公开(公告)号：US20220369961A1

公开(公告)日：2022-11-24

申请号：US17663657

申请日：2022-05-16

Applicant: Medtronic, Inc.

Inventor： Kamal Deep Mothilal ,  Michael D. Eggen ,  Ning Yu ,  John P. Keane ,  Shantanu Sarkar ,  Randal C. Schulhauser ,  David L. Probst ,  Mark R. Boone ,  Kenneth A. Timmerman ,  Stanley J. Taraszewski ,  Matthew A. Joyce ,  Amruta Paritosh Dixit ,  Kathryn E. Hilpisch ,  Kathryn Ann Milbrandt ,  Laura M. Zimmerman ,  Matthew L. Plante

IPC: A61B5/145 ,  A61B5/0205 ,  A61B5/00 ,  G16H50/20 ,  G16H50/30

Abstract: This disclosure is directed to systems and techniques for detecting change in patient health based upon patient data. In one example, a medical system comprising processing circuitry communicably coupled to a glucose sensor and configured to generate continuous glucose sensor measurements of a patient. The processing circuitry is further configured to: extract at least one feature from the continuous glucose sensor measurements over at least one time period, wherein the at least one feature comprises one or more of an amount of time within a pre-determined glucose level range, a number of hypoglycemia events, a number of hyperglycemia events, or one or more statistical metrics corresponding to the continuous glucose sensor measurements; apply a machine learning model to the at least one extracted feature to produce data indicative of a risk of a cardiovascular event; and generate output data based on the risk of the cardiovascular event.