13 results about "Basal insulin" patented technology

A diabetes management system adapted to determine adherence for a subject in treatment according to a basal insulin regimen, the system being adapted to receive regimen data. BG data and insulin injection data. If one or more insulin injections have not been received in accordance with the prescribed regimen and thus are missing, the system is adapted to calculate for each missing injection an expected dose response BG value. By comparing received BG data, corresponding to the missing insulin injections, it can be determined for a given confidence interval whether or not the subject has been in adherence with the basal insulin regimen.

An apparatus comprising a user interface configured to generate an electrical signal to start a basal insulin rate test when prompted by a user, an input configured to receive sampled blood glucose data of a patient that is obtained during a specified time duration, including a time duration during delivery of insulin according to a specified basal insulin rate pattern, and a controller communicatively coupled to the input and the user interface. The controller includes an insulin calculation module configured for determining at least one of an amount of basal insulin over-delivered and an amount of basal insulin under-delivered during the basal insulin rate test in trying to meet a target blood glucose baseline. Other devices and methods are disclosed.

A continuous glucose monitor (CGM)-driven basal insulin titration system and method for patients with Type 2 Diabetes can be adapted to the needs and concerns of subjects just starting on basal insulin therapy. The method uses as inputs historical CGM data, basal insulin dose information, reports of hypoglycemia, and past recommendations and generates an adjusted insulin dose along with a report advising whether to continue the titration process, or to stop. The method can generate a new recommendation on a regular basis (e.g., each day) until it determines an adequate, consistent dose size.

Presented is a medicament delivery system including a controller, a wearable medication delivery device, an analyte sensor, and other devices. In an example, a receiver is operable to receive glucose measurement values from the analyte sensor. A number of devices of the medicament delivery system may include a processor operable to execute programming code and to identify anomalous readings among the received glucose measurement values. The identified anomalous reading may, for example, be based on the received glucose measurement values violating a measurement change threshold indicative of abnormal sensor behavior. The processor may be operable to, in response to identifying the anomalous reading, revert a medicament delivery setting to a default safety basal delivery setting and / or generate a notification, an inquiry, and / or an alert for presentation to a user.

A system for titrating a basal insulin dose that includes a glucose monitoring device configured to collect glucose data of a user, processors in communication with the glucose monitoring device, and a memory coupled to the processors. The processors are configured to determine an initial basal insulin dose, receive insulin data and glucose data during a titration period. The validity of each day is assessed, and a titration glucose level is determined for each valid day. The titration glucose level for each day is compared to glucose level thresholds, and a recommended adjustment to the basal insulin dose is determined based on the comparison.

Provided are a method, system, and computer-readable medium for recommending titration measurement for basal insulin dosing and then automatedly causing delivery of the dosing. The recommendation can be personalized to accomplish a weekly recommended dosing according to evaluation for a daily titration glucose level (TGL) determined for received CGM data over the course of a preceding weekly time period. With increased receipt of CGM data, the TGLs can be categorized according to refinement for risk of occurrence of hypoglycemia, and the recommendation may be provided commensurately. In any instance, the recommendation can be automatedly adjusted either upon the CGM data satisfying conditions for hypoglycemia or upon a patient self-reporting hypoglycemia.

The present invention provides a method for treating or preventing type 2 diabetes in patients with low HOMA2-B using tilzepatide as a first-line pharmaceutical treatment for diabetes. A method is also provided for treating patients with long-term type 2 diabetes using tilzepatide and reduction or elimination of basal insulin therapy, such treatment being continued for at least 26 weeks.

Disclosed herein are systems and methods for automated insulin delivery that provide for adaptive closed loop control that can modify the stored basal profile used by the closed loop algorithm to better reflect the user's actual needs. Actual delivery rates calculated by the closed loop algorithm can be compared to the user's stored profile. If the differences between the actual delivery rates and the stored profile are statistically significant, the stored profile can be modified.

The present disclosure relates to a system for closed loop control of glycemia. In one arrangement, the system comprises: an insulin delivery device; a user interface for inputting patient data, the patient data including a basal insulin profile, an insulin-to-carbohydrate ratio, and meal data; and a controller in communication with the user interface and the insulin delivery device and configured to receive glucose data. The controller is further configured to execute: estimating an amount of active insulin in the patient, the active insulin not including the basal insulin profile, determining a meal carbohydrate value from the meal data, estimating a physiological glucose for the patient and a rate of change of physiological glucose based in part on the glucose data, determining an attenuation factor based on the physiological glucose and the rate of change of the physiological glucose, determining a meal bolus based on meal data, the insulin-to-carbohydrate ratio, and the determined attenuation factor, modifying the determined meal bolus based on the estimated amount of active insulin in the patient, and transmitting a request to deliver the modified meal bolus to the insulin delivery device.

A continuous glucose monitor (CGM)-driven basal insulin titration system and method for patients with Type 2 Diabetes can be adapted to the needs and concerns of subjects just starting on basal insulin therapy. The method uses as inputs historical CGM data, basal insulin dose information, reports of hypoglycemia, and past recommendations and generates an adjusted insulin dose along with a report advising whether to continue the titration process, or to stop. The method can generate a new recommendation on a regular basis (e.g., each day) until it determines an adequate, consistent dose size.

A system for titrating a basal insulin dose that includes a glucose monitoring device configured to collect glucose data of a user, processors in communication with the glucose monitoring device, and a memory coupled to the processors. The processors are configured to determine an initial basal insulin dose, receive insulin data and glucose data during a titration period. The validity of each day is assessed, and a titration glucose level is determined for each valid day. The titration glucose level for each day is compared to glucose level thresholds, and a recommended adjustment to the basal insulin dose is determined based on the comparison.

A system for titrating a basal insulin dose that includes a glucose monitoring device configured to collect glucose data of a user, processors in communication with the glucose monitoring device, and a memory coupled to the processors. The processors are configured to determine an initial basal insulin dose, receive insulin data and glucose data during a titration period. The validity of each day is assessed, and a titration glucose level is determined for each valid day. The titration glucose level for each day is compared to glucose level thresholds, and a recommended adjustment to the basal insulin dose is determined based on the comparison.

An ambulatory glucose profile (AGP) intelligent interpretation and insulin adjustment method based on an expert system includes: establishing a knowledge base in an inference mechanism; constructing an interpretation and decision support expert system with a simplified expert system architecture based on the knowledge base; constructing a patient problem analysis tree in three dimensions of hypoglycemia, blood glucose fluctuation, and hyperglycemia of patients; expanding each rule with expert AGP interpretation and empirical data; constructing a basal insulin dosage adjustment rule and a mealtime insulin dosage adjustment rule based on an interval type-2 fuzzy expert system; and adjusting a node of the patient problem analysis tree based on the interpretation and decision support expert system and a group of the patient, and providing a decision suggestion in combination with the basal insulin dosage adjustment rule and the mealtime insulin dosage adjustment rule.