UFs measured (2-3 days for daily measurements or a short-term moving average). ΔUF can be positive or negative. ΔUF / UF target If the absolute value of exceeds a condition threshold preset by the physician, the system 10 alerts the patient and physician 110 and / or clinician 120 (at the machine 104 level or via the server 114 / 118), which can trigger a prescription adjustment or other response, as discussed below.

[0140] The warning thresholds can accommodate UF anomalies so as not to cause the system 10 to false-trigger or be overly sensitive to day-to-day UF variations that may be significant in nature (e.g., due to measurement errors and residual amounts). The following equation illustrates an example where the system 10 requires a certain deviation over several days. δ(generated warnings)=|△UF / UF target |>X% in Y days X% can be preset by a physician or clinician, with a typical value being 30 to 50 percent. Y can also be preset by a physician or clinician, with a typical value being 3 to 7 days.

[0141] The following equation corresponds to the likelihood of UF for patients who skip dialysis or who are consistently much lower than the target UF.

[0142]

number

[0143] Example #1: P=150%, Q=3 days Generate a warning if on day 1, patient skips treatment and UF error = 100%, on day 2, patient skips treatment and UF error = 100%, on day 3, patient takes treatment and UF error = 10%, cumulative UF error = 210% > 150%.

[0144] Example #2: P=150%, Q=3 days If on day 1, the patient skips a treatment and UF error = 100%, on day 2, the patient takes a treatment and UF error = 20%, on day 3, the patient takes a treatment and UF error = 10%, and the cumulative UF error = 130% < 150%, then no warning is generated.

[0145] 17 through 21 show trend screens 128, 132, 134, 136, and 138, respectively, that may be displayed to the patient on a display device 130 of the dialysis instrument 104 and / or on a computer monitor of the physician 110 or dialysis center 120. It is contemplated that trends may be generated in any of these locations, as desired. The main trend screen 128 of FIG. 17 allows the patient to select to view, for example, (i) pulse and pressure trends, (ii) recent treatment statistics, (iii) UF trends, and (iv) weight trends. The patient may access any of the screens via touch screen input, via a membrane-type or other type of switch associated with each selection, or via a knob or other selector that allows one of the selections to be highlighted after which the patient presses a "select" button.

[0146] When the patient selects the pulse and pressure trend selection on the main trends screen 128, the display device 130 displays the pulse and pressure trend screen 132 of FIG. 18. Pulse (heart rate, line with ●), systolic pressure (line with ▲), and diastolic pressure (line with ■) are shown over a one month period in mmHg. Selection options on the pulse and pressure trend screen 132 include (i) returning to the main trends screen 128, (ii) alternatively viewing weekly trends for pulse, systolic pressure, and diastolic pressure, and (iii) advancing to the next trends screen 134. One or more therapies administered during the trend period, i.e., therapy number 1 (e.g., standard UF), are also shown.

[0147] When the patient selects the next trend selection on the pulse and pressure trend screen 132, the display device 130 displays a recent therapy trend or statistics screen 134 as seen in FIG. 19. FIG. 19 shows the actual values ​​of UF removed (in milliliters, including total and breakdown UF for daytime and nighttime exchanges), cumulative hold time (in hours, seconds, including total and breakdown hold time for daytime and nighttime exchanges), drained volume (in milliliters, including total and breakdown volumes for daytime and nighttime exchanges), and fill volume (in milliliters, including total and breakdown volumes for daytime and nighttime exchanges). The recent therapy trend or statistics screen 134 as seen in FIG. 19, in one embodiment, shows statistics from previous therapy. The screen 134 alternatively includes a log option that allows the patient to view the same information for previous therapy, for example, therapy up to one month ago, or therapy since the last full set of prescriptions was downloaded. Selection options displayed on the Recent Treatment Trends or Statistics screen 134 include (i) returning to the main trends screen 128, (ii) returning to the previous trends screen 132, and (iii) advancing to the next trends screen 136.

[0148] When the patient selects the next trend selection on the Recent Treatment Trends or Statistics screen 134, the display device 130 displays a UF Trends screen 136 as seen in FIG. 20. The UF Trends screen 136 shows the target UF line and the measured UF line over a one month period in milliliters. Selection options on the UF Trends screen include (i) returning to the main trends screen 128, (ii) viewing the weekly UF trend, monthly UF trend, or three month UF trend as long as data is available, and (iii) proceeding to the next trends screen 138. Treatments administered during the UF trend period are also shown.

[0149] When the patient selects the next trend selection on the UF trends screen 136, the display device 130 displays a patient weight trends screen 138 as seen in FIG. 21. The patient weight trends screen 138 shows a measured weight ("BW") line over a one month period in pounds. Selection options on the patient weight trends screen 138 include (i) returning to the main trends screen 128 and (ii) going to the next screen. Treatments administered during the BW trend period are also shown.

[0150] The alternative trend charts of Figs. 22 and 23 display actual days on the x-axis. These trends can be reserved for the physician 110 and / or dialysis center 120, or can additionally be accessible by the patient, meaning that alerts can be generated from the APD device 104 to the physician and / or clinician, or from a server computer to the physician, clinician, and / or patient. The alternative trend charts of Figs. 22 and 23 show the patient's expected UF value or UF target based on the patient's last PET result. If the difference between the expected PET UF and the actual UF increases beyond a value that the physician or clinician determines to be significant, the clinician can order a new PET, with or without laboratory testing. That is, the patient can perform the UF portion of the PET as described in connection with Figs. 2 and 3, and bring the drainage volume to the dialysis center 120. U.S. patent application Ser. No. 12 / 128,385, entitled "Dialysis System Having Automated Effluent Sampling And Peritoneal Equilibration Test," filed May 28, 2008, the entire contents of which are incorporated herein by reference, discloses an automated PET that provides an effluent sample that the patient can take to a dialysis center 120 so that the sample can be analyzed for urea clearance, creatinine clearance, etc.

[0151] The alternative trend charts of Figures 22 and 23 also show which treatment regimen was used on a given day, as seen on the right side of the figures (for example, assume that treatment regimen 0 is low UF, treatment regimen 1 is standard UF, and treatment regimen 2 is high UF). As seen in Figures 22 and 23, the standard UF regimen is administered on all days except day 2, when the high UF regimen is administered. In Figure 22, the 30-day moving average (line with ●) notably shows that, in general, patient treatments are meeting UF goals. In Figure 23, the 30-day moving average (line with ●) shows that after October 2, 2006, patient treatments began to not meet UF goals and got progressively worse. Also, the entire 30-day trend line for October 2006 slopes towards less and less UF removal. Now, a skilled clinician would view such a trend as potentially due to a loss of renal function in the patient and (in conjunction with the physician) would order a new PET, provide a new prescription, or closely monitor the patient's UF capabilities to see if the trend continues. Alternatively, the clinician / physician would prescribe higher UF prescriptions more frequently in an attempt to reverse the negative UF trend.

[0152] As alluded to above, a doctor or clinician probably does not want to be notified when a day falls below the lower limit. Therefore, the UF data needs to be filtered. The filter considers all three in the algorithm: the daily UF value, the 7-day rolling average UF (line with ▼), and the 30-day rolling average (line with ●) to determine if the patient's prescription needs to be modified. The filter can also consider which treatments are being performed. For example, if a patient is performing a high percentage of high UF treatments and still not meeting the standard of care UF target, a warning notification can occur sooner.

[0153] One specific example of a warning algorithm is when the 30-day cyclic average UF (line with ●) drops 10 percent while on a standard or high UF regimen and the actual UF (baseline) is below the lower limit for 3 of the last 7 days. Another specific example of a warning algorithm is when the 30-day cyclic average UF (line with ●) drops 10 percent while on a standard or high UF regimen and the 7-day cyclic UF (line with ▼) is below the lower LCL.

[0154] The alert algorithm may also take into account daily weight and blood pressure data. For example, an alert is triggered when UF deviation, daily blood pressure, and weight each exceed their respective safety thresholds. In one specific example, the system 10 alerts if (i) UF deviates from target UF, (ii) short-term moving average (e.g., 3-7 days) body weight ("BW") is greater than a threshold, and (iii) short-term moving average (e.g., 3-7 days) systolic / diastolic blood pressure ("BP") is greater than a threshold. The BP and BW thresholds are preset by the physician 110.

[0155] Additionally, weight data alone can trigger an alarm, for example, when a patient is gaining weight at a certain rate or gaining a certain amount of weight. Here, the system 10 can notify the physician 110 and / or clinician 120, prompting a call or email to the patient seeking an explanation for the weight gain. If the weight gain is not due to diet, it may be due to an excess amount of dextrose in the patient's prescription, and a new lower dextrose prescription or set of such prescriptions may need to be prescribed. For example, the clinician 120 can set a target weight for the patient, and if the daily measured weight is off by Xw pounds for Yw days in a seven-day period, the weight gain is deemed excessive and an alert is triggered. ΔBW=BW m -B.W. target >Xw for Yw days, where BW m is the measured daily body weight, BW targetis the target weight (set by the physician 110 or clinician 120), Xw is the weight limit above the target (set by the physician 110 or clinician 120), and Yw is the number of days (set by the physician 110 or clinician 120).

[0156] Similarly, an increase in blood pressure alone may prompt a communication from the physician 110 and / or clinician 120 for an explanation from the patient. Additionally, trending of the patient's daily bioimpedance is contemplated, particularly as such sensing becomes more developed. Such sensing is not inconvenient for the patient, as bioimpedance may be integrated, for example, into a blood pressure cuff (for wired or wireless communication with the dialysis equipment 104). The system 10, in one embodiment, uses bioimpedance to monitor the patient's hydration state in the dialysate by estimating the patient's intracellular and extracellular water. Such data assists the patient and clinician in selecting a therapy (e.g., high UF when the patient is overhydrated, and low UF when the patient is dehydrated). Bioimpedance may thereby help control the patient's fluid balance and blood pressure.

[0157] Clinicians are generally concerned about two factors: treatment efficacy and patient compliance. Patients whose UF falls below the target because they are performing low UF too frequently or skipping treatments need to be told in time to change their behavior. Patients whose UF falls below the target but are well compliant and even performing high UF treatment to obtain the target UF may need to have their prescription changed in time. The trends in Figures 22 and 23 provide all such information to the clinician.

[0158] Thus, the system 10 knows if a lower than expected UF is due to a compliance issue or an underlying treatment prescription problem. In embodiments where the patient selects which prescription to run on a given day, the dialysis instrument 104 can be programmed to provide a warning to the patient when the patient is running a low UF too often (a low UF prescription may be less demanding than a standard UF prescription). The programming can be configured to escalate the warning if the patient continues this behavior, to let the patient know that the dialysis center 120 is notified, and to notify the dialysis center accordingly. The instrument 104 can similarly be programmed to warn the patient if the patient is skipping too many treatments, and to notify the dialysis center 120 if missed treatments continue. Here, warnings and notifications can occur regardless of whether the patient chooses which prescription to run or the machine 104 / clinic 120 selects the prescription for a given day.

[0159] FIG. 24 summarizes the options available for setting simple or complex alert generation logic. Parameters that can be monitored include (in the top row) (i) daily UF deviation limit, (ii) UF deviation cumulative limit, (iii) weight target, and (iv) blood pressure limit. The logic operators in the middle indicate that one or more of (a) measured daily UF, (b) measured daily weight, and (c) measured daily blood pressure can be used to combine the limits in the top row in different combinations using "AND" logic and / or "OR" Boolean logic to determine when to send an alert to the patient, physician, or clinician. The illustrated alerts are based on (i) UF and BW, or (ii) UF, BW, and BP. However, alerts can be based on UF only.

[0160] 25, an algorithm or operational flow diagram 140 illustrates one alternative alert sequence for the system 10. Starting at oval 142, the system 10 collects daily UF, BP, and BW data at block 144. At block 146, a deviation analysis is performed, for example, based on doctor / clinician settings and rolling averages of UF, BP, and BW. At diamond 148, the method or algorithm 140 of the system 10 determines whether any of the UF, BP, and BW are over limits. If not, the method or algorithm 140 waits another day, as seen at block 150, and then returns to the collection step at block 144. If a limit or combination of limits is exceeded at diamond 148, as seen at block 152, an alert is sent to the patient, clinician, and / or physician. The deviation and cumulative values ​​are reset.

[0161] A hold or observation period is then initiated at diamond 154, for example, for seven days, to see if the alert condition persists. During this period, it is contemplated that the system 10 will communicate between the patient 104, the physician 110, and / or the clinician 120 on a daily or otherwise periodic basis until the low UF trend is reversed. The clinician may make suggestions during this period, for example, to try a higher UF prescription or to modify the patient's diet. As will be discussed, the dialysis center 120 also receives patient weight and blood pressure trend data in addition to the UF trend data. Mean arterial pressure ("MAP") may be the most appropriate value to trend against blood pressure. The clinician simultaneously evaluates weight and MAP data during the low UF period.

[0162] If the alert condition persists for, for example, a seven day period as seen at diamond 154, method 140 and system 10 prescribe a new PET and / or change the patient's prescription as seen at block 156. Method 140 then ends as seen at oval 158.

[0163] (Patient case study) Patient A started peritoneal dialysis treatment just 2 months ago and still has residual renal function ("RRF"). The patient's UF target is 800 mL / day. The physician set up warning observations to look at daily UF deviation, UF deviation accumulation, and target weight, where deviation limit X was selected at 30% with period Y equal to 4 days out of 7 days. The 3 day UF deviation cumulative error was selected at 150%. Target weight was selected at 240 lbs with a safety limit differential of +5 lbs over 7 days. The table below is an example of daily 24 hour UF, BP, and BW measured over a 7 day period.

[0164] [Table 5] In the treatment week shown above for Patient A, only Thursday's daily UF falls below the 30% lower threshold. The three day cumulative UF deviation does not exceed 150%. The patient's weight remains below the limit (+5 lbs) for all but the last two days. Here, system 10 does not generate an alert.

[0165] Patient B has been on PD for over 2 years. The patient is highly compliant with treatment and closely follows clinician instructions. The patient has no RRF and the daily UF target is 1.0 L. Now, the physician 110 and / or clinician 120 have set the warning conditions as follows: Deviation limit X was selected to be 20% with period Y equal to 4 days out of 7 days. The cumulative error of UF deviation over 3 days was selected to be 150%. The target weight was selected to be 140 lbs with a safety limit differential of +5 lbs over 7 days. The table below is an example of daily 24 hour UF, BP, and BW measured over a 7 day period.

[0166] [Table 6] During the treatment week shown above for Patient B, none of the daily 24 hour UF values ​​fall below the 20% lower threshold. The 3 day cumulative UF deviation does not exceed 150% on any day. The patient's weight never exceeds the +5 lbs threshold. Therefore, the system 10 does not generate a trend alert during this week.

[0167] Patient C has been on PD for over a year. The patient has binge eating / drinking and occasionally skips treatments. The patient has no RRF and a daily UF target of 1.0 L. Now, the physician 110 and / or clinician 120 have set the warning conditions as follows: Deviation limit X was selected at 25% with a period Y equal to 4 days out of 7 days. The cumulative error of UF deviation over 3 days was selected at 150%. The target weight was selected at 220 lbs with a safety limit differential of +5 lbs over 7 days. The table below is an example of daily 24 hour UF, BP, and BW measured over a 7 day period.

[0168] [Table 7] In the week of treatment shown above for Patient C, the patient's daily UF was below the 25% lower threshold on Monday, Thursday, Friday, and Saturday, as highlighted. The three-day cumulative UF deviation exceeded the 150% limit after Saturday's treatment. The patient's weight also exceeds the +5 lbs weight limit four times, namely, on Monday, Thursday, Friday, and Saturday. Therefore, the system 10 will send a trend alert after this week.

[0169] (Trend and Alert Generation Using Statistical Process Control) Also contemplated is the use of statistical process control ("SPC") to identify instability and unusual situations. Referring now to FIG. 26, one example moving average or trend is shown showing the 5-day average UF (dots) and the average UF for the past 30 days (reference center line). The range is calculated to be the difference between the lowest and highest UF values ​​over the past 30 days. The upper control limit line ("UCL", line with an X through it) for a given day is calculated to be UCL=(moving average for a given day)+(constant, e.g., 0.577, *range for a given day), and the lower control limit line ("LCL", line with a / through it) is calculated to be LCL=(moving average for a given day)-(constant, e.g., 0.577, *range for a given day).

[0170] FIG. 26 shows a UF trend generated for a patient, for example, from August 2003 to June 2004, using SPC. In December 2003 and April 2004, the 5-day moving average UF (dot) was below the LCL. The system 10 can be configured to monitor the 5-day average and alert the patient, clinic and / or physician when the 5-day moving average UF (dot) is below the LCL (or below the LCL for several consecutive days). Software configured to generate trends can be located on the dialysis instrument 104 or on the server computer 114 or 118. In various embodiments, the trends can be accessed and viewed by any one or more or all of the patient 102, dialysis center 120, or physician 110. The trend data is generated regardless of whether the trends are actually viewed by anyone. The alerts, in one embodiment, are automatically generated, allowing the system 10 to automatically monitor the patient 102 on behalf of the dialysis center 120 and physician 110.

[0171] Figure 27 shows a second trend for the same patient after a change was made to the patient's prescription (line with ●) where the patient's daytime exchange was changed from Nutrineal® to Extraneal® dialysate. Figure 27 shows the difference in the new prescription (line with ●) in the patient's UF starting in September 2004 and again in November 2004 as the patient's residual renal function gradually declined.

[0172] The statistical process control alert algorithm may also take into account body weight ("BW") and / or blood pressure ("BP"). If UF has a normal distribution with a mean of μ and a standard deviation of σ, calculated based on time and population, then C is an empirically determined constant. In most processes controlled using statistical process control (SPC), multiple measurements and observations are made at each time point (e.g., measuring room temperature multiple times at 8am), but in one embodiment of system 10, only one measurement of SPC is made at each time point, e.g., one UF measurement, one pressure and one weight measurement per day. Then, (i) the short-term moving average (e.g., 3-7 days) UF is adjusted to the upper control limit (UCL UF =UF target +Cσ) or Lower Control Limit (LCL UF =UF target -Cσ), or (ii) if the short term moving average (3-7 days) Weight > BW Threshold, and / or (iii) if the short term moving average (3-7 days) Systolic / Diastolic BP > BP Threshold.

[0173] FIG. 27 shows that the SPC trend chart can also display the patient's expected UF value (line with ▲) based on the last PET result. While the 30-day average line shows the actual UF, a slight lag to the expected UF (as would be expected for the 30-day average) eventually aligns with the expected UF value result. Here, the patient is meeting the target, rather than being under par. However, the patient may be losing RRF, meaning that the patient's prescription needs to be more aggressive with UF, as the patient is reducing their ability to remove waste and excess fluid on their own. On the other hand, if the difference between expected and actual UF increases beyond what the physician / clinician determines to be significant, e.g., below the LCL for more than a day, the clinician / physician can prescribe a new PET, as discussed above.

[0174] (Prescription recall and amendment) The system 10 also includes a prescription recall and modification feature 26, as shown and described in connection with Figure 1. Referring now to Figure 28, the prescription recall and adjustment feature or module 26 is illustrated in more detail. The prescription recall and adjustment feature or module 26 depends on and works in conjunction with other features of the system 10, such as the improved PET feature 12, the dosing regimen generation feature 14, the prescription filtering feature 16, and the trend alert generation feature 24. As seen in Figure 28, one aspect of the prescription recall and adjustment feature or module 26 is the selection of one of the approved prescriptions for treatment.

[0175] 29, the screen 160 of the display device 130 of the dialysis machine 104 illustrates one patient selection screen that allows the patient to select one of the approved prescriptions (standard, high, and low UF) for that day's treatment. The input type can be via a membrane key or here via a touch screen overlay, with areas 162, 164, and 166 mapped in memory as standard UF prescription, high UF prescription, and low UF prescription selection, respectively. The system 10 in the illustrated embodiment allows the patient to select a prescription for that day's treatment. For example, if the patient has consumed more fluid than normal on a given day, the patient may run a high UF prescription. If the patient has exercised, been exposed to the sun, or sweated a lot during the day for any reason, the patient may choose to run a low UF prescription.

[0176] If a patient viewing the above treatment trend screens 134 and 136 notices a drop in UF running the standard UF prescription, the patient may be entitled to choose to run the high UF prescription for a few days to see how the patient responds to the prescription change. Perhaps the daily UF will increase. However, it should also be understood that the patient, clinician, or physician should verify whether the actual increased UF corresponds to the increased expected UF due to the use of the high UF prescription. If the patient is below par for both prescriptions, it may be time for a new PET and perhaps a new set of prescriptions.

[0177] As explained above, allowing the patient to adjust their treatment is likely only done when the doctor or clinician has the patient's reassurance that the patient is compliant in terms of lifestyle and treatment adherence. Also, the doctor / clinician may want to ensure that the patient has enough experience with the treatment and the dialysis device 104 to be able to gauge accurately when the patient needs a high UF treatment versus a low UF treatment versus a standard UF treatment. In this embodiment, even if the patient is making the prescription decision, the trend data as shown above is sent to the dialysis center 120 and / or doctor 110 so that if the patient is making a poor decision about which prescription to follow, the dialysis center 120 and / or doctor 110 can quickly detect the situation and correct it. For example, the system 10 allows the dialysis center 120 and / or doctor 110 to remove a prescription from the possible selections or to set the dialysis device 104 to automatically select a prescription set in the machine 104 or server computer 114 or 118.

[0178] Considering the importance of dialysis treatment, it is believed that most responsible, conscientious and thoughtful patients will be able to best gauge when a patient may need a more aggressive or less aggressive prescription, removing a certain amount of UF even knowing that a less aggressive prescription is approved. Providing more than three prescriptions is contemplated. For example, a patient may have two high UF prescriptions, one requiring a longer overnight treatment and the other requiring a higher dextrose concentration. Assuming the patient knows that a high UF prescription needs to be run after a day in which they consumed a relatively large amount of fluid, the patient may choose the longer overnight treatment, knowing that they have recently gained weight and would be better off refraining from the higher caloric intake of the higher dextrose prescription. The system 10 establishes a thorough patient history that seeks to accommodate the patient's lifestyle while ensuring that the proper treatment is administered, and while collecting treatment data over time, allowing physiological changes in the patient to be detected relatively quickly and accurately.

[0179] In another embodiment, the dialysis device 104 selects which prescription the patient will run based on the patient's daily weight and possibly the patient's blood pressure. The patient weighs himself and a weight signal is transmitted, for example wirelessly, to the dialysis device 104, which uses the weight signal to determine how much UF the patient has accumulated and therefore which prescription to run. In one embodiment, the patient weighs himself just before the last overnight fill or just before the daytime fill to establish a local "dry weight". The patient then weighs himself overnight just after the last fill drain to establish a local "wet weight". The difference between the local "wet weight" and the local "dry weight" determines the UF volume. The UF volume is matched to one of a low UF range, a standard UF range, and a high UF range. The dialysis device 104 then chooses the corresponding low UF prescription, standard UF prescription, or high UF prescription to run. Alternatively, the dialysis instrument 104 may offer a range of alternative formulations, e.g., two high UF formulations, allowing the patient to choose one of the two high UF formulations. As discussed above, the dialysis instrument 104, in one embodiment, is configured to read the bag identifier and ensure that the patient connects the correct dialysate and the correct amount of dialysate.

[0180] In a further alternative embodiment, the physician 110 or dialysis center 120 selects or pre-approves the prescription to be run on a given day, so that the patient cannot run a different prescription. Here, fill, dwell, and / or drain times can be pre-set, and the dialysis instrument 104 can also be configured to read bag identifiers to ensure the patient connects the right dialysate and the right amount of dialysate.

[0181] It is further contemplated that the patient may input which prescriptions are to be run, but the physician 110 or dialysis center 120 ultimately approves the prescription selection, or a pre-prescription selection plan is downloaded to the dialysis device 104. For example, it is contemplated that the dialysis center 120 may send an automatically generated email to the patient 102, e.g., each month, one week before the start of the next month. The email includes a calendar, with each day of the calendar showing all available prescriptions, e.g., (i) lowUF, (ii) midUFlowDEX, (iii) midUFhighDEX, (iv) highUFlowDEX, and (v) highUFhighDEX. The patient clicks on one of the prescriptions for each day and sends the completed calendar to the clinician 120 for approval. For example, the patient may choose to run one of the high UF prescriptions on the weekend and one of the medium or standard prescriptions during the week. Perhaps the patient attends a physically demanding exercise class after work on Mondays and Wednesdays, and selects the low UF prescription on these days.

[0182] It is contemplated that patients may type annotations on dates to explain why a particular prescription is being suggested. For example, a patient may select a lowUF prescription and type "Spin class" on that calendar day. Or, a patient may select a highUFhighDEX prescription and type "Birthday party, up early the next day" on that calendar day.

[0183] Once the clinician receives the completed suggested calendar from the patient, the clinician can approve the suggested calendar, call or email to ask questions about why one or more prescriptions were selected for a particular day, forward the calendar to the physician's office 110 if the clinician has concerns or questions regarding the suggested calendar, or modify the selections in the calendar and send the modified calendar back to the patient. The clinician can review patient trend data when evaluating the suggested prescription calendar. For example, if the patient has gained weight and has selected high dextrose standard UF for many or all days of the month, the clinician can call or email the patient and suggest switching to a low dextrose standard UF prescription in an attempt to control the patient's weight gain.

[0184] Ultimately, the clinician and patient come to an agreement. The physician may or may not need to be consulted. It is expected that the patient's calendar will look the same from month to month and may vary naturally based on seasons, vacations, and holidays. When radical changes are proposed, for example, the patient intends to begin an active exercise or training routine and would like to introduce more low UF days, the clinician may seek the physician's approval.

[0185] In one embodiment, the dialysis instrument 104 identifies that the patient wishes to perform a non-standard treatment on a particular day. The dialysis instrument 104 also allows the patient to switch to a standard treatment if the patient so desires. For example, if the patient expects to be actively exercising on Monday and Wednesday and a low UF prescription is approved for those days, but if the patient misses exercising, the patient can choose to perform the standard UF prescription instead. Or, if the patient is expected to attend a party on a given day and therefore a high UF prescription is to be performed, but the patient misses the party, the patient can choose to perform the standard UF prescription instead.

[0186] The dialysis instrument 104 may also be configured to provide a limited amount of prescription changes to the patient from a standard UF prescription to a low or high UF prescription. For example, if the patient decides to exercise on Thursday instead of Wednesday, the patient may switch prescription from standard UF to low UF on Thursday. The system 10 may be configured to allow, for example, one such standard to non-standard prescription change per week.

[0187] In another embodiment, the dialysis device 104 allows the patient to increase UF removal at any time, i.e., switch from a low UF prescription to a standard or high UF prescription, or switch from a standard UF prescription to a high UF prescription, and if the patient selects this option a certain number of times during a month, the dialysis device 104 can send an alert to the physician 110 or clinician 120.

[0188] The approval calendar, in one embodiment, is integrated with the inventory tracking feature 18. The approval calendar tells the inventory tracking feature 18 what is needed for the next delivery cycle, which can be a monthly cycle. If the patient is able to plan and obtain approval for multiple months, the delivery cycle can be multiple months. In either case, the patient can be delivered extra solution if necessary to allow for a changeover from the planned prescription.

[0189] In a further alternative embodiment, the patient and clinician and / or doctor agree that each week the patient will run a certain number of standard, low, and high formulas, for example, five standard formulas, one low formula, and one high formula. The patient then selects which days during the week to run the various formulas. The weekly allotment may not include any low UF or high UF allotments. The patient may have, for example, seven standard UF allotments, with four low dextrose standard formulas and three high dextrose standard formulas. Again, the dialysis instrument 104 may be configured to allow the patient to change formulas in some cases, as described above.

[0190] In yet a further alternative embodiment, the dialysis instrument 104 or one of the server computers 114 or 118 selects one of the approved prescriptions for the patient for each treatment. The selection can be based on any of the trend data described above and / or based on a series of questions answered by the patient, such as: (i) Was your fluid intake today low, moderate, average, high, or very high?; (ii) Was your food intake today low, moderate, average, high, or very high?; (iii) Was your carbohydrate intake today low, moderate, average, high, or very high?; (iv) Was your sugar intake today low, moderate, average, high, or very high?; (v) Was your activity level today low, moderate, average, high, or very high? The system 10 then selects one of the approved prescriptions for the patient. The inventory management in this embodiment can be based on average usage over the past X number of delivery cycles. In any of the above regimens, the dialysis instrument 104 can also be configured to read the bag identifier to ensure that the patient connects the correct dialysate and the correct amount of dialysate.

[0191] As seen in Fig. 28, the selected daily prescription is provided to a switching mechanism for prescription recall and modification feature 26. The switching mechanism is activated when the applied alert generation algorithm of feature 24 calculates an error greater than the threshold of the applied alert generation algorithm. As seen in Fig. 28, when the applied alert generation algorithm of feature 24 calculates an error not greater than the threshold, feature 26 maintains the current prescription set, regardless of which prescription recall regime is employed. Thus, the switching mechanism does not switch to a new prescription or set of prescriptions.

[0192] When a prescription is used for treatment, the prescription has with it a predicted UF, which is generated via the regimen generation feature 14 and selected via the prescription filtering feature 16 .

[0193] The actual UF data is obtained from short-term and long-term running averages as discussed above in connection with trend and alert generation feature 24, which in turn are created from measured UF data generated at dialysis instrument 104. The actual UF value is a function of the patient's transport characteristics as described herein, but also accounts for environmental factors such as patient dosing regimen deviations. The actual UF value is subtracted from the predicted UF value in difference generator 66a and provided to the alert generation algorithm at diamond 24. The actual UF value is also provided to difference generator 66b, which is used to adjust the target UF value, which is used to generate the dosing regimen in connection with feature 14. Other target values ​​include target urea removal, target creatinine removal, and target glucose absorption, as discussed above.

[0194] Once the system 10 determines an alarm condition, as seen at diamond 24, the system 10 triggers a prescription adjustment switching mechanism, which does not necessarily mean that the patient's prescription is adjusted. The physician 110 ultimately initiates a call based on UF, the patient's daily weight, daily blood pressure, or estimated dry weight data using bioimpedance. When a prescription adjustment is deemed necessary, the system 10 communicates with the patient via the communication module 20, e.g., via wireless communication between the APD system and a modem through a router. Based on the received data, the nephrologist 110 can make the following decisions in the switching mechanism 26: (i) continue the current prescription and visit the outpatient clinic as previously scheduled; (ii) continue the current prescription but visit sooner for possible prescription adjustment; (iii) switch to a different routine using the current prescription and visit sooner, for example within two weeks, and receive trend data on the new routine; (iv) warn the patient about non-adherence to treatment and maintain the current prescription; (v) warn the patient about running a low UF prescription too frequently and maintain the current prescription; (vi) continue the current treatment and monitoring, but lower the UF target to A and the UF limit to B; or (vii) perform a new APD PET to evaluate changes in PD membrane transport properties and provide the center with updated treatment suggestions based on this PET.

[0195] If the patient is well compliant and the low UF is the result of a change in transport characteristics as verified by the new PET, the physician 110 can direct that a new prescription be generated that includes one or more modifications to the standard UF prescription. To do so, the dosing regimen generation module 14 and prescription filtering module 16 are again used to formulate the new prescription. The physician agrees to the new prescription and the new prescription and switching mechanism 26 changes to the new prescription, as seen in FIG. 28.

[0196] It should be understood that various changes and modifications to the preferred embodiments of the present invention described herein will be apparent to those skilled in the art. Such changes and modifications can be made without departing from the spirit and scope of the present subject matter and without diminishing its intended advantages. Accordingly, such changes and modifications are intended to be covered by the appended claims. (Item 1) an automated peritoneal dialysis ("APD") machine; a server computer in communication with the APD machine, the server computer and the APD machine programmed to enable the APD machine to transmit patient ultrafiltration ("UF") clearance data to the server computer, and programmed to output the UF clearance data in a form suitable for a physician / clinician to review the data and make therapy adjustments if necessary; A peritoneal dialysis system comprising: (Item 2) 2. The peritoneal dialysis system of item 1, wherein the profile includes a daily UF removal trend. (Item 3) 3. The peritoneal dialysis system of item 2, wherein the trend includes at least one of an upper and lower UF limit, and the at least one limit is used together with the trend UF removal data to determine whether a therapy adjustment is necessary. (Item 4) 4. The peritoneal dialysis system of claim 3, wherein the APD machine is programmed to send an alert to the server computer if an alert condition is met, the alert condition being based at least in part on a comparison of the daily UF removal data to the at least one limit. (Item 5) 4. The peritoneal dialysis system of claim 3, wherein the server computer is programmed to generate an alert if an alert condition is met, the alert condition being based at least in part on a comparison of the daily UF removal data with the at least one limit. (Item 6) 4. The peritoneal dialysis system of item 3, wherein the at least one limit is a factor multiplied by the expected daily UF removal. (Item 7) 2. The peritoneal dialysis system of claim 1, wherein the server computer and the APD machine are further configured to enable the APD machine to transmit at least one of blood pressure and patient weight data to the server computer. (Item 8) 8. The peritoneal dialysis system of item 7, further comprising a wireless interface receiver operable with a logic implementer, wherein at least one of the meter and the blood pressure monitor includes a wireless interface transmitter, and at least one of the blood pressure and patient weight data is wirelessly transmitted from the meter and at least one of the blood pressure monitor to the wireless interface receiver. (Item 9) 2. The peritoneal dialysis system of claim 1, wherein the UF removal data form includes a moving average UF removal trend. (Item 10) 10. The peritoneal dialysis system of item 9, wherein the trend includes at least one of an upper and lower UF limit, and the at least one limit is used together with the moving average UF removal trend to determine whether a therapy adjustment is required. (Item 11) Item 11. The peritoneal dialysis system of item 10, wherein the APD machine is programmed to send an alert to the server computer if an alert condition is met, the alert condition being based at least in part on a comparison of the moving average UF removal trend with the at least one limit. (Item 12) 11. The peritoneal dialysis system of claim 10, wherein the server computer is programmed to generate an alert if an alert condition is met, the alert condition being based at least in part on a comparison of the moving average UF removal trend with the at least one limit. (Item 13) Item 11. The peritoneal dialysis system of item 10, wherein the moving average UF removal trend is a first trend and the at least one limit is a factor multiplied by a second moving average trend. (Item 14) Item 14. The peritoneal dialysis system of item 13, wherein the second moving average trend is of longer duration than the first moving average trend. (Item 15) an automated peritoneal dialysis ("APD") machine; a server computer in communication with the APD machine, the server computer and the APD machine programmed to generate peritoneal dialysis data trends that can be used by a physician / clinician to determine if treatment adjustments need to be made; A peritoneal dialysis system comprising: (Item 16) Item 16. The peritoneal dialysis system of item 15, wherein the peritoneal dialysis trend data is of a type selected from the group consisting of: (i) ultrafiltrate removal data, (ii) blood pressure data, and (iii) patient weight data. (Item 17) Item 16. The peritoneal dialysis system of item 15, wherein the APD machine is programmed to collect / generate the data about the trends, and the server computer is programmed to generate the trends of the data. (Item 18) Item 16. The peritoneal dialysis system of item 15, wherein the APD machine is programmed to collect / generate the data about the trends and generate the trends of the data. (Item 19) 20. The peritoneal dialysis system of claim 18, wherein the APD machine is further configured to send an alert to the server computer when the data trends indicate that a therapy adjustment is likely to need to be made. (Item 20) Item 16. The peritoneal dialysis system of item 15, wherein the therapy adjustment is of a type selected from the group consisting of: (i) changing the type of dialysate, (ii) changing the dextrose concentration of the dialysate, (iii) changing the duration of therapy, (iv) changing the fill volume, (v) changing the number of nighttime fill exchanges, and (vi) whether a diurnal change is made. (Item 21) an automated peritoneal dialysis ("APD") machine configured to remove ultrafiltrate ("UF") from a patient and record how much UF has been removed; a logic implementer configured to: (i) form a first moving average UF removal trend; (ii) determine a trend range around said first moving average UF removal trend; (iii) determine at least one of an upper and lower UF removal limit from said trend range; (iv) form a second moving average UF removal trend; and (v) alert when the second moving average UF removal trend moves outside of at least one removal UF limit; A peritoneal dialysis system comprising: (Item 22) 22. The peritoneal dialysis system of claim 21, wherein the logic implementor is stored in one of the APD machine and a server computer in communication with the APD machine. (Item 23) 22. The peritoneal dialysis system of claim 21, wherein the first moving average UF removal trend is of longer duration than the second moving average UF removal trend. (Item 24) 22. The peritoneal dialysis system of claim 21, wherein the upper limit is formed by adding a factor multiplied by the trend range to the first moving average UF removal trend, and the lower limit is formed by subtracting the factor multiplied by the trend range to the first moving average UF removal trend. (Item 25) 22. The peritoneal dialysis system of claim 21, wherein the alert is provided if (i) the UF removal trend moves outside of the at least one UF removal limit for a number of consecutive days, or (ii) the UF removal trend moves outside of the at least one UF removal limit and the patient's blood pressure rises above the limit.

Claims

1. At least one pump; an ultrafiltration ("UF") therapy regimen including a first UF therapy regimen, a second UF therapy regimen having a longer duration and a lower dextrose concentration compared to the first UF therapy regimen, and a third UF therapy regimen having a shorter duration and a higher dextrose concentration compared to the first UF therapy regimen; a schedule indicating which of the first, second, or third UF treatment regimens will be administered on a particular date; and Limits on permissible UF treatment regimen changes for a given week; a memory device storing the a logic implementer communicatively connected to the memory device, Determine or identify the current date, using the schedule stored in the memory device to select one of the first, second, or third UF treatment regimens based on the current date; receiving input from a patient regarding a selection of the first, second, or third UF therapy prescription for the current date that has been changed from a UF therapy prescription specified by the schedule; incrementing a counter for the number of times the patient-selected UF therapy prescription has been used to perform a peritoneal dialysis therapy in place of a UF therapy prescription specified by the schedule; determining whether the counter is less than a limit of the permitted UF therapy regimen changes; if the counter is less than the limit, controlling the at least one pump to perform a peritoneal dialysis treatment based on a UF treatment prescription selected by the patient instead of a UF treatment prescription specified by the schedule. the logic implementor; A peritoneal dialysis system comprising:

2. The logic implementer is communicatively connected to a network; The logic implementor: receiving the schedule from a clinician's computer or server over the network; storing said schedule in said memory device; The peritoneal dialysis system of claim 1.

3. The peritoneal dialysis system of claim 1, further comprising a user interface device that accepts a first calendar input from the patient regarding a selection of the UF treatment prescription for a specific date, accepts a second calendar input from the patient regarding a reason for the selection of the UF treatment prescription for each specific date, and transmits the first and second calendar inputs via a network to a clinician's computer or server.

4. The logic implementer: receiving the schedule from the clinician's computer or the server via the network after the clinician's computer or the server (a) receives approval of the first and second calendar entries or (b) receives a modification to the selected UF treatment prescription for at least one of the dates of the first calendar entry; storing said schedule in said memory device; The peritoneal dialysis system of claim 3.

5. The user interface device is communicatively connected to the logic implementer. The peritoneal dialysis system of claim 3.

6. The logic implementer: determining whether the counter has reached or exceeded a limit for the permitted UF therapy regimen change; if the counter reaches or exceeds the limit, controlling the at least one pump to perform the peritoneal dialysis treatment based on a UF therapy prescription specified by the schedule instead of using a UF therapy prescription selected by the patient. The peritoneal dialysis system of claim 1.

7. The restriction includes two or more UF treatment regimen changes per week. The peritoneal dialysis system of claim 1.

8. At least one pump; an ultrafiltration ("UF") therapy regimen including a first UF therapy regimen, a second UF therapy regimen having a longer duration and a lower dextrose concentration compared to the first UF therapy regimen, and a third UF therapy regimen having a shorter duration and a higher dextrose concentration compared to the first UF therapy regimen; a schedule indicating which of the first, second, or third UF treatment regimens will be administered on a particular date; and alarm thresholds for permissible UF therapy regimen changes for a given week or month; a memory device storing the a logic implementer communicatively connected to the memory device, Determine or identify the current date, using the schedule stored in the memory device to select one of the first, second, or third UF treatment regimens based on the current date; receiving input from a patient regarding a selection of the first, second, or third UF therapy prescription for the current date that has been changed from a UF therapy prescription specified by the schedule; controlling the at least one pump to perform a peritoneal dialysis treatment based on a UF treatment prescription selected by the patient instead of a UF treatment prescription specified by the schedule; incrementing a counter for the number of times the patient-selected UF therapy prescription has been used in place of the schedule-specified UF therapy prescription for the current week or month; determining whether the counter has reached or exceeded the alarm threshold; if the counter reaches or exceeds the alarm threshold, sending an alarm message over a network to a clinician's computer or server indicating that the alarm threshold has been reached or exceeded; the logic implementor; A peritoneal dialysis system comprising:

9. The method of claim 8, wherein the logic implementer increments the counter only if the patient selects the second UF treatment prescription or the third UF treatment prescription. The peritoneal dialysis system of claim 8.

10. The UF treatment formulation further comprises a fourth UF treatment formulation having a shorter duration and a higher dextrose concentration compared to the first UF treatment formulation, and a fifth UF treatment formulation having a shorter duration and a higher dextrose concentration compared to the first UF treatment formulation. The peritoneal dialysis system of claim 8.

11. The peritoneal dialysis treatment comprising at least one of a cyclic dialysis treatment or a continuous cycling peritoneal dialysis ("CCPD") treatment. The peritoneal dialysis system of claim 8.

12. At least one pump; an ultrafiltration ("UF") treatment regimen including a first UF treatment regimen, a second UF treatment regimen, and a third UF treatment regimen; a schedule indicating which UF treatment regimen will be administered on specific dates; alarm thresholds for permissible UF therapy regimen changes for a given week or month; a memory device storing the a logic implementer communicatively connected to the memory device, Determine or identify the current date, using the schedule stored in the memory device to select one of the first, second, or third UF treatment regimens based on the current date; receiving input from a patient regarding a selection of the first, second, or third UF therapy prescription for the current date that has been changed from a UF therapy prescription specified by the schedule; controlling the at least one pump to perform a peritoneal dialysis treatment based on a UF treatment prescription selected by the patient instead of a UF treatment prescription specified by the schedule; incrementing a counter for the number of times the patient-selected UF therapy prescription has been used in place of the schedule-specified UF therapy prescription for the current week or month; determining whether the counter has reached or exceeded the alarm threshold; if the counter reaches or exceeds the alarm threshold, sending an alarm message over a network to a clinician's computer or server indicating that the alarm threshold has been reached or exceeded; the logic implementor; A peritoneal dialysis system comprising:

13. The peritoneal dialysis system of claim 12, further comprising a user interface device that accepts calendar input from the patient regarding selection of the UF treatment prescription for a particular date and transmits the calendar input via a network to a clinician's computer or server.

14. The logic implementer, receiving the schedule from the clinician's computer or server via the network after the clinician's computer or server (a) receives an approval of the calendar entry or (b) receives a modification of the selected UF treatment prescription for at least one date; storing said schedule in said memory device; The peritoneal dialysis system of claim 13.

15. The user interface device, communicatively connected to the logic implementer. The peritoneal dialysis system of claim 13.

16. The method of claim 15, wherein the schedule is integrated with an inventory tracking feature of the server to determine when to deliver a fluid container to the patient for performing a subsequent peritoneal dialysis treatment. The peritoneal dialysis system of claim 13.

17. A method for producing a liquid-filled ... an ultrafiltration ("UF") treatment regimen including a first UF treatment regimen, a second UF treatment regimen, and a third UF treatment regimen; a schedule indicating which UF treatment regimen will be administered on specific dates; Limits on permissible UF treatment regimen changes for a given week; a memory device storing the a logic implementer communicatively connected to the memory device, Determine or identify the current date, using the schedule stored in the memory device to select one of the first, second, or third UF treatment regimens based on the current date; receiving input from a patient regarding a selection of the first, second, or third UF therapy prescription for the current date that has been changed from a UF therapy prescription specified by the schedule; incrementing a counter for the number of times the patient-selected UF therapy prescription has been used to perform a peritoneal dialysis therapy in place of a UF therapy prescription specified by the schedule; determining whether the counter is less than a limit of the permitted UF therapy regimen changes; if the counter is less than the limit, controlling the at least one pump to perform a peritoneal dialysis treatment based on a UF treatment prescription selected by the patient instead of a UF treatment prescription specified by the schedule. the logic implementor; A peritoneal dialysis system comprising:

18. The logic implementer comprising: determining whether the counter has reached or exceeded a limit for the permitted UF therapy regimen change; if the counter reaches or exceeds the limit, controlling the at least one pump to perform the peritoneal dialysis treatment based on a UF therapy prescription specified by the schedule instead of using a UF therapy prescription selected by the patient.

18. The peritoneal dialysis system of claim 17.

19. The peritoneal dialysis system of claim 17, further comprising a user interface device that accepts calendar input from the patient regarding selection of the UF treatment prescription for a particular date and transmits the calendar input via a network to a clinician's computer or server.

20. The logic implementer comprising: receiving the schedule from the clinician's computer or server via the network after the clinician's computer or server (a) receives an approval of the calendar entry or (b) receives a modification of the selected UF treatment prescription for at least one date; storing said schedule in said memory device; 20. The peritoneal dialysis system of claim 19.

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