Continuous potassium measurement system and uses thereof

Abstract

A continuous potassium measurement system for determining potassium levels in a user over time is provided. The system includes a continuous potassium sensor (CPS) positioned in interstitial fluid of the user. The system further includes programmed circuitry comprising a processor and a memory where the CPS and programmed circuitry are communicatively coupled. The programmed circuitry is programmed with logic and instructions for completion of the following steps by the programmed circuitry: (i) obtaining data related to the level of potassium in the user from the CPS; (ii) determining the level of potassium in the user from the data obtained in step (i); (iii) storing the level of potassium in the user determined in step (ii) in the memory; and (iv) repeating steps (i) to (iii) to determine and store in the memory potassium levels in a user over time.

Description

[0001] Title:

[0002] Continuous potassium measurement system and uses thereof

[0003] Cross-Reference to Related Applications:

[0004] The present application can be used alone or in combination with any of the devices and / or method as described in: PCT / US2022 / 037198 (PROT.P-OOl-WO); PCT / US2022 / 052927 (PROT.P-002-WO); PCT / IB2023 / 061417(PROT.P-003-WO); and US Prov. Pat. App. Ser. No. US 63 / 523,060 (PROT.P-004-PV), which are all incorporated by reference for all purposes. The present application claims priority to US Prov. Pat. App. Ser. No. 63 / 605,425 fried on December 1, 2023, which is incorporated in its entirety by reference.

[0005] Background of the Invention:

[0006] Potassium level is a critical indicator of a person’s health and well-being, which impacts or is indicative of various bodily functionalities including renal and / or cardiac functions. Existing methods for monitoring potassium levels are intermittent and require periodic invasive procedures and periodic manual testing in a professional healthcare setting. This prevents realtime monitoring of the analyte and hence limits visibility into a person’s bodily functions and overall health. There is a need for a continuous potassium measurement system that can monitor potassium levels in a user over time, along with other functionalities, and for use of such systems in providing accurate and timely data for better health management and insights into bodily functions.

[0007] Summary of the Invention:

[0008] The continuous potassium measurement system and method of its use herein described comprise a sophisticated setup enabling continuous, and / or semi-continuous, monitoring of a user's potassium levels over time. The system and methods integrate and communicatively couple a continuous potassium sensor (CPS) and programmed circuitry equipped with a processor, memory, and a suite of functionalities, facilitating data collection, analysis, storage, and provision of alerts based on the collected and / or determined data. The systems and methods aim to improve healthcare management by providing accurate and timely information about an individual's potassium levels over time, allowing for proactive health measures and interventions.

[0009] In a first embodiment the present invention provides a continuous potassium measurement system for determining potassium levels in a user over time. The system includes a continuous potassium sensor (CPS) positioned in interstitial fluid of the user and configured to determine data related to a potassium level in the user. The system also includes programmed circuitry comprising a processor and a memory communicatively coupled with the CPS. The programmed circuitry is programmed with logic and instructions for completion of the following steps by the programmed circuitry: (i) obtaining data related to the level of potassium in the user from the CPS; (ii) determining the level of potassium in the user from the data obtained in step (i); (iii) storing the level of potassium in the user determined in step (ii) in the memory; and (iv) repeating steps (i) to (iii) to determine and store in the memory potassium levels in a user over time.

[0010] Using this system as a base continuous potassium measurement system, the present invention provides a host of other functionalities, systems, and methods which provide insights into patient health, treatment protocols, population health, and related concerns.

[0011] Brief Description of the Figures:

[0012] Fig. 1 shows an exemplary system according to the present invention.

[0013] Fig. 2, shows correlation of raw voltage data into potassium levels.

[0014] Fig. 3 shows correlation between voltage measured by the CPS and potassium concentration which can be used as part of conversion algorithms with optional additional correction factors. Fig. 4 shows how CPS measurements may track a patient's potassium concentration over time in an exemplary case..

[0015] Detailed Description of the Invention:

[0016] The present invention provides solutions to the long-felt desire and need of the ability to continuously measure a user’s potassium levels in a discrete, user-friendly, manner without the need and costs associated with healthcare office visits. As shown in Fig. 1 and described herein, the continuous potassium measurement system 101 includes multiple components and functionalities, each serving a specific role in the continuous monitoring and determination of potassium levels in a user 103. The system's 101 components include the continuous potassium sensor (CPS) 105, programmed circuitry 107 incorporating a processor 109 and memory 111. In additional embodiments the system also includes a user computing device 113, a remote server (shown in Fig. 1 as 107), and healthcare provider computing device 115. The user computing device 113 and / or healthcare computing device 115 preferably include respective software applications (e.g. a user application and a healthcare provider application) running on resident programmed hardware. These respective computing devices are preferably included, and in operative communication (as represented with arrows), with the programmed circuitry of the presently contemplated systems and allow data transfer and communication between all of the user, the healthcare provider, processing, memory, and CPS. Furthermore, these respective devices can include user interface hardware for display of information of alerts and interaction therewith. In preferred embodiments, the respective computing devices are selected from the group consisting of personal computers, laptops, cell phones, tablets, or other known computing devices. Data collection, processing, and memory storage preferably occur in the remote server 107, however can occur in part or entirety in any, or combination of the user computing device 113, remote server 107 (e.g. cloud server / storage / processing), and / or healthcare computing device 115.

[0017] The CPS 105 can be that as described in any of the above-mentioned references which are incorporated herein by reference, or any other sensor adapted for and capable of determining potassium level in a user. A portion of the CPS 105 is positioned in the interstitial fluid of the user and is responsible for obtaining data related to the user's potassium levels. The CPS includes sensor electronics (e.g. a power source such as a battery and a wireless transmitter for transmitting data all of which are optionally disposed within a housing on the skin of a user and being configured to maintain the CPS in interstitial fluid of a user) and measures and transmits data, typically in the form of voltage measurements, to the programmed circuitry 107, optionally through a user computing device 113 (as shown via arrows).

[0018] Programmed circuitry 107, including processor 109 and memory 111, is equipped with logic and instructions programmed to perform specific tasks related to the data by the CPS. These tasks include data acquisition from the CPS, processing of the obtained data to determine the user's potassium level and storing this information in memory 11 1. The programmed circuitry repeats these steps continuously, upon request, or at regular intervals, ensuring continuous (or semi- continuous or intermittent) monitoring and storage of potassium levels of the user over time.

[0019] The term continuous and semi-continuous are used interchangeably herein and include: constant measurement of data relating potassium levels and / or determination of the level; and / or measurement of data and determination of potassium levels upon request or at predetermined (e.g. regular) time intervals, ranging from seconds to hours. In preferred embodiments, the steps are repeated at regular time intervals selected from the group consisting of: 1 second, 5 seconds, 10 seconds, 15 seconds, 30 seconds, 1 minute, 5 minutes, 10 minutes, 15 minutes, 30 minutes, 1 hour, 2 hours, 6 hours, 12 hours, 24 hours (preferably in 5-15 minute intervals).

[0020] An exemplary algorithm for determination of potassium levels in a user can be seen in Figs. 2, 3, and 4. In a first step shown in Fig. 2, data relating to potassium level of a user is continuously determined / obtained by a potassium specific sensor, here CPS, positioned in interstitial fluid of a user. Here, the data is raw voltage data collected by the sensor in volts (or volts over a period of time). This data is then converted or correlated via use of a correlation or offset factor (e.g. via a lookup table, conversion chart, and / or recovery algorithm) into determined potassium levels of the user over time. Figure 3 shows a correlation calculation between the voltage measured by the CPS and the potassium concentration which will be used as part of the conversion algorithm with additional correction factors. Other signal processing techniques can be applied to, or in lieu of, the above-described steps and do not depart from the scope of the present invention. Such techniques include but are not limited to: drift correction; filtering algorithms; calibration techniques; signal conditioning and / or filtering; application of correction and / or offset factors; etc. The CPS data and / or determined potassium levels are stored in the memory of the programmed circuitry. The respective data can be associated with a timestamp for tracking (e.g. chronological tracking) of data and / or values overtime. Figure 4 shows how CPS measurements may track a patient's potassium concentration over time in an exemplary case.

[0021] In addition to potassium level monitoring, the programmed circuitry can integrate functionalities for handling dietary and activity input, activity tracking, medication delivery tracking (e.g. orally and / or intravenously delivered etc.), medication protocol, health tracking and time stamp association. This integration involves modules comprising logic and instructions and / or hardware for receiving, storing, and associating medication, dietary and / or activity input with the stored potassium levels. The system can further comprise hardware and respective data collection modules commonly available including hardware for such functionalities such as an accelerometer, an activity tracker, blood pressure monitor, PulseOx, smart medication dispenser tracker, and / or a heart rate monitor etc. Any and / or all of the herein described, timestamp, medication, dietary input, activity tracking and / or input, and health tracking etc. can be stored together with the potassium level data, for example as metadata, optionally in an aggregated data file, which can provide useful context for current interpretation and / or later interpretation of the potassium level data.

[0022] In additional embodiments, the system can include a variety of correlation modules (e.g. software and / or instructions executable by a processor) programmed to: provide instantaneous alerts regarding current potassium levels, predict future potassium levels, to compare potassium level data obtained over time, compare activity and dietary data, compare and optionally suggestion modifications to medication intake data and protocols, analyze trends and other stored data, determine rate of changes in levels; predict from the rate of change the timeframe for reaching a particular state of kalemia, and / or determine correlations indicating changes in potassium levels and / or overall health of a user and / or overall functionality of a user’s organs including the heart, kidneys, and liver etc. Based on the determined correlations, the system can generate alerts for users and / or healthcare providers, offering alerts and / or instructions and / or recommendations tailored to the observed correlation, potassium levels and / or changes thereof over time. The alerts vary according to the detected correlation, such as the current or approaching conditions of normokalemia, hyperkalemia, severe hyperkalemia, and / or hypokalemia, and to providing actionable guidance to the user and / or her health care provided to better manage the user's health effectively.

[0023] Additionally, the methods and systems herein described can include a stored data summary module which can obtain from memory the stored potassium level(s) and / or data files such as the aggregated data file described above and generate a report and / or summary report for each user and / or health care provider which reports individual CPS data and / or summaries CPS data and optionally other data such as biometric providing contextual information about the potassium data. This may include, but is not limited to, current / past / predicted potassium levels, mean potassium level over a given time period (daily), potassium level trend data and / or rate of change data, a measure of potassium variability such as coefficient of variance or standard deviation, time in a normal range, time above normal range, time below normal range, maximum K+ value, minimum K+ value, number of hypokalemic episodes, number of hyperkalemic episodes, data reliability, sensor wear time, medication levels etc. The reports can be provided and displayed to a user and / or health care provider visually via a graphical user interface and / or audibly via speaker.

[0024] Additionally, the system may determine an estimated potassium and / or lab value based on multiple readings, time of day readings were taken, dietary intake, activity level (e.g, exercise), and further data processing (e.g, removing outliers). The system may likewise generate a report that shows problematic time areas where an individual seems to experience hypo- or hyperkalemia (e.g., K+ spikes at certain times of day such as in the mornings around 8 am most days indicating a change in breakfast is needed.) In another example, K+ levels are correlated to other biomarkers (e.g., eGFR, uACR, ECG) to indicate further disease progression and give realtime disease progression monitoring for kidney and cardiovascular diseases, the functionality of which can be incorporated into any of the described or different correlation and / or results summary modules.

[0025] The result summary module and / or a different module may also provide population health reports observing summary information of a plurality of patients such that summary metrics (estimated lab value, average potassium levels, time in range, max K+, min K+, ect.) are reported for the plurality of patients simultaneous in a report, and provide each patient with an automated suggestion (e.g., confirm K+ level, have staff call the patient, send emergency report, no action needed) for the care team based on the patient data (e.g., dietary input, activity level, demographic or clinical information, ect.) This information can be provided to the healthcare provider team via a patient panel or dashboard, where the team can see patient data and provide recommendations to several patients in a timely manner for compliance and healthcare monitoring. In another example, the data can be used to risk stratify patients for those that are highest risk and those that are lowest risk to allow providers to appropriately manage time, and triage high risk patients. In another example, suggested actions are classified by care provider type allowing for optimized care delivery (e g. suggested dietary actions automatically go to dietician, suggested drug changes go to pharmacist, etc.) through automated care suggestions. In another example, data is used for risk stratification to identify care gaps and inapposite risk adjustment factors (RAF) scores such that K+ levels that likely indicate further disease progression are automatically scheduled for additional labs to confirm disease progression (e.g., eGFR, glucose test, ect.) and adjust RAF scores and again allow the health care team to quickly analyze their patient database and provide recommendations and any protocol changes quickly via use of a dashboard or panel. In another example, CPS is used to categorize patients based on the potassium dynamics and other potential risk metrics and create a triage table across their treated patients.

[0026] In another example, the system can be used to categorize patients based on the potassium dynamics and other potassium-related metrics, as well as other data. This may be how their potassium fluctuates during over a time period, how their potassium responds after dosing of specific potassium-modulating and other medications [e.g., beta-blockers, diuretics, angiotensinconverting enzyme inhibitors (ACEi), angiotensin receptor blockers (ARBs), angiotensin receptor neprilysin inhibitors (ARNIs), or mineralocorticoid receptor antagonists (MRAs), K+ binder use], or how their potassium levels respond to consumption of a fixed amount of potassium (e.g., potassium challenge with an oral K+ supplement or fixed meal.) The categorization can then be used to determine / predict likely response to a therapy (e.g., medications or diet), determine / predict disease progression (e.g., CKD or heart failure progression), or indicate the need for more or less monitoring.

[0027] Potassium levels for each of the outlined conditions and respective actions are not particularly limited herein. For example, severe hypokalemia is typically associated with a user having a serum potassium level of less than 3.0 mM / L, hypokalemia is often associated with a user having a serum potassium level of less than 3.5 mM / L, normokalemia is often associated with a user having a serum potassium level of between 3.5-5.0 mM / L, hyperkalemia is often associated with a user having a serum potassium level of greater than 5.0 mM / L, while extreme hyperkalemia is often associated with a user having a serum potassium level of 5.5 mM / L or greater. The exact threshold of each state of kalemia can be determined by patient characteristics based on clinical judgment and may vary, and may be determined or changed by the user and / or healthcare provider. Several different alerts and / or recommendations are contemplated depending on the determined correlation and / or current or future predicted potassium level. Contemplated alerts include providing an indication or alert of the current potassium level and / or health condition of the user (e.g. user is in a specific state of kalemia); a recommendation to maintain or change diet (e.g. maintain or increase / decrease ingestion of potassium containing foods / beverages), activity (take a walk), medication protocol (dosage and / or type of potassium lowering or raising medication for example those selected from the group consisting of IV calcium, IV insulin / glucose, nebulized salbutamol, IV sodium bicarbonate, diuretics, dialysis, K+ binders); initiate dialysis; seek emergency medical attention and optionally directions to the closest emergency facility; contact the user and / or health care provider. The user may also be using CPS data for improvement in health and wellness or athletic performances, such that potassium levels are being monitored and recommended actions are related to the amount of dietary or oral supplemental potassium and the timing to take it to maintain or improve performance.

[0028] In other embodiments the correlation module can be programmed to determine and act upon longer term trends, rates of change in levels, and / or specific daily trends regarding observed correlations surrounding particular events such as meals, sleep, wakefulness, medications and / or activities. For example, the correlation module can be employed in further management of chronic disease states wherein the correlation module can be programmed to determine longer term trends and / or rates of change in potassium levels to determine disease progression and to provide related alerts to the user or healthcare provider regarding longer term or timing of suggested changes in diet, activity levels, and / or medication protocols etc.

[0029] In yet further embodiments, the system can further incorporate a continuous analyte sensor (CAS) also positioned in interstitial fluid to monitor and determine levels of other analytes, such as sodium, calcium, magnesium, glucose, chloride, and / or creatine. The programmed circuitry for the CAS operates similarly to that for potassium monitoring by acquiring data, determining analyte levels, and storing this information for analysis, alerting and comprehensive health monitoring. The data received from the CAS and determined analyte levels can be used alone or together with the data regarding potassium levels determined by the CPS in a correlation module to determine particular health related events and associated alerts. For example, the CAS can determine data related to glucose or sodium levels in the user and when combined and correlated with the potassium levels determinations provided by the system and can provide an indication related to secondary therapies such as insulin levels and / or suggested insulin dosage of the user and / or providing an indication related to organ health, volume status and / or hydration levels in the user.

[0030] In still a further embodiment, the present system can further include a prescription medication lockbox containing medication and being maintained by the user. The lockbox is communicatively coupled to the programmed circuitry and the programmed circuitry further comprises logic and instructions for unlocking the lockbox in response to one or more stimuli selected from the group consisting of: an instruction from a health care provider; a determination of a correlation; and potassium levels determined in step (ii) and / or stored in step (iii). Where the system further comprises a heart rate monitor, the programmed circuitry preferably is configured to determine a cardiac event of a user and logic and instructions for unlocking the lockbox in response to a cardiac event determined by the heart rate monitor.

[0031] In further embodiments the present invention provides a data file, an aggregated data file, a data storage system, etc. comprising potassium levels obtained by a potassium measurement system or methods described herein. Such files and systems can include further data obtained from other systems which provide contextual information which allow for understanding of the potassium levels and can be stored in an aggregated data files, for example as metadata. Furthermore, an audible and / or visual display for producing and / or containing an alert produced by a potassium measurement system or methods described herein is herein provided.

[0032] In further embodiments, stored and / or real time CPS data from the CPS can be further analyzed to create predictive algorithms on the likelihood of reaching different kalemic states in the future and provide an audible or visual display alerting the user or care provider and suggesting possible actions described above. Different audible or visual displays can be used to indicate the severity or urgency of risk level with colors, frequency of alerts, directionality of arrows, etc. Additionally, CPS data can be combined with other data such as other analyte levels (e.g., sodium, glucose), patient characteristics (e.g., age, health conditions), patient medications [e.g., beta-blockers, diuretics, angiotensin-converting enzyme inhibitors (ACEi), angiotensin receptor blockers (ARBs), angiotensin receptor neprilysin inhibitors (ARNIs), or mineralocorticoid receptor antagonists (MRAs), K+ binder use], activity levels, dietary intake, patient actions, and or therapy actions (e.g., taking a K+ binder after an alert), and make predictions about the likelihood of a future kalemic state. In a specific example, factors impacting insulin levels are considered for future kalemic states including exogenous insulin, glucose levels (such as from a continuous glucose monitor), and patient characteristics (e.g., insulin sensitivity, diabetes disease progression status, kidney disease progression, etc.). In another example, other electrolyte levels are considered (such as from a CAS) and patient characteristics (e.g., insulin sensitivity, diabetes disease progression status, kidney disease progression, etc.).

[0033] In another embodiment, the CPS data is considered with other data metrics related to the effectiveness of certain medications in which K+ imbalances are an undesired side effect. For example, cardiorenal medications’, such as RAASi (e.g., angiotensin-converting enzyme inhibitors (ACEi), angiotensin receptor blockers (ARBs), angiotensin receptor neprilysin inhibitors (ARNIs), or mineralocorticoid receptor antagonists (MRAs)), effectiveness is measured by one or more biometrics (e.g., pulmonary artery pressure, edema, fluid load, interstitial pressure, sodium levels) and it is ensured the desired therapeutic effect is occurring for example by referencing to a lookup table; then K+ levels are measured (via the CPS) to ensure the K+ is not out of normal range; finally, the system can automatically suggest possible dose or timing adjustment of medications to ensure desired effect is achieved while K+ balance is maintained (e.g., down titrating a RAASi is hyperkalemic state is occurring while achieve cardiovascular effect, or up-titrating RAASi if therapeutic effect isn’t happening while K+ is normal). In another example, K+ changes are part of the desired effect (e.g., diuretic reducing K+ levels, insulin resulting in intracellular K+ update) and taken as an indication of appropriate treatment for suggested dose / timing adjustment to be provided to a user. In another example, patient characteristics (e.g., age, health conditions, etc ), other user input (e.g., diet, activity, etc.), and the details about the therapy management strategy (e.g., aim for max tolerated RAASi dose) from either imported data (e.g., electronic medical records or administrative claims data) or user / provider inputted data is considered in suggested clinical actions. In yet another example, the suggested treatment is transmitted to a drug delivery system (such as a wearable medication delivery system (e.g. insulin pump or a diuretic delivery system such as Furoscix) and the dosage or timing is automatically altered. In this example, this may be an iterative process to maintain therapeutic goals where one can determine therapeutic goals of using one medication without altering K+ levels and / or where K+ levels are used in the determination of medication levels to treat alternative illness (e.g. such as insulin in diabetics). In another example, changes in K+ are used to determine therapy adherence or non-adherence (e.g., decreases in K+ may indicate adherence to K+ binders, lack of temporary increase in K+ may indicate non-adherence to RAASi) and automatically sends nudges, messages, or other automated actions to improve adherence.

[0034] In another example, a CPS is used to assess insulin dynamics, with or without concurrent glucose data. Both endogenous and exogenous insulin can promote the transport of potassium into cells, thereby lowering extracellular potassium levels measured by CPS. Glucose intake stimulates endogenous insulin release, except in certain individuals such as those with type 1 diabetes or late-stage type 2 diabetes. By monitoring a known amount of glucose — either from a glucose challenge or through glucose measurements such as a finger-stick glucometer or a continuous glucose monitor (CGM), the present invention allows one to assess the impact of the resulting insulin release by analyzing the amount and rate of change in potassium levels measured by CPS. Additionally, using the herein teachings, one can use the amount and rate of change in potassium levels measured by CPS to assess the response to known exogenous insulin, insulin-modulating agents, or therapies that impact insulin sensitivity (e.g., rapid-acting insulin, short-acting insulin, long-acting insulin, ultra-long-acting insulin, mixed insulin formulations, insulin secretagogues, incretins, biguanides, thiazolidinediones, SGLT-2s etc.). The CPS measurements can then be interpreted to assess: 1) diabetes disease progression (e.g., early, middle, and late-stage type 2 diabetes, pre-diabetes, type 1 diabetes, etc.); 2) physiological factors such as insulin sensitivity, insulin secretion, and beta-cell function; and 3) therapy needs based on the expected results from diabetes medications (e.g., how much external insulin a patient needs, or therapy adjustments including those selected from the group consisting of: determining appropriate dosages of exogenous insulin; selecting suitable oral hypoglycemic agents; adjusting treatment regimens for optimal glycemic control; predicting the necessity for combination therapies; and tailoring personalized medicine approaches etc).

[0035] In another example, the present invention provides a method for real-time monitoring and management of potassium levels in acute clinical scenarios using a CPS. This method is particularly applicable when administering agents that significantly impact potassium dynamics as part of emergency medical interventions. For example, during the treatment of acute hyperkalemia, patients may receive therapeutic agents such as intravenous calcium compounds (calcium gluconate or calcium chloride), insulin combined with glucose infusion, nebulized beta- 2 adrenergic agonists (albuterol / salbutamol, levalbuterol), intravenous sodium bicarbonate, diuretics including loop diuretics (furosemide, bumetanide, torsemide) and thiazide diuretics (hydrochlorothiazide, chlorthalidone), potassium-binding agents (sodium polystyrene sulfonate, patiromer, sodium zirconium cyclosilicate), or may undergo dialysis procedures (hemodialysis, peritoneal dialysis). By utilizing the CPS to continuously measure extracellular potassium levels, clinicians can precisely control the rate at which potassium concentrations decrease, adjusting dosing and administration in real-time to achieve desired therapeutic outcomes safely and effectively. In many of these scenarios, the administration of the desired therapeutic could be automatically adjusted in a closed loop scenario where therapy (e.g., insulin, diuretic, dialysis) is automatically adjusted (e.g., increase or decrease agent, rate of dialysis) in response to CPS data such that therapeutic benefit is obtained while keeping potassium within the desired preset limits. Specifically, insulin and diuretics are available for delivery in pump systems and dialysis rate or dialysate concentration can be modulated.

[0036] Similarly, in the management of acute hypokalemia, the method involves administering intravenous or oral potassium supplements (potassium chloride, potassium phosphate, potassium bicarbonate) and employing potassium-sparing diuretics (spironolactone, eplerenone, amiloride, triamterene). The CPS enables continuous monitoring of potassium levels, allowing healthcare providers to regulate the rate of potassium correction and prevent complications associated with rapid electrolyte shifts by making timely adjustments to the treatment regimen.

[0037] Furthermore, the invention encompasses acute scenarios where agents affecting potassium levels are administered for primary indications other than potassium management, and where potassium dynamics constitute a critical side effect requiring careful control. For instance, during the treatment of diabetic ketoacidosis (DKA) in emergency settings, standard care protocols involve insulin therapy, fluid resuscitation with isotonic saline or balanced crystalloids, and electrolyte replacement. These interventions can precipitate rapid changes in potassium levels, leading to dyskalemia. By integrating the CPS into patient management and / or with automated pharmaceutical dosage and delivery systems (e.g. pharmaceutical delivery devices such insulin and / or pharmaceutical pumps), clinicians can continuously monitor extracellular potassium levels, enabling proactive adjustments to fluid and electrolyte administration rates to prevent dyskalemia and mitigate associated risks. Similar applications extend to the use of diuretics and fluid therapies in fluid resuscitation for conditions such as sepsis or acute blood loss, where continuous potassium monitoring informs real-time therapeutic modifications (either with clinician in the loop or in closed loop system) to maintain electrolyte balance and enhance patient outcomes.

[0038] In another example, the therapy involves a medical device such as a pacemaker, cardiac resynchronization therapy (CRT) device, implantable loop recorder, or other cardiovascular implantable electronic device (CIED). CPS data is used to:

[0039] 1. Indicate the need for such a medical device,

[0040] 2. Monitor the proper functioning of the device, and / or

[0041] 3. Integrate with device data to provide feedback for delivering appropriate therapy (e.g., preventing or treating arrhythmias related to dyskalemia).

[0042] For example, many CIEDs, such as implantable loop recorders, can provide signals similar to ECG or EKG recordings. In this case, CPS data may indicate a high risk of a cardiac event (e.g., sudden cardiac death) caused by potassium imbalances, while the EKG-like signals helps determine if cardiac membrane desensitization has occurred. The CPS or a CAS could be integrated directly into the CIED. Whether integrated or not, the data allows healthcare providers to determine the appropriate care and urgency required (e.g., treat and electrolyte imbalance or treat the desensitization). The CPS data could also be used automatically by the CIED to adjust therapy — for instance, modifying pacing frequency or delivering electrical charges to the heart as needed. Additionally, a CAS, capable of measuring potassium, sodium, calcium, or magnesium, could be used to enable the device to:

[0043] 1. Assess, detect, or rule out causes of QT prolongation, dyskalemia-related EKG changes, torsades de pointes, digoxin toxicity, atrial fibrillation (A-fib), ventricular fibrillation (V- fib), AV blocks, hypothermia, intracranial hemorrhage, myocardial infarction, and heart failure;

[0044] 2. Adjust the therapy provided based on analyte levels; and / or

[0045] 3. Transmit relevant information to the care provider or user for further action. The continuous potassium measurement system and method described herein offer an innovative approach to monitoring and determining potassium levels in a user over time. By combining the CPS comprising programmed circuitry equipped with logic and / or instructions for performing various functionalities and modules (all optionally combined with medication delivery systems) the system enables continuous, real-time monitoring, data analysis, and personalized alerts for effective management of potassium-related health concerns. The detailed description and accompanying drawings elucidate the structure, operation, and capabilities of this novel system, showcasing its potential in healthcare and personal health management.

[0046] The systems and methods described herein preferably comprise hardware and programmed circuitry such as processors, computers and / or local and / or cloud-based servers. The programmed circuity can be resident in specific medical settings (e.g. such as an office) and / or resident in the cloud. Such devices include programmed hardware and / or circuitry, comprising specific logic and / or instructions for performing any and / or all tasks described herein. For example, the programmed hardware and / or circuitry can include logic and / or instructions for receiving and storing potassium and patient-specific data, retrieving / accessing and analyzing stored and / or received data, determining and providing detailed and patient-specific information and treatment plans, providing signals and / or instructions to accomplish therapeutic treatment plans, and / or completing the other relevant steps and tasks outlined herein. Where the system and / or method is coupled with a continuous potassium sensor and / or other health monitor and / or implantable device for delivering a therapy, the programmed circuitry can communicate and receive / provide signals to / from the programmed circuitry for receiving data and / or providing signals or instruction to the relevant device to take a specific action. These methods and systems provide a marked improvement over systems of the art where patient-specific potassium measurements and / or data collection have not been collected in determining patient-specific conditions and / or determining and / or providing therapeutic treatment of the patient-specific conditions. The programmed circuity can now receive and store patient-specific data, access patient-specific data, particularly relating to potassium level data of a user, and the programmed circuity can make determinations related disease state, store related data, access stored data, determine treatment plans, initiate specific therapies amongst a host of other functionalities not ever been provided or understood before. Reference throughout the specification to “one embodiment,” “another embodiment,” “an embodiment,” “some embodiments,” and so forth, means that a particular element (e.g., feature, structure, property, and / or characteristic) described in connection with the embodiment is included in at least one embodiment described herein, and may or may not be present in other embodiments. In addition, it is to be understood that the described element(s) and / or feature(s) of any embodiment may be combined in any suitable manner with any other described embodiments.

Claims

Claims:

1. A continuous potassium measurement system for determining potassium levels in a user over time, the system comprising: a continuous potassium sensor (CPS) positioned in interstitial fluid of the user and configured to determine data related to a potassium level in the user; and programmed circuitry comprising a processor and a memory, wherein the CPS and programmed circuitry are communicatively coupled, and wherein the programmed circuitry is programmed with logic and instructions for completion of the following steps by the programmed circuitry:(i) obtaining data related to the level of potassium in the user from the CPS;(ii) determining the level of potassium in the user from the data obtained in step (i);(iii) storing the level of potassium in the user determined in step (ii) in the memory; and(iv) repeating steps (i) to (iii) to determine and store in the memory potassium levels in a user over time.

2. The system of claim 1, wherein the data related to the level of potassium in the user is a voltage measurement from the CPS, wherein step (i) is performed by obtaining a voltage measurement from the CPS and step (ii) is performed by correlating the voltage measure from the CPS obtained in step (i) to a reference value (e.g. lookup table) to determine the level of potassium in the user.

3. The system of claim 1, wherein the programmed circuitry further comprises: a user computing device running a user application; CPS electronics comprising a wireless transmitter and a power source; and a remote server running a remote server application, wherein the user computing device, CPS electronics and remote server are communicatively coupled, wherein the user application and / or the server application comprises logic and instructions for performing steps (i), (ii), and / or (iii), andwherein the CPS electronics are enclosed within a housing, wherein the housing is disposed on the skin of a user and configured to maintain the CPS in the interstitial fluid of the user.

4. The system of claim 3, wherein the programmed circuitry further comprises: a health care provider computing device running a health care provider application, the health care provider computing device communicatively coupled with the application server or both the application server and the user computing device, wherein the user computing device comprises a user display interface configured to display information to the user, wherein the information is received from the user application, the server application, and / or the health care provider application, wherein steps (i) to (iii) are repeated in step (iv) upon an instruction issued from the user application, health care provider application, and / or the server application.

5. The system of claim 1, wherein steps (i) to (iii) are repeated in step (iv) at regular time intervals selected from the group consisting of 1 second, 5 seconds, 10 seconds, 15 seconds, 30 seconds, 1 minute, 5 minutes, 10 minutes, 15 minutes, 30 minutes, 1 hour, 2 hours, 6 hours, 12 hours, and 24 hours, and wherein step (iii) further comprises associating the level of potassium in the user determined in step (ii) with a timestamp and storing the associated potassium level and time stamp in the memory.

6. The system of claim 1, wherein the programmed circuitry comprises a food intake module configured to receive and store in the memory dietary input from a user or health care professional, and / or wherein the programmed circuitry comprises an activity intake module configured to receive and store in the memory activity input from a user or health care professional about a user’s physical activity level, and / or wherein the programmed circuitry comprises a delivered medication module in communication with a medication delivery system (optionally wherein the system further comprises such medication delivery system) (e.g., insulin pump, wearable diuretic delivery system such as Furoscix, a smart-dispense medication delivery container) to receive and store in memory information relating to medication delivered to the user, andwherein the programmed circuitry is programmed with logic and instructions to store dietary input, physical activity input, and delivered medication information relating to and / or the time stamp in an aggregated data fde with the potassium level of the user, wherein the dietary input, delivered medication information, physical activity input provides context regarding the potassium levels stored over time in step (iv).

7. The system of claim 6, wherein the programmed circuitry is programmed with logic and instructions to store dietary input, physical activity input, and / or the time stamp in an aggregated data fde as metadata with the potassium level of the user, wherein the metadata provides context regarding the potassium levels stored overtime in step (iv), and wherein the programmed circuitry comprises an accelerometer, an activity tracker, and / or a heart rate monitor; the memory comprises accelerometer data, activity tracker data, and / or heart rate monitor data; and the programmed circuitry is programmed with logic and instructions for use of use of data stored in memory in predicting future health events of the user and / or determining health of the user.

8. The system of claim 1, wherein the programmed circuitry further comprises a correlation module programmed with logic and instructions for completion of the following steps by the programmed circuitry:(v) comparing the data relating to the potassium level obtained in step (i), the potassium level determined in step (ii), and / or the potassium level stored in step (iii) to a reference value to determine if a correlation exists; and(vi) if a correlation is determined to exist in step (v) providing an alert to the user and / or healthcare provider, wherein the correlation is selected from the group consisting of user is in normokalemia; user is in hyperkalemia; user is in severe hyperkalemia; user is in hypokalemia; and user is in severe hyperkalemia, and wherein the alert contains information selected from the group consisting of: user is in normokalemia; user is in hyperkalemia; user is in severe hyperkalemia; user is in hypokalemia; and user is in severe hyperkalemia.

9. The system of claim 8, wherein the correlation and alert are selected from the group consisting of: user is in normokalemia and the alert contains instructions selected from the group consisting of: maintain diet; maintain activity level; and maintain medication protocol, user is in hyperkalemia or severe hyperkalemia and the alert contains instructions selected from the group consisting of: maintain or change diet; maintain or change activity level; maintain or change medication protocol; initiate dialysis; go to emergency room and optionally directions to nearest emergency room; contact user; contact healthcare provider; decrease ingestion of potassium containing foods and beverages; increase activity level; take or increase dosage of potassium lowering medication; and initiate a potassium level lowering therapy such as a potassium level lowering therapy selected from the group consisting of IV calcium, IV insulin / glucose, nebulized salbutamol, IV sodium bicarbonate, diuretics, dialysis, K+ binders. user is in hypokalemia and the alert contains instructions selected from the group consisting of: change diet; change activity level; change medication protocol; go to emergency room and optionally directions to nearest emergency room; contact user; contact healthcare provider; increase ingestion of potassium containing foods and beverages; decrease activity level; and take and / or increase dosage of potassium raising medication.

10. The system of claim 1, wherein the programmed circuitry further comprises a correlation module programmed with logic and instructions for completion of the following steps by the programmed circuitry:(v) comparing potassium levels in a user over time determined and stored in memory in step (iv) to determine a rate of change or trend in potassium levels of the user;(vi) determining from the rate of change or trend in potassium level of the user determined in step (iv) if a correlation exists; and(vii) if a correlation is determined to exist in step (vii) providing an alert to the user and / or healthcare provider, wherein the correlation determined in step (vi) is selected from the group consisting of:user is in or approaching normokalaemia; user is in or approaching hyperkalemia; user is in or approaching severe hyperkalemia; user is in or approaching hypokalemia; user is in or approaching severe hypokalemia, and wherein the alert contains information selected from the group consisting of user is in or approaching normokalaemia; user is in or approaching hyperkalemia; user is in or approaching severe hyperkalemia; user is in or approaching hypokalemia; and user is in or approaching severe hypokalemia.

11. The system of claim 10, wherein the correlation and alert are selected from the group consisting of: user is in or approaching normokalemia and the alert contains instructions selected from the group consisting of: maintain diet; maintain activity level; and maintain medication protocol; user is in or approaching hyperkalemia or severe hyperkalemia and the alert contains instructions selected from the group consisting of: change diet; change activity level; change medication protocol; initiate dialysis; go to emergency room and optional directions to nearest emergency room; contact user; contact healthcare provider; decrease ingestion of potassium containing foods and beverages; increase activity level; take or increase dosage of potassium lowering medication; and initiate a potassium level lowering therapy such as a potassium level lowering therapy selected from the group consisting of IV calcium, IV insulin / glucose, nebulized salbutamol, IV sodium bicarbonate, diuretics, dialysis, and K+ binders. user is in hypokalemia and the alert contains instructions selected from the group consisting of: change diet; change activity level; change medication protocol; go to emergency room; contact user; and contact healthcare provide, increase ingestion of potassium containing foods and beverages; change activity level; take or increase dosage of potassium raising medication; and instructions to go to emergency room and / or directions to closest emergency room.

12. The system of claim 10, wherein the correlation module is programmed with logic and instructions for completion of the following further steps: (vii) estimating from the rate of change or trend determined in step (v) a time of reaching hyperkalemia (and / or cardiac event), normokalemia, or hypokalemia in the user and providing an alert to the user and / or healthcare provider13. The system of claim 12, wherein step (ix) further comprises estimating a time of reaching hyperkalemia, normokalemia, or hypokalemia from a data source selected from the group consisting of: activity data of the user, diet of the user; medicating protocol of the user; accelerometer data; activity tracker data; and heart rate monitor data.

14. The system of claims 10, wherein the alert contains instructions sent to a healthcare provider selected from the group consisting of: contact user; consider initiation or a change of a potassium level lowering therapy selected from the group consisting dietary and activity consultation, oral sodium bicarbonate, diuretics, and K+ binders.

15. The system of claim 10, wherein the correlation determined in step (vi) is that potassium level changes at a particular time of day (e.g. after a meal, after an activity, etc.) and the alert contains instructions selected from the group consisting of: change diet at the particular time per day; change activity level at the particular time per day; change medication at the particular time per day.

16. The system of claim 10, wherein the correlation determined in step (vi) is that the trend in potassium level in the user is increasing or decreasing over time and the alert contains instructions selected from the group consisting of: change medication; change diet; change activity level; user kidney function is decreasing; user heart function is decreasing; contact user; and contact health care provider.

17. The system of claim 1, further comprising a medication lockbox having medication disposed therein, wherein the medication lockbox is communicatively coupled to the programmed circuitry, wherein the programmed circuitry further comprises logic and instructions for unlocking the medication lockbox in response to: an instruction from a health care provider; a determination of a correlation; and / or potassium levels determined in step (ii) and / or stored in step (iii).

18. The system of claim 17, further comprising a heart rate monitor configured to determine a cardiac event, wherein the heart rate monitor is communicatively coupled to the programmed circuitry, and wherein the programmed circuitry further comprises logic and instructions forunlocking the medication lockbox in response to a cardiac event determined by the heart rate monitor.

19. A method for determining potassium levels in a user over time, the method comprising the steps of: providing the continuous potassium measurement system as described in claim 1; and the following steps by the programmed circuitry:(i) obtaining data related to the level of potassium in the user from the CPS;(ii) determining the level of potassium in the user from the data obtained in step (i);(iii) storing the level of potassium in the user determined in step (ii) in the memory; and(iv) repeating steps (i) to (iii) to determine and store in the memory potassium levels in a user over time, thereby determining potassium levels in the user over time.

20. A data file and / or data storage system comprising potassium levels obtained by the potassium measurement system of claim 1.

Images