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Diabetes screening intervals based on risk stratification

Overview of attention for article published in BMC Endocrine Disorders, November 2016
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Title
Diabetes screening intervals based on risk stratification
Published in
BMC Endocrine Disorders, November 2016
DOI 10.1186/s12902-016-0139-1
Pubmed ID
Authors

Sachiko Ohde, Emily McFadden, Gautam A. Deshpande, Hiroshi Yokomichi, Osamu Takahashi, Tsuguya Fukui, Rafael Perera, Zentaro Yamagata

Abstract

Guidelines for frequency of Type 2 diabetes mellitus (DM) screening remain unclear, with proposed screening intervals typically based on expert opinion. This study aims to demonstrate that HbA1c screening intervals may differ substantially when considering individual risk for diabetes. This was a multi-institutional retrospective open cohort study. Data were collected between April 1999 to March 2014 from one urban and one rural cohort in Japan. After categorization by age, we stratified individuals based on cardiovascular disease risk (Framingham 10-year cardiovascular risk score) and body mass index (BMI). We adapted a signal-to-noise method for distinguishing true HbA1c change from measurement error by constructing a linear random effect model to calculate signal and noise of HbA1c. Screening interval for HbA1c was defined as informative when the signal-to-noise ratio exceeded 1. Among 96,456 healthy adults, 46,284 (48.0%) were male; age (range) and mean HbA1c (SD) were 48 (30-74) years old and 5.4 (0.4)%, respectively. As risk increased among those 30-44 years old, HbA1c screening intervals for detecting Type 2 DM consistently decreased: from 10.5 (BMI <18.5) to 2.4 (BMI > 30) years, and from 8.0 (Framingham Risk Score <10%) to 2.0 (Framingham Risk Score ≥20%) years. This trend was consistent in other age and risk groups as well; among obese 30-44 year olds, we found substantially shorter intervals compared to other groups. HbA1c screening intervals for identification of DM vary substantially by risk factors. Risk stratification should be applied when deciding an optimal HbA1c screening interval in the general population to minimize overdiagnosis and overtreatment.

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Mendeley readers

The data shown below were compiled from readership statistics for 46 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 46 100%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 12 26%
Student > Doctoral Student 6 13%
Professor > Associate Professor 5 11%
Student > Postgraduate 3 7%
Researcher 3 7%
Other 10 22%
Unknown 7 15%
Readers by discipline Count As %
Medicine and Dentistry 21 46%
Nursing and Health Professions 8 17%
Social Sciences 2 4%
Agricultural and Biological Sciences 1 2%
Computer Science 1 2%
Other 5 11%
Unknown 8 17%