A PHP Error was encountered

Severity: Warning

Message: file_get_contents(https://...@pubfacts.com&api_key=b8daa3ad693db53b1410957c26c9a51b4908&a=1): Failed to open stream: HTTP request failed! HTTP/1.1 429 Too Many Requests

Filename: helpers/my_audit_helper.php

Line Number: 176

Backtrace:

File: /var/www/html/application/helpers/my_audit_helper.php
Line: 176
Function: file_get_contents

File: /var/www/html/application/helpers/my_audit_helper.php
Line: 250
Function: simplexml_load_file_from_url

File: /var/www/html/application/helpers/my_audit_helper.php
Line: 1034
Function: getPubMedXML

File: /var/www/html/application/helpers/my_audit_helper.php
Line: 3152
Function: GetPubMedArticleOutput_2016

File: /var/www/html/application/controllers/Detail.php
Line: 575
Function: pubMedSearch_Global

File: /var/www/html/application/controllers/Detail.php
Line: 489
Function: pubMedGetRelatedKeyword

File: /var/www/html/index.php
Line: 316
Function: require_once

CGMap: Characterizing continuous glucose monitor data in thousands of non-diabetic individuals. | LitMetric

CGMap: Characterizing continuous glucose monitor data in thousands of non-diabetic individuals.

Cell Metab

Department of Computer Science and Applied Mathematics, Weizmann Institute of Science, Rehovot, Israel; Department of Molecular Cell Biology, Weizmann Institute of Science, Rehovot, Israel; Pheno.AI, Tel-Aviv, Israel. Electronic address:

Published: May 2023

AI Article Synopsis

  • - The study discusses the limitations of current diabetes diagnosis methods, which still rely heavily on blood tests, despite the growing use of continuous glucose monitoring (CGM) devices that could provide better insights into glucose control.
  • - Researchers have characterized CGM data from over 7,000 non-diabetic individuals aged 40-70, offering reference values for important CGM-derived clinical measures to support future research in this area.
  • - The findings reveal significant connections between CGM-derived measures and diabetes-related health indicators, such as links between mean blood glucose levels and results from fundus imaging and sleep monitoring, paving the way for more comprehensive health studies.

Article Abstract

Despite its rising prevalence, diabetes diagnosis still relies on measures from blood tests. Technological advances in continuous glucose monitoring (CGM) devices introduce a potential tool to expand our understanding of glucose control and variability in people with and without diabetes. Yet CGM data have not been characterized in large-scale healthy cohorts, creating a lack of reference for CGM data research. Here we present CGMap, a characterization of CGM data collected from over 7,000 non-diabetic individuals, aged 40-70 years, between 2019 and 2022. We provide reference values of key CGM-derived clinical measures that can serve as a tool for future CGM research. We further explored the relationship between CGM-derived measures and diabetes-related clinical parameters, uncovering several significant relationships, including associations of mean blood glucose with measures from fundus imaging and sleep monitoring. These findings offer novel research directions for understanding the influence of glucose levels on various aspects of human health.

Download full-text PDF

Source
http://dx.doi.org/10.1016/j.cmet.2023.04.002DOI Listing

Publication Analysis

Top Keywords

cgm data
12
continuous glucose
8
non-diabetic individuals
8
glucose
5
cgm
5
cgmap characterizing
4
characterizing continuous
4
glucose monitor
4
data
4
monitor data
4

Similar Publications

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!