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: A technique for treating diabetes that recognizes patient insulin sensitivity is a time-varying physiological parameter. The described techniques for treating diabetes include measuring interstitial fluid glucose concentration, reading insulin delivery data, determining patient insulin sensitivity based on the interstitial fluid glucose concentration and insulin delivery data, and a time-varying physiological parameter, and dispensing an insulin dose from an insulin delivery device based on the determined patient insulin sensitivity.

Abstract: A system for monitoring a patient, wherein the system 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 the 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 optimized insulin dose.

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: Techniques for providing therapy recommendations are provided. In some embodiments, the techniques may involve receiving an input query pertaining to a prospective therapy modification for a patient, wherein the prospective therapy modification comprises a modification to a therapy regimen including therapy delivered using a medical device and wherein the input query comprises conversational input. The techniques may further involve determining, based on the input query and information on a current operational context of the medical device, a therapy recommendation that, when incorporated into the therapy regimen, is most likely to yield a better outcome with respect to the physiological condition of the patient, wherein the therapy recommendation comprises a recommendation regarding the therapy delivered using the medical device.

Abstract: Techniques for glucose level management are disclosed. In some examples, the techniques may involve obtaining a macronutrient content associated with a meal, wherein the macronutrient content includes a first macronutrient and a second macronutrient. The techniques may further involve predicting, using a patient-specific physiological simulator that utilizes the macronutrient content, glucose amounts to be absorbed into a bloodstream of a patient as a result of consumption of the meal, wherein the patient-specific physiological simulator is configured to account for a difference in glucose level rise due to consumption of the first macronutrient compared to consumption of the second macronutrient. The techniques may further involve determining, using the patient-specific physiological simulator, a dosage of insulin to deliver to the patient based on the glucose amounts to be absorbed into the bloodstream.

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: Techniques for glucose level management are disclosed. In some examples, the techniques may involve obtaining an estimated value of a first nutrient for a meal and an estimated value of a second nutrient for the meal. The techniques may further involve obtaining a patient-specific conversion factor that predicts a glucose level rise for a patient due to consumption of the first nutrient. The techniques may further involve converting the estimated value of the first nutrient into a corresponding value associated with the second nutrient using the patient-specific conversion factor to generate a conversion of the first nutrient. The techniques may further involve determining an equivalent value associated with the second nutrient for the meal based on the estimated value of the second nutrient and the conversion of the first nutrient.

Abstract: Techniques for detection of occurrence of a meal are provided. 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. The techniques may further involve detecting an occurrence of a meal during the analysis interval based on the plurality of glucose measurements obtained during the analysis interval. The techniques may further involve updating a user interface to include an indication of the meal detected during the analysis interval.

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 detection of occurrence of a meal are provided. 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. The techniques may involve determining one or more glucose measurement statistics based on the plurality of glucose measurements. The techniques may involve determining a likelihood of the patient having consumed a meal during the analysis interval based on the one or more glucose measurement statistics that are correlative to an occurrence of a meal for the patient. The techniques may involve detecting an occurrence of the meal during the analysis interval based on the likelihood of the patient having consumed the meal during the analysis interval.

Abstract: Techniques for adjustment of control parameters are provided. In some embodiments, the techniques may involve causing fluid delivery to a patient based on a first value for a control parameter. The techniques may further involve determining an anomalous physiological condition of the patient. The techniques may further involve in response to determining the anomalous physiological condition, causing fluid delivery to the patient based on a second value for the control parameter.

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: Techniques for contextual adjustment of insulin adjustment curves are provided. In some embodiments, the techniques may involve identifying a reference insulin absorption parameter for a patient based on demographic information. The techniques may further involve determining an adjusted insulin absorption parameter based on the reference insulin absorption parameter and context of the patient. The techniques may further involve delivering insulin to the patient based on the adjusted insulin absorption parameter.

Abstract: Techniques for detection of occurrence of a meal are provided. 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. The techniques may involve determining one or more glucose measurement statistics based on the plurality of glucose measurements. The techniques may involve determining a likelihood of the patient having consumed a meal during the analysis interval based on the one or more glucose measurement statistics that are correlative to an occurrence of a meal for the patient. The techniques may involve detecting an occurrence of the meal during the analysis interval based on the likelihood of the patient having consumed the meal during the analysis interval.

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: 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: Disclosed herein are techniques related to glucose level management without carbohydrate counting. The techniques may involve obtaining contextual information for food intake, predicting impact of carbohydrates on a patient's glucose included in the food intake during a duration of time based at least in part on the contextual information for the food intake, determining one or more amounts of insulin to counteract the predicted impact on the patient's 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.