Techniques for determining acid-base balance

Abstract

The described techniques may include a process that simulates a normal patient and acid-base equilibrium under acid-base imbalance conditions. In one embodiment, a method may include an acid-base equilibrium analysis process. The method may include providing, via a processor of a computing device, an acid-base model configured to simulate an acid-base balance of a patient, the acid-base model including a patient model, a dialyzer model, and an extracorporeal CO2 removal device (ECCO2RD), and determining predicted patient information using the acid-base model. Other embodiments are described.

Description

[0001] CROSS-REFERENCE TO RELATED APPLICATIONS

[0002] This application claims the benefit of U.S. Provisional Application No. 63 / 345,344, filed May 24, 2022, the entire contents of which are incorporated herein by reference in their entirety. Technical Field

[0003] The present disclosure generally relates to processes for modeling the functions of various parts of the human body to generate healthcare information, treatment recommendations, etc., and more specifically, to techniques for modeling the acid-base balance of patients being treated with certain medical devices, such as dialyzers and / or extracorporeal CO2 removal devices (ECCO2RDs). Background Art

[0004] Precise maintenance of pH and acid-base balance is fundamental to optimal physiological and cellular function. The presence of acid-base imbalances can affect clinical outcomes and may be related to underlying disease. Acid-base imbalances are common in patients with complications of kidney health, such as dialysis patients. Continuous renal replacement therapy (CRRT) is a slow, continuous method of dialysis that aids in solute and fluid homeostasis. Acid-base complications can be a contributing factor to morbidity in patients on CRRT. Therefore, it is important to assess the patient's acid-base status and how effective various treatments are in controlling these acid-base changes.

[0005] However, conventional methods and techniques are unable to determine patient information sufficient to accurately and effectively provide decision support to guide clinicians in determining treatment or setting optimal parameters for a selected treatment regimen.

[0006] It is with these and other considerations in mind that improvements of the present invention may be useful. Summary of the invention

[0007] This Summary is provided to introduce a selection of concepts in a simplified form that are further described below in the Detailed Description. This Summary is not intended to be necessarily identifying.

[0008] In one embodiment, a device may include at least one processor and a memory coupled to the at least one processor, the memory including instructions that, when executed by the at least one processor, cause the at least one processor to access an acid-base model configured to simulate a patient's acid-base balance, the acid-base model including a patient model, a dialyzer model, and an extracorporeal CO2 removal device (ECCO2RD) model, and use the acid-base model to determine predicted patient information.

[0009] In some embodiments of the device, the predicted patient information may include at least one of blood flow rate (Q), serum pH level, pCO2 level, or HCO3 level.

[0010] In some embodiments of the device, the predicted patient information may include a treatment recommendation. In various embodiments of the device, the treatment recommendation may include a treatment course for the acid-base imbalance.

[0011] In some embodiments of the apparatus, when executed by at least one processor, the instructions may cause the at least one processor to determine continuous renal replacement therapy (CRRT) parameters to control acid-base status based on the predicted patient information.

[0012] In various embodiments of the apparatus, the acid-base model may be configured to simulate H + , CO2 and of adjustment.

[0013] In some embodiments of the apparatus, the patient model may be configured to simulate patient physiology with inputs being blood flow and outputs being hydrogen ion concentration, carbon dioxide concentration, and bicarbonate concentration.

[0014] In various embodiments of the apparatus, the dialyzer model may be configured to simulate continuous renal replacement therapy (CRRT).

[0015] In an exemplary embodiment of the apparatus, the ECCO2RD model may be configured to simulate a one-dimensional (1D) diffusion device between blood and air.

[0016] In some embodiments of the apparatus, the acid-base model may include a blood flow circuit from a patient simulated by the patient model, to a dialyzer simulated by the dialyzer model, to an ECCO2RD simulated by the ECCO2RD model, and back to the patient.

[0017] In various embodiments of the apparatus, the blood flow circuit may include diffusion at any point in the blood flow circuit.

[0018] In some embodiments of the apparatus, the patient may include a virtual patient.

[0019] In one embodiment, a method of acid-base balance analysis, such as a computer-implemented method via a processor of a computing device, may include providing an acid-base model configured to simulate a patient's acid-base balance, the acid-base model comprising a patient model, a dialyzer model, and an extracorporeal CO2 removal device (ECCO2RD) model, and determining predicted patient information using the acid-base model.

[0020] In some embodiments of the method, the predicted patient information may include at least one of blood flow rate (Q), serum pH level, pCO2 level, or HCO3 level.

[0021] In some embodiments of the method, the predicted patient information may include a treatment recommendation. In various embodiments of the computer-implemented method, the treatment recommendation may include a course of treatment for the acid-base imbalance.

[0022] In some embodiments of the method, the method may include prescribing continuous renal replacement therapy (CRRT) parameters to control acid-base status based on the predicted patient information.

[0023] In some embodiments of the method, the acid-base model is configured to simulate H + , CO2 and of adjustment.

[0024] In some embodiments of the method, the patient model can be configured to simulate patient physiology with inputs being blood flow and outputs being hydrogen ion concentration, carbon dioxide concentration, and bicarbonate concentration.

[0025] In some embodiments of the method, the dialyzer model may be configured to simulate continuous renal replacement therapy (CRRT).

[0026] In some embodiments of the method, the ECCO2RD model may be configured to simulate a one-dimensional (1D) diffusion device between blood and air.

[0027] In some embodiments of the method, the acid-base model may include a blood flow circuit from a patient simulated by the patient model, to a dialyzer simulated by the dialyzer model, to an ECCO2RD simulated by the ECCO2RD model, and back to the patient.

[0028] In some embodiments of the method, the blood flow circuit may include diffusion at any point in the blood flow circuit.

[0029] In some embodiments of the method, the patient may include a virtual patient.

[0030] In various embodiments of the method, the predicted patient information may include a treatment recommendation. In some embodiments of the method, the treatment recommendation may include a course of treatment for the acid-base imbalance. BRIEF DESCRIPTION OF THE DRAWINGS

[0031] Specific embodiments of the disclosed machine will now be described by way of example with reference to the accompanying drawings, in which:

[0032] Figure 1 An example of an operating environment 100 is shown that may be representative of some embodiments according to the present disclosure.

[0033] Figure 2 An example of an operating environment that may be representative of some embodiments according to the present disclosure is shown.

[0034] Figure 3 An example of a patient model that may represent some embodiments according to the present disclosure is shown.

[0035] Figure 4 An example table of constant data that may represent an acid-base model according to some embodiments of the present disclosure is shown.

[0036] Figure 5 A block diagram is shown that may represent an intradialytic acid-base model according to some embodiments of the present disclosure.

[0037] Figure 6 A table is shown that may represent a first set of illustrative acid-base model parameters according to some embodiments of the present disclosure.

[0038] Figure 7 A table is shown that may represent a second set of illustrative acid-base model parameters according to some embodiments of the present disclosure.

[0039] Fig. 8A and Figure 8B Simulation results of an acid-base model that may represent some embodiments of the present disclosure are shown.

[0040] Fig. 9 An illustrative ECCO2RD model is depicted that may represent some embodiments according to the present disclosure.

[0041] Fig.10 An example table is shown that may represent parameter data for an acid-base model according to some embodiments of the present disclosure.

[0042] Figures 11A-11D The simulation results of the acid-base model according to some embodiments of the present disclosure are shown.

[0043] Fig.12 The simulation results of the acid-base model according to some embodiments of the present disclosure are shown.

[0044] Fig.13 An embodiment of an exemplary computing architecture that may represent some embodiments according to the present disclosure is shown. DETAILED DESCRIPTION

[0045] The present embodiment will now be described more fully below with reference to the accompanying drawings, in which several exemplary embodiments are shown. However, the subject matter of the present disclosure can be implemented in many different forms and should not be construed as being limited to the embodiments set forth herein. On the contrary, these embodiments are provided so that the present disclosure will be detailed and complete and the scope of the subject matter will be conveyed to those skilled in the art. In the accompanying drawings, the same reference numerals always represent the same elements.

[0046] Acid-base imbalance is a common complication in patients with chronic kidney disease (CKD) that is typically treated with dialysis regimens. One type of dialysis regimen is continuous renal replacement therapy (CRRT), which is typically a slower, continuous dialysis approach to promote solute and fluid homeostasis. Acid-base imbalance, such as acidemia, is a contributing factor to morbidity in patients with CKD, including those on CRRT. Correction of acidemia, especially rapid correction, can significantly improve patient outcomes. Therefore, it is critical to appropriately detect, predict, and / or correct acidemia.

[0047] Thus, some embodiments may operate to enable personalized treatment of CKD patients, including CRRT patients, and / or groups of CRRT patients (e.g., groups with the same or similar characteristics, disease states, etc.). Although CRRT patients are used in some examples of the present disclosure, the embodiments are not limited thereto, as the described processes, techniques, methods, systems, etc. may be used to treat other types of CKD patients and / or treatment regimens.

[0048] Embodiments may include an acid-base balance analysis process that is operable to serve as a decision support to help clinicians determine treatment and / or set optimal treatment parameters for dialysis patients, such as CKD patients, including CRRT patients (with or without mechanical ventilation). The acid-base balance analysis process can use a computational model ("acid-base model" or "model"). The output of the acid-base model can provide guidance in determining parameters, predicting (e.g., patient acid-base characteristics) treatment, treatment recommendations, treatment adjustments, etc. The acid-base balance analysis process can include using / analyzing citrate and lactate metabolism, ventilation, and / or other parameters. The acid-base model output can provide a prediction of the patient's acid-base status, such as CKD treatment, including individuals receiving CRRT treatment (e.g., renal or respiratory replacement therapy).

[0049] The use of extracorporeal CO2 removal devices (ECCO2RD) in the ICU has been introduced to provide protective ventilation strategies for patients with acute respiratory distress syndrome (ARDS). In general, extracorporeal carbon dioxide removal (ECCO2R) therapy aims to reduce or even eliminate blood CO2 to counteract the adverse effects of certain acid-base imbalances (e.g., acidemia). ARDS patients may experience acute kidney injury (AKI), which may require dialysis therapy. These patients are often subjected to CRRT (or RRT), which may include attaching the ECCO2RD to the hemodialysis (HD) circuit as a combined protective ventilation strategy.

[0050] Therefore, some embodiments can incorporate the model of the dialyzer and / or the model of ECCO2RD into the acid-base model. Non-limiting examples of acid-base models can include models identical to, similar to, and / or adapted from the models described in Cherif et al., "Amathematical model of the four cardinal acid-base disorders", Mathematical Biosciences and Engineering, 17(5): 4457-4476 (2020) ("Cherif et al.") and / or U.S. Patent Application No. 2020 / 0294676, entitled "Techniques for Determining Acid-Base Homeostasis", filed March 11, 2020 ('676 publication) (Cherif et al. and '676 publication are both referred to as "Acid-Base Dynamics Disclosure"), the contents of both of which are incorporated by reference as if fully set forth in the present disclosure.

[0051] A model according to some embodiments may describe H + , CO2 and HCO3 - In various embodiments, the model can be configured to capture continuous veno-venous hemodialysis (CVVHD) using a gas exchanger integrated into an HD system (eg, a continuous HD system).

[0052] In some embodiments, the model can be configured to capture different CRRT modes (e.g., continuous veno-venous hemofiltration (CVVH), CVVHD, continuous veno-venous hemodiafiltration (CVVHDF), and / or the like), for example, with pre-replacement / dilution fluid or post-replacement / dilution fluid, using a pre-filter or post-filter with an attached gas exchanger, and / or the like.

[0053] In some embodiments, the model may be or may include a mathematical model of intradialytic acid-base dynamics in patients receiving extracorporeal CO2 removal.

[0054] The described techniques may generally include an acid-base balance analysis process operable to simulate pH and acid-base balance of one or more patients, one or more patient populations, one or more virtual patients, and / or one or more virtual patient populations. In some embodiments, the patient and / or virtual patient may be or may include one or more patients, one or more physiological systems (e.g., renal system, pulmonary system, respiratory system, organs thereof, functions thereof, etc.), one or more patient populations, portions thereof, virtual models thereof, etc. In some embodiments, the acid-base balance analysis process may use one or more acid-base models, which may include the major physiological components and mechanisms controlling pH and acid-base balance of a patient, including a healthy (or normal) patient, a patient with an abnormality or disease, and / or a patient undergoing a therapeutic regimen (e.g., dialysis, such as HD).

[0055] In various embodiments, the acid-base model may include one or more physiological acid-base models (e.g., a general model of a patient) and one or more intradialytic acid-base models to simulate dialysis patients and dialyzer operation. In various embodiments, the intradialytic acid-base model may include one or more dialysis patient models (e.g., a functionally impaired model corresponding to a dialysis patient, such as impaired renal regulation) and a dialyzer model to simulate intradialytic dynamics associated with pH and acid-base balance.

[0056] In some embodiments, the acid-base model can operate as a dynamic model of physiological regulation of the HCO3 / CO2 buffer system. In various embodiments, the acid-base model can be configured at least in part using or based on Henderson-Hasselbalch kinetics. For example, some embodiments can include an acid-base model of the HCO3 / CO2 buffer system with Henderson-Hasselbalch mass action kinetics.

[0057] In an exemplary embodiment, the acid-base model can simulate normal physiological conditions and several acid-base imbalances, including but not limited to metabolic acidosis, metabolic alkalosis, respiratory acidosis, and / or respiratory alkalosis.

[0058] Regulation of pH and acid-base balance in the blood and extracellular fluids plays a key role in many aspects of cellular metabolism and other physiological functions. The effects of acid-base changes have far-reaching implications. In addition to physicochemical buffering, acid-base balance is also regulated by the respiratory and renal systems. Changes in pH can affect many physiochemical reactions and buffering systems, transport / channel dynamics, muscle contraction, metabolic enzyme reactivity, and protein / membrane structure and function. Changes in pH can also affect other functions, including the cardiovascular, central nervous, renal, and pulmonary systems, tissue metabolism and oxygenation, and bone remodeling. For example, chronic H + Retention leads to increased muscle protein degradation and muscle wasting. In addition, through different synergistic pathways, H + Retention also increases osteolysis, cell-mediated bone resorption, and decreases bone formation. + Retention can also lead to kidney damage and kidney stones and may accelerate the progression of CKD.

[0059] Pulmonary ventilation is controlled by arterial CO2 partial pressure (pCO2), oxygen partial pressure, and pH. Central chemoreceptors (located near the ventral surface of the medulla oblongata in the brain) and peripheral chemoreceptors (located in the carotid and aortic bodies of the aortic arch) respond to changes in pCO2 by triggering respiratory responses, which in turn affect bicarbonate (HCO3 or - ) concentration, thus changing the pH level. Likewise, the kidneys are responsible for regulating HCO3 through reabsorption, production, and, in some cases, excretion of HCO3. The kidneys reabsorb nearly all of the altered HCO3 in the proximal and distal segments of the nephron and produce new HCO3 to replace the amount consumed by acid by excreting titratable acid and ammonium.

[0060] Simple alterations in acid-base balance may include one of four major conditions: metabolic acidosis, metabolic alkalosis, respiratory acidosis, and respiratory alkalosis. In addition to these simple acid-base changes, combinations ("mixed" acid-base disorders) may occur. Whether an acid-base disorder is metabolic or respiratory depends on whether the changes in HCO3 or pCO2 are due to abnormalities in renal or respiratory function, respectively. In particular, the acid-base disorder is called metabolic when the primary abnormality is attributable to changes in HCO3, which are either due to changes in net HCO3 or pCO2. + The acid-base imbalance is due to an imbalance between the production and renal HCO3 reabsorption, or due to defects in the renal or gastrointestinal absorption and secretion of HCO3. If the primary abnormality is due to changes in pCO2 caused by an imbalance between the metabolic production of CO2 and its excretion by the lungs or abnormal respiratory function, the acid-base imbalance can be called respiratory. If the blood pH is below or above the normal physiological range, the acid-base imbalance state is acidosis or alkalosis, respectively. In some embodiments, the normal physiological range can be a pH of about 7.40 ± 0.02. Therefore, acidosis or alkalosis can refer to H +The process by which concentration increases or decreases.

[0061] Figure 1 An example of an operating environment 100 that may represent some embodiments is shown. Figure 1 As shown, operating environment 100 may include acid-base analysis system 105. In various embodiments, acid-base analysis system 105 may include computing device 110 communicatively coupled to network 190 via transceiver 180. In some embodiments, computing device 110 may be a server computer or other type of computing device.

[0062] According to some embodiments, computing device 110 may be configured to manage operational aspects of the acid-base balancing process, among other things. Figure 1 Only one computing device 110 is depicted in the figure, but the embodiments are not limited in this regard. In various embodiments, the functions, operations, configurations, data storage functions, applications, logic, etc. described with respect to computing device 110 may be performed by and / or stored in one or more other computing devices (not shown), which are coupled to computing device 110 (e.g., one or more of client or peer devices 194) via network 190, for example. A single computing device 110 is depicted for illustrative purposes only to simplify the figure. The embodiments are not limited in this context.

[0063] The computing device 110 may include a processor circuit 120, which may include and / or access various logics for performing a process according to some embodiments. For example, the processor circuit 120 may include and / or access acid-base balance analysis logic 130, acid-base model logic 132, dialysis patient model logic 134, dialyzer model logic 136, and / or ECCO2RD model logic 138. The processor circuit 120, acid-base model logic 132, dialysis patient model logic 134, dialyzer model logic 136, and / or ECCO2RD model logic 138 and / or parts thereof may be implemented in hardware, software, or a combination thereof. As used in this application, the terms "logic", "component", "layer", "system", "circuit", "decoder", "encoder", "control loop", and / or "module" are intended to refer to an entity associated with a computer, or a combination of hardware, hardware and software, software, or software in execution, an example of which is provided by an exemplary computing architecture 2800. For example, logic, circuits, or modules may be and / or may include, but are not limited to, a process running on a processor, a processor, a hard drive, multiple storage drives (optical and / or magnetic storage media), an object, an executable file, an execution thread, a program, a computer, a hardware circuit, an integrated circuit, an application specific integrated circuit (ASIC), a programmable logic device (PLD), a digital signal processor (DSP), a field programmable gate array (FPGA), a system on a chip (SoC), a memory cell, a logic gate, a register, a semiconductor device, a chip, a microchip, a chipset, a software component, a program, an application, firmware, a software module, computer code, a control loop, a computational model or application, an artificial intelligence model or application, a machine learning model or application, variations thereof, combinations of any of the foregoing, and / or the like.

[0064] Although the acid-base balance analysis logic 130 Figure 1 120, but the embodiments are not limited thereto. For example, the acid-base model logic 132, the dialysis patient model logic 134, the dialyzer model logic 136, and / or the ECCO2RD model logic 138 and / or any components thereof may be located in an accelerator, a processor core, an interface, a separate processor die, fully implemented as a software application (e.g., an acid-base balance analysis application 160), etc.

[0065] The memory unit 140 may include various types of computer-readable storage media and / or systems in the form of one or more high-speed memory units, such as read-only memory (ROM), random access memory (RAM), dynamic RAM (DRAM), double data rate DRAM (DDRAM), synchronous DRAM (SDRAM), static RAM (SRAM), programmable ROM (PROM), erasable programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), flash memory, polymer memory (e.g., ferroelectric polymer memory), Osborn memory, phase change or ferroelectric memory, silicon-oxide-nitride-oxide-silicon (SONOS) memory, magnetic or optical card, device array (e.g., redundant array of independent disks (RAID) drive), solid-state storage device (e.g., USB memory, solid-state drive (SSD), and any other type of storage medium suitable for storing information. In addition, the memory unit 140 may include various types of computer-readable storage media in the form of one or more low-speed memory units, including an internal (or external) hard disk drive (HDD), a magnetic floppy disk drive (FDD), an optical drive that reads from or writes to a removable optical disk (e.g., CD-ROM or DVD), a solid-state drive (SSD), and the like.

[0066] According to some embodiments, the memory unit 140 may store various types of information and / or applications for the acid-base balance process. For example, the memory unit 140 may store acid-base information 150, patient information 152, dialyzer information 154, ECCO2RD information 156, treatment recommendations 158, and / or acid-base balance analysis applications 160. In some embodiments, some or all of the acid-base information 150, patient information 152, dialyzer information 154, ECCO2RD information 156, treatment recommendations 158, and / or acid-base balance analysis applications 160 may be stored in one or more data storage devices 192a-n accessible to the computing device 110 via the network 190. For example, one or more of the data storage devices 192a-n may be or may include a clinical data repository or database, a health information system (HIS), an electronic medical record (EMR) system, a dialysis information system (DIS), a picture archiving and communication system (PACS), a Centers for Medicare and Medicaid Services (CMS) database, a United States Renal Data System (USRDS), a proprietary database, and the like. In some embodiments, memory 140 and / or data sources 192a - n may store historical patient population information, for example, for use in validating acid-base model results according to some embodiments.

[0067] In some embodiments, acid-base balance analysis logic 130 is operable to simulate acid-base balance according to some embodiments, for example, via acid-base model logic 132 and / or acid-base balance analysis application 160. In various embodiments, acid-base balance analysis logic 130 is operable to simulate the acid-base balance of a dialysis patient undergoing dialysis treatment according to some embodiments, for example, via acid-base model logic 132 and / or acid-base balance analysis application 160. Dialysis patient model logic 134 is operable to realize a dialysis patient model according to various embodiments. According to some embodiments, dialyzer model logic 1386 is operable to realize a dialyzer model. According to some embodiments, ECCO2RD model logic 138 is operable to realize ECCO2RD.

[0068] In various embodiments, the acid-base information 150 may include parameters, variables, values, etc. used by the acid-base balance analysis logic 130 and the acid-base model and / or its components implemented by the acid-base balance analysis logic 130. Among the various information, the acid-base information 150 may include information generated by the acid-base model. For example, in various embodiments, the acid-base information 150 may include predicted patient information determined by the model. For example, the predicted patient information may include predicted pH (e.g., serum pH), pCO2, and / or HCO3.

[0069] In an exemplary embodiment, patient information 152 may include information associated with a patient and / or an actual patient of a virtual patient and / or historical information modeled via an acid-base model according to some embodiments, for example, for teaching or verifying an acid-base model. Non-limiting examples of patient information 152 may include sex, age, weight, dry weight, treatment regimen (e.g., HD) and dosage (e.g., HCO3), pre- / post-dialysis information (e.g., pH, pCO2, pO2, HCO3) and / or the like. In various embodiments, dialyzer information 154 may include information associated with an actual or virtual (i.e., modeled) dialyzer for an acid-base model and / or its verification, such as ultrafiltration volume (UFV), UF rate (UFR), dialyzer type, machine model, treatment mode (hemodialysis, hemodiafiltration, etc.), operating parameters, etc. In various embodiments, ECCO2RD156 may include information associated with an actual or virtual ECCO2RD and / or its operation.

[0070] In some embodiments, treatment recommendations 158 may include treatment recommendations, suggestions, plans, information, etc. generated by an acid-base model according to various embodiments. For example, an acid-base model according to some embodiments may generate treatment recommendations 158 for a real-world patient and / or patient population based on model results generated for a corresponding virtual patient and / or patient population. Non-limiting examples of treatment recommendations may include administering HCO3- supplements, acid binders, hemodialysis bicarbonate dialysate, and / or patient dietary instructions (e.g., limiting excessive consumption of acidic foods). In a specific example, treatment recommendations 158 may include a prescription for optimizing the dialysate bicarbonate concentration to restore acid-base balance without producing an "overshoot" metabolic alkalosis. In some embodiments, treatment recommendations 158 for patients and / or patient populations may be generated based on primary parameters and / or predicted patient information for the patients and / or patient populations (and / or virtual realizations thereof) associated with the patients and / or patient populations (e.g., patient populations with specific characteristics (e.g., gender, weight, health status, etc.)). In some embodiments, primary parameters may include one or more parameters that affect a certain condition. For example, for a healthy individual, the primary parameters that affect pH are parameters related to renal function (acid secretion rate). and Reabsorption rate ), treat The reaction rate or pK of a buffer system a , the production of protons (P H ) and removal or non-bicarbonate buffering parameters. Treatment targeting these parameters may have a strong effect on correcting pH disturbances. Therefore, these can be the main parameters of pH acid-base balance in healthy individuals. For individuals with metabolic acidosis, the main parameters can include respiratory CO2 removal Supplement or treatment ( such as NaHCO3 or HD), hydration reaction rate And / or removal of excess protons (eg, by supplementation with an acid-binding agent) would be effective.

[0071] In some embodiments, such as by acid-base model logic 132 (see e.g. Figure 2) can be operated to model the acid-base balance of a patient and / or a patient population to determine predicted patient information (e.g., pH level, pCO2 level, and / or HCO3 level). In various embodiments, the acid-base model can model the acid-base imbalance of a specific patient population to determine predicted patient information (e.g., pH level, pCO2 level, and / or HCO3 level). The acid-base model can be used to determine predicted patient information (predicted treatment information) for certain treatments, which can model the patient's treatment outcome. In some embodiments, treatment recommendations may include maintaining / adjusting acid-base balance. Due to the accuracy of the acid-base model described in some embodiments in predicting treatment outcomes, the acid-base model can be used to generate useful treatment recommendations for patients compared to conventional systems. In some embodiments, the main parameters can be determined based on the predicted patient information (e.g., running the acid-base model to determine the main parameters that affect the acid-base imbalance). Treatment recommendations 158 can be targeted at influencing the main parameters in order to effectively address the condition. The embodiments are not limited to this context.

[0072] Some embodiments may provide an acid-base model in the form of a physiological acid-base model. In various embodiments, the physiological acid-base model may provide a physiological model describing acid-base balance under normal (or substantially normal) physiological conditions, which may be used, for example, to analyze the effects of pathophysiological acid-base perturbations on the acid-base status of a patient (or virtual patient). In an exemplary embodiment, the physiological acid-base model may be operable to model, process, analyze, experiment, or otherwise simulate Physiological regulation of the CO2 / CO2 buffer system, including Henderson-Hasselbalch mass action kinetics, CO2 and H + Endogenously produced, non-bicarbonate buffered and / or renal and respiratory regulated.

[0073] Various embodiments may provide an acid-base model in the form of an intradialytic model. In some embodiments, the intradialytic model may be or may include a dialysis patient model (e.g., implemented via dialysis patient model logic 134), which may include an implementation of a physiological acid-base model for a dialysis patient characterized by impaired renal regulation replaced by dialysis (e.g., hemodialysis (HD)).

[0074] As described in more detail below, the acid-base model according to some embodiments can be used to predict treatment outcomes and / or provide treatment recommendations for various acid-base imbalances. In some embodiments, certain model parameters can be changed to determine their impact on acid-base balance. For example, changes in acid secretion rate parameters and renal filtration rate parameters (e.g., reducing or eliminating these parameters (e.g., setting their model values ​​to zero)) can simulate acid-base imbalances, such as renal failure, metabolic acidosis, metabolic alkalosis, respiratory acidosis, respiratory alkalosis, etc. Based on the specific configuration and operating procedures of the acid-base model according to some embodiments, they can be used to accurately predict changes in parameters that affect acid-base balance.

[0075] In some embodiments, the acid-base balance logic 130 is operable to receive patient information 152 (e.g., sex, age, health status (e.g., renal failure, normal, etc.), HCO3 level, pH, etc.) for a particular patient and determine treatment recommendations 156 for maintaining acid-base balance and / or treating acid-base imbalance. For example, the method for correcting insufficient HCO3 levels for a healthy person may be different from that for a patient with metabolic acidosis. In some embodiments, the acid-base model can be used to model, predict, or otherwise process various treatment models (e.g., acid binder therapy, HCO3 therapy, etc.) to determine, predict, or otherwise analyze treatment outcomes that can be used to determine an actual patient treatment regimen. In some embodiments, the acid-base balance logic 130 may include, implement, or otherwise process a feedback loop (or iteration) function for continuously using the acid-base model to adjust acid-base conditions, including through dialysis modifications (e.g., adjusting ultrafiltration rate and / or volume), or administering medications, bicarbonate, etc. based on continuously predicted patient information. In some embodiments, while treatment is being administered (e.g., during dialysis, supplemental dosing, etc.), treatment information can be used as input to an acid-base model to generate updated predicted patient information, which can then be used to determine treatment outcomes and / or update treatment recommendations (including in real time or substantially real time, such as during dialysis treatment).

[0076] Figure 2 An example of an operating environment 200 that may be representative of some embodiments is shown. Figure 2 As shown, operating environment 200 may include acid-base model 205 depicting an illustrative model structure according to the present disclosure. For example, Figure 2 The structure between different elements of the acid-base model according to some embodiments may be represented. In various embodiments, the acid-base model 205 may include a patient model (or element) 210 , a dialyzer model 220 , an ECCO2RD model 230 , and / or a dilution model 240 .

[0077] Figure 2The configuration of the acid-base model 205 depicted in FIG. 2 is for non-limiting illustrative purposes. For example, according to some embodiments, the acid-base model 205 may have a different form, configuration, etc. For example, the acid-base model 205 may have more or fewer elements, and / or elements arranged in a different configuration. For example, the acid-base model may not include the dialyzer model 220 and / or the ECCO2RD model 230. In another example, the dialyzer model 220 and / or the ECCO2RD model 230 may be in a different position (e.g., as shown in FIG. 2 ). Figure 2 As shown, the dialyzer model 220 and the ECCO2RD model 230 may swap their positions).

[0078] In a further example, the dilution model 240 can be inserted anywhere in the circuit (e.g., between the patient model 210 and the dialyzer model 220; between the dialyzer model 220 and the ECCO2RD model 230; between the ECCO2RD model 230 and the patient model 210; and / or the like). In various embodiments, the dilution model 240 can operate or represent an increase in blood flow rate (Q) between the models 210, 220, and / or 230 and an appropriate decrease in concentration.

[0079] In some embodiments, the models 210, 220, 230, and / or 240 of the acid-base model 205 may exchange the values ​​of Q and H. + , HCO - and CO2 (e.g., C H , C HCO , C CO These inputs / outputs can be represented as boundary conditions within the acid-base model 205.

[0080] The concentrations of hydrogen and CO2 can be expressed by solution pH and carbon dioxide partial pressure (pCO2). In some embodiments, the conversion between pH and carbon dioxide partial pressure can be performed according to the following equation (1):

[0081]

[0082] in,

[0083] Figure 3 An example of a patient model 210 that may represent some embodiments is shown. In general, Figure 3 Input 310 and output 320 are depicted from the perspective of patient (or patient model) 210. In various embodiments, input 310 may be or may include Q in , C H , In some embodiments, output 320 may be or may include Q out , CH ,

[0084] In some embodiments, The steady-state kinetics of the / CO2 acid-base system can be the same or similar to the kinetics described by Cherif et al. The steady-state kinetics of the / CO2 acid-base system may include the following equations (2)-(4):

[0085]

[0086]

[0087]

[0088] in From Henderson-Hasselbalch mass action dynamics.

[0089] When the patient model 210 is included in a blood circuit with a dialyzer (e.g., dialyzer model 220), changes in total blood volume (e.g., by fluid removal) may be included. From the patient's perspective, such as through the patient model 210, such changes may be given by the following equation (5):

[0090]

[0091] In various embodiments, equations (2)-(4) can be rewritten in terms of moles, for example, for each concentration C i =n i / V,n i The derivative of can be given by the following formula (6):

[0092]

[0093] In some embodiments, when included, the inflow rate (C i,in ) may be different from the concentration of the outflow flow; therefore, the acid-base model 205 may include the following equation (7) (or equations (7a)-(7d)):

[0094]

[0095]

[0096]

[0097]

[0098] At each concentration, C i =n iIn various embodiments of / V, if Q in =Q out =0, then Then equations (7a)-(7d) can be rewritten back to the original form of equations (2)-(4).

[0099] Figure 4 An example table 400 according to the present disclosure is shown. More specifically, table 400 shows the values ​​and units of constants and variables in Cherif et al., and their respective SI unit values. Conversion factors are also present if applicable. For example, the values ​​in table 400 are adjusted so that pH = 7.4, pCO2 = 40 mmHg, and C HCO3 = 2.4 mM is the fixed point of equations (7a)-(7d).

[0100] In some embodiments, the dialyzer model 220 may be configured to be the same as or very similar to a parallel plate heat exchanger or model thereof. In various embodiments, the equations for the dialyzer model may be the same as, similar to, based on, and / or adapted from the equations described in the acid-base kinetics disclosure.

[0101] In various embodiments, the dialyzer model 220 may be configured to simulate intradialytic dynamics related to pH and acid-base balance. In some embodiments, the dialyzer model 220 may be configured to model an HD dialyzer. In an exemplary embodiment, the dialyzer model 220 may be configured to quantify and H + Intradialytic dynamics, which can be parameterized to simulate anuric patients receiving HD. In some embodiments, the dialyzer model 220 may include, be identical or substantially identical to, or be an adaptation of, the dialyzer model described in Maheshwari et al., “An In Silico Method to Predict Net Calcium Transfer During Hemodialysis,” 2017 39th Annual IEEE Engineering in Medicine and Biology Society International Conference (EMBC), pp. 2740-2743 (2017).

[0102] In various embodiments, the acid-base model 205 and / or models thereof may be the same as or similar to a physiological acid-base model, for example, as described in the acid-base kinetics disclosure.

[0103] For example, the physiological acid-base model according to some embodiments can be operated to simulate the effects of systemic acid-base balance. In some embodiments, the physiological acid-base model can be implemented using a coupled nonlinear ordinary differential equation system, for example, to describe the acid-base buffering dynamics through the HCO3-CO2 system and in combination with related physiological regulatory mechanisms. In some embodiments, the physiological acid-base model can focus on the HCO3-CO2 buffering dynamics, which is the most effective buffering system for controlling systemic pH.

[0104] The pH of the extracellular fluid is regulated primarily by three mechanisms, which act on different time scales: (i) chemical acid-base buffering, (ii) respiratory control, and (iii) renal filtration. The following equation (8) provides an illustrative and non-limiting HCO3 buffering system according to some embodiments:

[0105]

[0106] In some embodiments, in equation (8), it can be assumed that carbonic anhydrase (CA) accelerates the carbonation reaction.

[0107] Chemical acid-base buffering prevents excessive changes in pH, with the time scale for this process typically measured in seconds. The ability of the lungs to increase or decrease ventilation enables them to regulate the removal of CO2 from the extracellular fluid in the form of gases in the exhaled breath, thereby regulating pH. In particular, since CO2 is constantly produced as a byproduct of cellular metabolism, the ventilation rate must be able to adapt to changes in CO2 in order to balance the pH of the extracellular fluid. Although this process is rapid, occurring within minutes, it is not as effective as chemical buffering. If the acid-base imbalance persists, the kidneys will excrete the excess acid or base, and this adaptation process takes hours to days.

[0108] The kidneys represent a very powerful regulatory system capable of converting large amounts of H + The ability to secrete into the tubular lumen. In addition, the excretion and reabsorption of HCO3 occur in the proximal and distal tubules. In particular, in the proximal tubule, H + By Na + / H + Antiport promotes secretion, and HCO3 is secreted by + In intercalated cells, H + / Cl - Cotransporters promote H + Although this process only accounts for the secretion of H + 5%, but it further secretes more H into the renal tubular lumen + Provides a gradient. Most of the secreted H+ Used to recover filtered HCO3, and the rate of HCO3 reabsorption is related to the rate of acid excretion.

[0109] To model the acid-base balance process, a physiological acid-base model according to some embodiments can track the bicarbonate concentration Carbon dioxide concentration and free hydrogen proton concentration Utilizing Henderson-Hasselbalch mass action kinetics and renal and pulmonary regulatory mechanisms, the steady-state kinetics of the HCO3 / CO2 acid-base system modeled by the physiological acid-base model according to some embodiments can be configured according to the following equations (9)-(11) (i.e., the physiological acid-base model equations or the bicarbonate buffer kinetic system):

[0110]

[0111]

[0112]

[0113] In some embodiments, in equations (9)-(11), The initial conditions are as follows: and The patient (or virtual patient) can be set to a normal physiological state. Parameters Represents H + The cells produce Indicates that renal clearance and / or non-bicarbonate buffering (eg, with albumin, Ca 2+ , Buffer) caused by H + The hydration and dehydration reaction rates are given by the parameters and where these values ​​can be adjusted to reflect the activity of carbonic anhydrase. In addition, express Treatment and / or supplementation, represents the acid secretion rate, It is CO2 produced by the body or cells (mitochondria), represent Renal filtration rate. Effective ventilation rate reflects the excretion of CO2 from the lungs, where V0 is the minute ventilation, is the ventilation rate. In some embodiments, the kinetics of H2O is not included in equations (9)-(11) because H2O is assumed to be abundant as a solvent. In some embodiments, equations (9)-(11) can be formulated by general expressions (see, e.g., equations (12) and (13)), e.g., using nonlinear ventilation ).

[0114] In various embodiments, the first two terms in equation (9) can account for the production of H + , and removal of H in the form of titratable acid and / or ammonium or non-carbonate buffers (e.g., buffered with phosphate and / or calcium) + The two terms together correspond to the H resulting from buffering by non-bicarbonate buffers and other processes. + Activity. The third and last term in equation (9) corresponds to the buffer reaction kinetics.

[0115] For equation (10), the first term express Treatment, second and third The renal filtration process can be described, where it is assumed that the amount of The amount may be related to the filter load, and The equivalence of reabsorption and acid excretion is achieved by the breakdown of CO2 by the enzymatic activity of intracellular carbonic anhydrase. For example, an increase in CO2 concentration may increase the conversion of CO2 to H in a normally functioning kidney. + and This may result in increased acid secretion in the urine and increased CO2 absorption in the blood. Therefore, the second term of equation (3) can describe the acid secretion, while the third term is the filtered load.

[0116] Similarly, equation (11) can be related to the buffer dynamics, where the first term can be CO2 production in vivo (e.g., cellular metabolism or mitochondrial processes), and the second It is the lungs that remove CO2 through respiratory ventilation, which may depend on blood volume, cardiac output, and arteriovenous CO2 difference (e.g., the difference in concentration between arterial and venous blood). To simplify the model, some embodiments may assume that the ventilation rate V0 is constant; however, V0 may depend on pCO2, oxygen partial pressure (pO2), and / or pH.

[0117] In some embodiments, the item can be nonlinear and can represent the effective ventilation rate, D CO2 V(Y CO2 ) in becomes the ventilation rate and V represents the minute ventilation. The empirical ventilation function can take the form of one of the following equations (12) or (13):

[0118] V1(pCO2, pO2) = V0 + Vp e -0.05pO2(t) max {0, pCO2(t)-I p} (12),

[0119]

[0120] Where V0 and V p represents the baseline and slope parameters, I p is the cutoff threshold. In terms of ventilation, the role of the pH sensor in the medulla oblongata in regulating bicarbonate buffer homeostasis is considered to be negligible. The ventilation term V1(pCO2,pO2) above involves the interaction between the partial pressures pCO2 and pO2 and their effects on ventilation. In V2(pCO2,pO2), V2(pCO2,pO2) uses the oxygen saturation function It can be expressed as pO2. The relationship between pCO2 and In some embodiments, we can also assume that pO2 is constant. Under normal pO2, for every 1 mmHg increase in pO2, ventilation increases by 2.5 L / min. According to the above equations (5) and (6) and Figure 2 , for a given pCO2 and the steepness of the net effective slope of ventilation, reducing pO2 will increase ventilation. Assuming pO2 is constant or provided by an exogenous source, the term V0 can be replaced by any of the above functional expressions. In some embodiments, a simplified version according to some embodiments can be used to determine acid-base dynamics, thereby reducing the number of model parameters that need to be identified. In other embodiments, all effects of ventilation can be concentrated into the ventilation rate parameter. In some embodiments, equations (12) and (13) can provide a general physiological acid-base model (for example, equations (9)-(11) are specific implementations thereof).

[0121] In various embodiments, the acid-base model 205 and / or models thereof may be the same as or similar to intradialytic acid-base models, for example, as described in the acid-base kinetics disclosure.

[0122] Figure 5 FIG. 4 shows a block diagram of an acid-base model in dialysis according to some embodiments. Figure 5 As shown, the intradialysis acid-base model 502 may include a dialysis patient model or compartment 510 and a dialyzer model or compartment 512 having a dialyzer 514. In various embodiments, the patient compartment 510 may include a distribution volume (V ex ) and the concentrations of acid-base variables (e.g. ). In some embodiments, Q p , Q d and Q ufare respectively the plasma flow rate, the dialysate flow rate and the ultrafiltration rate. A single dialyzer fiber 516 can depict the countercurrent interaction between the blood and the dialysate flow in the dialyzer 514, where there is an intradialytic transfer between the blood and the dialysate through an infinitesimal fiber segment Δx. The subscripts q and C represent plasma (pl) or extracellular fluid (ex), dialyzer input (di) and output (do), dialyzer blood inlet (pi) and outlet (out).

[0123] For the dialysis patient model, some embodiments may use a physiologically based dynamic model that describes the / CO2 buffer system, in which we combine CO2 and H + Endogenous production, non-bicarbonate buffering, and excretion by ventilation and kidneys / Physiological regulation of CO2 buffer systems. Although other buffer systems exist, some embodiments may focus primarily on / CO2 buffer system, which is the most abundant and effective buffer system in the body. Under physiological conditions, pH is mainly regulated by chemical acid-base buffering, respiratory control, and glomerular filtration. Chemical acid-base buffering is modeled using Henderson-Hasselbalch mass action kinetics, where in some embodiments, carbonic anhydrase acts very quickly and is and association and dissociation rates.

[0124] During normal cellular metabolic activity, CO2 and H + As a by-product; this endogenous production is respectively CO2 and H + of and In addition, acids are mobilized or buffered by other non-bicarbonate buffers (e.g., phosphates), which Indicates that is the rate of mobilization or removal. Under normal physiological conditions, the kidneys (the second regulatory organ) are responsible for + Secreted into the tubular lumen and / or excreted or reabsorbed in the proximal and distal parts of the nephron To adjust Unlike the physiological acid-base model according to some embodiments, the dialysis patient model may not include (or may include a less functional) and H +renal regulation because the dialysis patient model is adapted for dialysis patients with impaired acid excretion. As a result, in some embodiments, the dialysis patient model may assume little or even no renal function. In some embodiments, renal function is substituted by using a dialyzer (e.g., by dialyzer flux) implemented via a dialyzer model. For example, the expression and The bicarbonate flux from the patient and the post-dialysis flux to the patient can be explained separately and are characterized by the blood flow rate, Q p , and ultrafiltration rate, Q uf For the third regulatory mechanism, to regulate CO2 clearance, the lungs increase or decrease ventilation, which is triggered by central and peripheral chemoreceptors in response to changes in pCO2, and Describes the lung's ability to clear CO2 through ventilation, as characterized by blood volume, cardiac output, and arteriovenous CO2 difference. and V0 are ventilation rate and minute ventilation, respectively. In some embodiments, the dialysis patient model describing acid-base balance can be based on the following equations (14)-(16):

[0125]

[0126]

[0127]

[0128] During dialysis, the patient loses a large amount of fluid. Assume this is at a constant ultrafiltration rate Q uf The volume of extracellular fluid can be determined according to the following equation (17):

[0129]

[0130] In some embodiments, the dialyzer model may include two space-time models describing the blood side and the dialysate side using hyperbolic partial differential equations. The concentration can be determined according to the following formula (18):

[0131]

[0132] Where N is the number of fibers, A represents the fiber cross-sectional area, express Reflection coefficient, Peclet number is defined as follows: L is the fiber length, K is O A is is the effective membrane mass transfer coefficient, and β is the Gibbs-Donnan correction factor (i.e., the Gibbs-Donnan correction dialyzer model). In some embodiments, β can be set to a constant value of 1.05, which corresponds to 5% of In various embodiments, for the dialyzer side, it can be assumed that the dialysate flow is uniform and is equally shared by the N fibers present in the dialyzer housing. The hyperbolic partial differential equation describing the concentration within the annular dialysate flow boundary can have the form of the following equation (19):

[0133]

[0134] Among them A d is the circular cross-sectional area of ​​the annular space around the fibers where the dialysate flows. In various embodiments, the plasma flow rate (Q p ) may decrease along the fiber length in the dialyzer due to ultrafiltration, which decrease may decrease linearly along the fiber length. In some embodiments, the dialysate flow rate may increase the amount of fluid removed from the blood side to the dialysate side by ultrafiltration, resulting in countercurrent dynamics. The spatial aspects of the plasma and dialysate flow rates may be determined according to the following equations (20) and (21):

[0135]

[0136]

[0137] Where Q pi and Q di are the initial plasma and dialysate flow rates.

[0138] In some embodiments, equations (14)-(21) may form part of an intradialytic acid-base model that describes, simulates, predicts, or otherwise addresses intradialytic acid-base dynamics.

[0139] Figure 6 Table 600 is shown of a first set of illustrative acid-base model parameters and values, according to some embodiments. Figure 7 A second set of illustrative acid-base model parameters and values ​​are shown in table 700 according to some embodiments. In some embodiments, for the dialyzer model, the hydration rate and dehydration rate (K H and ) can differ by an order of magnitude from the differences described in the acid-base kinetics disclosure.

[0140] Fig. 8A and 8B 1 shows simulation results of a physiological acid-base model according to some embodiments. More specifically, Fig. 8A Results 810 from a published acid-base model of acid-base kinetics are depicted. Figure 8BResults 820 of an acid-base model (eg, acid-base model 205 ) are depicted according to some embodiments. Fig. 8A and 8B The result is that when, for example, residual renal function is not included in the model, only one ρ residual is obtained when it is zero.

[0141] Fig. 9 An illustrative ECCO2RD model 230 according to some embodiments is depicted. In some embodiments, the ECCO2RD model 230 can be approximately modeled as a one-dimensional (1D) diffusion device between blood and air. In various embodiments, the ECCO2RD model 230 can receive an input 910 to generate an output 920. Fig. 9 As shown, the dynamics of the ECCO2RD model 230 may include the following equations (22a) and (22b):

[0142]

[0143]

[0144] In some embodiments, equations describing the kinetics of the ECCO2RD model 230, such as equations (22a) and (22b), may be the same as, similar to, and / or adapted from equations described in “Mathematical Modeling of Extracorporeal CO2 Removal Therapy” by Habran et al. (Medical & Biological Engineering & Computing, 56(3):421–434 (2018) (“Habran et al.”), the contents of which are incorporated by reference as if fully set forth in the present disclosure. Fig.10 Depicted is a table 1000 providing illustrative values ​​for the parameters used in equations (22a) and (22b):

[0145] Figures 11A-11D Depicts the results of an acid-base model according to some embodiments. More specifically, Fig.11A The results for patients with normal renal function are depicted; Fig. 11B The results for patients without renal function are depicted; Fig. 11C Describes the calculation Results as a function of time at the measurement point; Fig.11D The time evolution results of the model with validation data are depicted.

[0146] In some embodiments, the results of the ECCO2RD model can be determined as Q d=268mL / min, the patient's parameter can be Q p =350 mL / min, V0 = 0 L / min and the patient has intact residual renal function (ρ residual =1). The optimized parameters can be P H =1.6962×10 -7 mol / L / min, γ=2.9864×10 3 min-1, V blood =0.5294L, V gas =2.9694L.

[0147] Example of results: Validation of the acid-base model

[0148] According to Forster et al., "Low-flow CO2 removal integrated into a renal-replacement circuit can reduce acidosis and decrease vasopressor requirements" (Crit Care 17, R154 (2013). https: / / doi.org / 10.1186 / cc12833), the model was validated using the average data of 10 ventilated critically ill patients with ARDS and AKI who received renal and respiratory replacement therapy. The following parameter values ​​were set at the beginning of treatment: blood flow 355±79ml / min, dialysate flow 2.3±7L / h, ultrafiltration rate 58±66ml / h, gas flow 5.2±1.0L / min, and treatment time 95±68h. The model was parameterized to obtain patient-specific parameters. Fig.12 Results of an acid-base model according to some embodiments are depicted, wherein results of model predictions for a patient with renal failure and hypoventilation are depicted. Fig.12 In the figure, the solid line is the model prediction; the dots are the patient data. Fig.12 As shown, models according to some embodiments are able to accurately predict changes in pH and pCO2 over time, for example, at least for the first 24 hours after treatment.

[0149] Fig.13 An embodiment of an exemplary computing architecture 1300 suitable for implementing various embodiments as previously described is shown. In various embodiments, the computing architecture 1300 may include or be implemented as part of an electronic device. The embodiments are not limited in this context.

[0150] As used in this application, the terms "system," "component," and "module" are intended to refer to a computer-related entity, which can be hardware, a combination of hardware and software, software, or software in execution, examples of which are provided by exemplary computing architecture 1300. For example, a component can be, but is not limited to, a process running on a processor, a processor, a hard drive, multiple storage drives (of optical and / or magnetic storage media), an object, an executable file, an execution thread, a program, and / or a computer. For example, an application running on a server and a server can both be components. One or more components can reside in a process and / or execution thread, and a component can be localized on one computer and / or distributed across two or more computers.

[0151] In addition, components can be communicatively coupled to each other via various types of communication media to coordinate operations. Coordination may involve unidirectional or bidirectional information exchange. For example, components can transmit information in the form of signals transmitted via a communication medium. The information can be implemented as signals assigned to various signal lines. In such an assignment, each message is a signal. However, other embodiments may alternatively employ data messages. Such data messages can be sent via various connections. Exemplary connections include parallel interfaces, serial interfaces, and bus interfaces.

[0152] The computing architecture 1300 includes various common computing elements, such as one or more processors, multi-core processors, coprocessors, memory units, chipsets, controllers, peripherals, interfaces, oscillators, timing devices, video cards, audio cards, multimedia input / output (I / O) components, power supplies, etc. However, embodiments are not limited to the implementation of the computing architecture 1300.

[0153] like Fig.13 As shown, computing architecture 1300 includes a processing unit 1304, a system memory 1306, and a system bus 1308. Processing unit 1304 may be a commercially available processor and may include dual microprocessors, multi-core processors, and other multi-processor architectures.

[0154] The system bus 1308 provides an interface to the processing unit 1304 for system components including, but not limited to, the system memory 1306. The system bus 1308 may be any of several types of bus structures, which may further interconnect to a memory bus (with or without a memory controller), a peripheral bus, and a local bus using any of a variety of commercially available bus architectures. Interface adapters may be connected to the system bus 1308 via a slot architecture. Exemplary slot architectures may include, but are not limited to, Accelerated Graphics Port (AGP), Cardbus, (Extended) Industry Standard Architecture ((E)ISA), Micro Channel Architecture (MCA), NuBus, Peripheral Component Interconnect (Extended) (PCI(X)), PCI Express, Personal Computer Memory Card International Association (PCMCIA), and the like.

[0155] The system memory 1306 may include various types of computer-readable storage media in the form of one or more high-speed memory cells, such as read-only memory (ROM), random access memory (RAM), dynamic RAM (DRAM), double data rate DRAM (DDRAM), synchronous DRAM (SDRAM), static RAM (SRAM), programmable ROM (PROM), erasable programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), flash memory, polymer memory (e.g., ferroelectric polymer memory), bidirectional memory, phase change or ferroelectric memory, silicon-oxide-nitride-oxide-silicon (SONOS) memory, magnetic or optical cards, arrays of devices such as redundant arrays of independent disks (RAID) drives, solid-state storage devices (e.g., USB memory, solid-state drives (SSDs), and any other type of storage medium suitable for storing information. Fig.13 In the illustrated embodiment, the system memory 1306 may include non-volatile memory 1310 and / or volatile memory 1312. A basic input / output system (BIOS) may be stored in the non-volatile memory 1310. The computer 1302 may include various types of computer-readable storage media in the form of one or more low-speed memory units, including an internal (or external) hard disk drive (HDD) 1314, a magnetic floppy disk drive (FDD) 1316 for reading or writing to a removable disk 1311, and an optical drive 1320 for reading or writing to a removable optical disk 1322 (e.g., a CD-ROM or DVD). The HDD 1314, the FDD 1316, and the optical drive 1320 may be connected to the system bus 1308 via a HDD interface 1324, a FDD interface 1326, and an optical drive interface 1328, respectively. The HDD interface 1324 for external drive implementation may include at least one or both of a universal serial bus (USB) and an IEEE 114 interface technology.

[0156] The drives and associated computer-readable media provide volatile and / or nonvolatile storage of data, data structures, computer-executable instructions, etc. For example, a number of program modules may be stored in the drives and memory units 1310, 1312, including an operating system 1330, one or more application programs 1332, other program modules 1334, and program data 1336. In one embodiment, the one or more application programs 1332, other program modules 1334, and program data 1336 may include, for example, various applications and / or components of a computing device.

[0157] A user can enter commands and information into the computer 1302 through one or more wired / wireless input devices, such as a keyboard 1338 and a pointing device such as a mouse 1340. These and other input devices are typically connected to the processing unit 1304 through an input device interface 1342 coupled to the system bus 1308, but may be connected by other interfaces.

[0158] A monitor 1344 or other type of display device is also connected to the system bus 1308 via an interface, such as a video adapter 1346. The display 1344 may be internal or external to the computer 1302. In addition to the display 1344, computers typically include other peripheral output devices such as speakers, printers, etc.

[0159] The computer 1302 can operate in a network environment using logical connections to one or more remote computers (e.g., remote computer 1348) via wired and / or wireless communications. The remote computer 1348 can be a workstation, server computer, router, personal computer, portable computer, microprocessor-based entertainment device, peer device, or other common network node, and typically includes many or all of the elements described relative to the computer 1302, but for the purpose of simplicity, only a memory / storage device 1350 is shown. The depicted logical connections include wired / wireless connections to a local area network (LAN) 1352 and / or a larger network (e.g., a wide area network (WAN) 1354). Such LAN and WAN network environments are common in offices and companies and facilitate the establishment of enterprise-wide computer networks, such as intranets, all of which can be connected to a global communication network, such as the Internet.

[0160] The computer 1302 is operable to communicate with wired and wireless devices or entities using the IEEE 802 family of standards, such as wireless devices that are operatively arranged in wireless communications (e.g., IEEE 802.16 over-the-air modulation techniques). This includes at least Wi-Fi (or Wireless Fidelity), WiMax, and Bluetooth. TMWireless technology, etc. Therefore, the communication can be a predefined structure like a traditional network, or just an ad hoc communication between at least two devices. Wi-Fi networks use radio technologies called IEEE802.11x (a, b, g, n, etc.) to provide secure, reliable, and fast wireless connections. Wi-Fi networks can be used to connect computers to each other, to the Internet, and to wired networks (using IEEE802.3 related media and functions).

[0161] Many specific details have been set forth herein to provide a thorough understanding of the embodiments. However, those skilled in the art will appreciate that the embodiments may be practiced without these specific details. In addition, well-known operations, components, and circuits are not described in detail to avoid confusing the embodiments. It is understood that the specific structural and functional details disclosed herein may be representative and do not necessarily limit the scope of the embodiments.

[0162] Some embodiments may be described using the expressions "coupled" and "connected" and their derivatives. These terms are not synonymous with each other. For example, some embodiments may be described using the terms "connected" and / or "coupled" to indicate that two or more elements are in direct physical or electrical contact with each other. However, the term "coupled" may also mean that two or more elements are not in direct contact with each other, but still cooperate or interact with each other.

[0163] Unless otherwise specifically stated, it is understood that terms such as "processing", "computing", "calculating", "determining", etc. refer to the actions and / or processes of a computer or computing system or similar electronic computing device that manipulates and / or transforms data represented as physical quantities (e.g., electronic quantities) within registers and / or memories of the computing system into other data similarly represented as physical quantities within the memory, registers, or other such information storage, transmission, or display devices of the computing system. The embodiments are not limited in this context.

[0164] It should be noted that the methods described herein do not have to be executed in the order described or in any particular order. In addition, the various activities described with respect to the methods identified herein can be executed in serial or parallel manner.

[0165] Although specific embodiments have been illustrated and described herein, it should be understood that any arrangement calculated to achieve the same purpose may replace the specific embodiments shown. The present disclosure is intended to cover any and all modifications or variations of various embodiments. It should be understood that the above description is carried out in an illustrative manner rather than a restrictive manner. After reading the above description, the combination of the above-described embodiments and other embodiments not specifically described herein will be apparent to those skilled in the art. Therefore, the scope of the various embodiments includes any other application using the above-mentioned compositions, structures and methods.

[0166] Although the subject matter has been described in language specific to structural features and / or methodological acts, it is to be understood that the subject matter defined in the appended claims is not necessarily limited to the specific features or acts described above. Rather, the specific features and acts described above are disclosed as example forms of implementing the claims.

[0167] As used herein, elements or operations recorded in the singular and processed with the word "a" or "an" should be understood as not excluding plural elements or operations, unless such exclusion is explicitly recorded. In addition, reference to "one embodiment" of the present disclosure is not intended to be interpreted as excluding the existence of additional embodiments that also include the listed features.

[0168] The scope of the present disclosure is not limited to the specific embodiments described herein. In fact, in addition to those described herein, various other embodiments and modifications of the present disclosure will be apparent to those of ordinary skill in the art based on the foregoing description and accompanying drawings. Therefore, such other embodiments and modifications are intended to fall within the scope of the present disclosure. In addition, although the present disclosure has been described herein in the context of a specific implementation for a specific purpose in a specific environment, it will be appreciated by those of ordinary skill in the art that its practicality is not limited thereto, and the present disclosure can be beneficially implemented in any number of environments for any number of purposes. Therefore, the claims described below should be interpreted according to the full scope and spirit of the present disclosure as described herein.

Claims

1. A device comprising: at least one processor; and a memory coupled to the at least one processor, the memory comprising instructions that, when executed by the at least one processor, cause the at least one processor to: accessing an acid-base model configured to simulate the acid-base balance of a patient, the acid-base model comprising a patient model, a dialyzer model, and an extracorporeal CO2 removal device ECCO2RD model, and Determine predicted patient information using the acid-base model.

2. The apparatus of claim 1, wherein the predicted patient information comprises at least one of a blood flow rate (Q), a serum pH level, a pCO2 level, or an HCO3 level.

3. The apparatus of claim 1, wherein when executed by the at least one processor, the instructions cause the at least one processor to determine continuous renal replacement therapy (CRRT) parameters based on the predicted patient information to control acid-base status.

4. The device according to claim 1, wherein the acid-base model is configured to simulate H + , CO2 and of adjustment.

5. The apparatus of claim 1 , wherein the patient model is configured to simulate patient physiology, wherein the input is blood flow and the output is hydrogen ion concentration, carbon dioxide concentration, and bicarbonate concentration. The apparatus according to claim 1 , wherein the dialyzer model is configured to simulate continuous renal replacement therapy (CRRT).

7. The apparatus according to claim 1, wherein the ECCO2RD model is configured to simulate a one-dimensional 1D diffusion device between blood and air.

8. The apparatus according to claim 1, the acid-base model comprising a blood flow circuit, the blood flow circuit flowing from the patient simulated by the patient model to the dialyzer simulated by the dialyzer model, to the ECCO2RD simulated by the ECCO2RD model, and back to the patient.

9. The apparatus of claim 1, the blood flow circuit comprising diffusion at any point in the blood flow circuit.

10. The apparatus of claim 1, the patient comprising a virtual patient.

11. The apparatus of claim 1, the predicted patient information comprising a treatment recommendation.

12. The device of claim 11, the treatment recommendation comprising a course of treatment for an acid-base imbalance.

13. A computer-implemented method for acid-base balance analysis, the method comprising, by a processor of a computing device: providing an acid-base model configured to simulate the acid-base balance of a patient, the acid-base model comprising a patient model, a dialyzer model, and an extracorporeal CO2 removal device ECCO2RD model, and Determine predicted patient information using the acid-base model.

14. The computer-implemented method of claim 13, the predicted patient information comprising at least one of blood flow rate (Q), serum pH level, pCO2 level, or HCO3 level. 15 . The computer-implemented method of claim 13 , further comprising prescribing continuous renal replacement therapy (CRRT) parameters to control acid-base status based on the predicted patient information.

16. The computer-implemented method of claim 13, wherein the acid-base model is configured to simulate H + , CO2 and of adjustment.

17. The computer-implemented method of claim 13, wherein the patient model is configured to simulate patient physiology with blood flow as input and hydrogen ion concentration, carbon dioxide concentration, and bicarbonate concentration as output.

18. The computer-implemented method of claim 13, the dialyzer model being configured to simulate continuous renal replacement therapy (CRRT).

19. The computer-implemented method of claim 13, wherein the ECCO2RD model is configured to simulate a one-dimensional 1D diffusion device between blood and air.

20. The computer-implemented method of claim 13, the acid-base model comprising a blood flow circuit from a patient simulated by the patient model, to a dialyzer simulated by the dialyzer model, to an ECCO2RD simulated by the ECCO2RD model, and back to the patient.

21. The computer-implemented method of claim 13, the blood flow circuit comprising diffusion at any point in the blood flow circuit.

22. The computer-implemented method of claim 13, the patient comprising a virtual patient.

23. The computer-implemented method of claim 13, the predicted patient information comprising a treatment recommendation.

24. The computer-implemented method of claim 23, the treatment recommendation comprising a course of treatment for an acid-base imbalance.

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