Abstract: Disclosed herein are techniques related to glucose level management without carbohydrate counting. The techniques may involve obtaining contextual information for a meal, predicting amounts of glucose to be absorbed into a bloodstream of the patient over a duration of time due to consumption of the meal based on the contextual information for the meal, determining one or more amounts of insulin to counteract effects of the predicted amounts of glucose, and affecting insulin therapy based on outputting information indicative of the determined one or more amounts of insulin.

Abstract: Techniques for glucose level management are disclosed. In some examples, the techniques may involve obtaining an estimated protein value for a meal and determining an equivalent carbohydrate value for the meal based on the estimated protein value. In some examples, the techniques may involve obtaining an estimated fat value for a meal and determining, based on the estimated fat value, a glucose absorption rate resulting from consumption of the meal. In some examples, the equivalent carbohydrate value and/or the glucose absorption rate may be used to determine an amount of insulin to deliver to a patient to counteract a glucose level increase caused by consumption of the meal. The techniques may further involve generating an output indicative of the amount of insulin to deliver to the patient to counteract the glucose level increase caused by consumption of the meal.

Abstract: Techniques for glucose level management are disclosed. In some examples, the techniques may involve obtaining an estimated protein value for a meal and determining an equivalent carbohydrate value for the meal based on the estimated protein value. In some examples, the techniques may involve obtaining an estimated fat value for a meal and determining, based on the estimated fat value, a glucose absorption rate resulting from consumption of the meal. In some examples, the equivalent carbohydrate value and/or the glucose absorption rate may be used to determine an amount of insulin to deliver to a patient to counteract a glucose level increase caused by consumption of the meal. The techniques may further involve generating an output indicative of the amount of insulin to deliver to the patient to counteract the glucose level increase caused by consumption of the meal.

Abstract: Techniques for determining insulin therapy are described. The techniques include obtaining patient characteristic information for a current patient; determining, with a machine-learning model, an insulin delivery therapy from a plurality of insulin delivery therapies for the current patient based on the patient characteristic information, wherein the machine-learning model is generated based on digital representations of a plurality of patients; and outputting information indicative of the determined insulin delivery therapy.

Abstract: Disclosed herein are techniques related to glucose level management without carbohydrate counting. The techniques may involve obtaining contextual information for a meal, predicting amounts of glucose to be absorbed into a bloodstream of the patient over a duration of time due to consumption of the meal based on the contextual information for the meal, determining one or more amounts of insulin to counteract effects of the predicted amounts of glucose, and affecting insulin therapy based on outputting information indicative of the determined one or more amounts of insulin.

Abstract: Disclosed herein are techniques related to glucose level management without carbohydrate counting. The techniques may involve obtaining contextual information for a meal, predicting amounts of glucose to be absorbed into a bloodstream of the patient over a duration of time due to consumption of the meal based on the contextual information for the meal, determining one or more amounts of insulin to counteract effects of the predicted amounts of glucose, and affecting insulin therapy based on outputting information indicative of the determined one or more amounts of insulin.

Abstract: Disclosed herein are techniques related to personalized event detection. In some embodiments, the techniques may involve obtaining a plurality of glucose measurements indicative of a glucose level in a body of a patient during an analysis interval, obtaining a patient-specific meal detection model that identifies one or more glucose measurement statistics that are correlative to occurrence of a meal for the patient, determining values for the one or more glucose measurement statistics based on the plurality of glucose measurements, determining a meal consumption metric based on the values for the one or more glucose measurement statistics, detecting an occurrence of the meal during the analysis interval based on the meal consumption metric, and in response to detecting the occurrence of the meal, providing an indication of the occurrence of the meal during with the analysis interval.

Abstract: A system for monitoring a patient includes one or more processors and a sensor device implemented in circuitry. The system is configured to measure, using the sensor device, a blood glucose status of the patient, and determine, using one or more processors, an initial insulin dose for the patient based on the blood glucose status of the patient. The system is further configured to optimize the initial insulin dose for the patient, based at least in part on a correction factor, to create an optimized insulin dose for the patient. The system is configured to facilitate therapy, using the one or more processors, based on the determined optimized insulin dose.

Abstract: A processor-implemented method includes causing fluid delivery to a patient based on a first value for a control parameter, identifying a second value for the control parameter based on a determination that a current operational context is associated with the second value, and causing fluid delivery to the patient based on the second value for the control parameter in lieu of the first value for the control parameter.

Abstract: A processor-implemented method includes identifying a reference insulin absorption curve for a patient based on demographic data of the patient, identifying a contextual adjustment factor based on current contextual information for the patient, obtaining an adjusted insulin absorption curve based on the reference insulin absorption curve and the contextual adjustment factor, and causing insulin delivery to the patient based on the adjusted insulin absorption curve.

Abstract: Infusion devices and related medical devices, patient data management systems, and methods are provided for monitoring a physiological condition of a patient. An exemplary method of monitoring a physiological condition of a patient involves obtaining current measurement data for the physiological condition of the patient provided by a sensing arrangement, obtaining a user input indicative of one or more future events associated with the patient, and in response to the user input, determining a prediction of the physiological condition of the patient in the future based at least in part on the current measurement data and the one or more future events using one or more prediction models associated with the patient, and displaying a graphical representation of the prediction on a display device.

Abstract: Infusion devices, systems and related methods of autonomously delivering fluid to a patient are disclosed. One method involves monitoring a current operational context during autonomous operation of the infusion device to deliver fluid to a patient in accordance with an operating mode using an initial value for a control parameter, and in response to identifying an adjusted value for the control parameter associated with the current operational context, autonomously operating the infusion device to deliver the fluid to the patient in accordance with the operating mode using the adjusted value for the control parameter in lieu of the initial value and thereafter reverting the control parameter to the initial value.

Abstract: Infusion devices and related medical devices, patient data management systems, and methods are provided for monitoring a physiological condition of a patient. An exemplary method of monitoring a physiological condition of a patient involves obtaining current measurement data for the physiological condition of the patient provided by a sensing arrangement, obtaining a user input indicative of one or more future events associated with the patient, and in response to the user input, determining a prediction of the physiological condition of the patient in the future based at least in part on the current measurement data and the one or more future events using one or more prediction models associated with the patient, and displaying a graphical representation of the prediction on a display device.

Abstract: Infusion systems, infusion devices, and related operating methods are provided. A method of operating an infusion device involves determining a reference insulin absorption curve for the patient based at least in part on demographic data associated with the patient, determining a contextual adjustment factor based at least in part on a current patient context, calculating an adjusted insulin absorption curve for the patient as a function of the reference insulin absorption curve and the contextual adjustment factor, and determining a bolus dosage of the insulin based at least in part on the adjusted insulin absorption curve.

Abstract: Infusion devices and related medical devices, patient data management systems, and methods are provided for monitoring a physiological condition of a patient. An exemplary method of querying a database involves receiving an input query from a client device, identifying a logical layer of a plurality of different logical layers of the database for searching based at least in part on the input query, generating a query statement for searching the identified logical layer of the plurality of different logical layers of the database based at least in part on the input query, querying the identified logical layer of the database using the query statement to obtain result data, and providing a search result influenced by the result data.

Abstract: Infusion devices and related medical devices, patient data management systems, and methods are provided for monitoring a physiological condition of a patient. An exemplary method of querying a database involves receiving an input query from a client device, identifying a logical layer of a plurality of different logical layers of the database for searching based at least in part on the input query, generating a query statement for searching the identified logical layer of the plurality of different logical layers of the database based at least in part on the input query, querying the identified logical layer of the database using the query statement to obtain result data, and providing a search result influenced by the result data.

Abstract: Infusion devices, systems and related methods of autonomously delivering fluid to a patient are disclosed. One method involves monitoring a current operational context during autonomous operation of the infusion device to deliver fluid to a patient in accordance with an operating mode using an initial value for a control parameter, and in response to identifying an adjusted value for the control parameter associated with the current operational context, autonomously operating the infusion device to deliver the fluid to the patient in accordance with the operating mode using the adjusted value for the control parameter in lieu of the initial value and thereafter reverting the control parameter to the initial value.

Abstract: Infusion systems, infusion devices, and related operating methods are provided. A method of operating an infusion device involves determining a reference insulin absorption curve for the patient based at least in part on demographic data associated with the patient, determining a contextual adjustment factor based at least in part on a current patient context, calculating an adjusted insulin absorption curve for the patient as a function of the reference insulin absorption curve and the contextual adjustment factor, and determining a bolus dosage of the insulin based at least in part on the adjusted insulin absorption curve.

Abstract: A computer-implemented system and related method of managing use of a diabetes management device are presented here. An embodiment of the method obtains input data for a user of the diabetes management device, and compares the input data against historical event/outcome combinations maintained for the user. Each of the event/outcome combinations includes insight event data indicative of a glycemic event and a glycemic outcome corresponding to the insight event data. The method determines, based on the comparing, a correlation between the input data and a glycemic outcome. The method continues by generating a glycemic insight message for delivery to the user, wherein the glycemic insight message includes information regarding a relationship between at least some of the input data and the glycemic outcome.

Abstract: A computer-implemented system and related method of reporting glucose information for a user of a diabetes management device are presented here. An embodiment of the method obtains input data for the user of the diabetes management device, and identifies a tracked glycemic response event. One or more recommended glycemic control parameters are calculated based on an analysis of the obtained input data. The glycemic control parameters are calculated to extend a time period during which the user remains within a target glucose range following the tracked glycemic response event. The method continues by generating an output message that includes at least some of the recommended glycemic control parameters, and delivering the generated output message to a user device operated by the user of the diabetes management device.