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A nomogram model for screening the risk of diabetes in a large-scale Chinese population: an observational study from 345,718 participants.

Abstract：

:Our study is major to establish and validate a simple type||diabetes mellitus (T2DM) screening model for identifying high-risk individuals among Chinese adults. A total of 643,439 subjects who participated in the national health examination had been enrolled in this cross-sectional study. After excluding subjects with missing data or previous medical history, 345,718 adults was included in the final analysis. We used the least absolute shrinkage and selection operator models to optimize feature selection, and used multivariable logistic regression analysis to build a predicting model. The results showed that the major risk factors of T2DM were age, gender, no drinking or drinking/time > 25 g, no exercise, smoking, waist-to-height ratio, heart rate, systolic blood pressure, fatty liver and gallbladder disease. The area under ROC was 0.811 for development group and 0.814 for validation group, and the p values of the two calibration curves were 0.053 and 0.438, the improvement of net reclassification and integrated discrimination are significant in our model. Our results give a clue that the screening models we conducted may be useful for identifying Chinses adults at high risk for diabetes. Further studies are needed to evaluate the utility and feasibility of this model in various settings.

journal_name

Sci Rep

journal_title

Scientific reports

authors

Xue M,Su Y,Feng Z,Wang S,Zhang M,Wang K,Yao H

doi

10.1038/s41598-020-68383-7

subject

Has Abstract

pub_date

2020-07-14 00:00:00

pages

11600

issue

1

issn

2045-2322

pii

10.1038/s41598-020-68383-7

journal_volume

10

pub_type

杂志文章

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