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三组分无创性中国人群未诊断糖尿病风险评分:研发、验证与纵向评估。

Three-component non-invasive risk score for undiagnosed diabetes in Chinese people: Development, validation and longitudinal evaluation.

机构信息

Department of Medicine, Queen Mary Hospital, The University of Hong Kong, Hong Kong, Hong Kong SAR.

Department of Endocrinology, Xijing Hospital, Air Force Medical University, Xi'an, China.

出版信息

J Diabetes Investig. 2020 Mar;11(2):341-348. doi: 10.1111/jdi.13144. Epub 2019 Oct 1.

DOI:10.1111/jdi.13144
PMID:31495069
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7078083/
Abstract

AIMS/INTRODUCTION: To develop a new non-invasive risk score for undiagnosed diabetes in Chinese people, and to evaluate the incident diabetes risk in those with high-risk scores, but no diabetes on initial testing.

MATERIALS AND METHODS

A total of 2,609 participants with no known diabetes (aged 25-74 years) who underwent oral glucose tolerance tests in Hong Kong (HK) were investigated for independent risk factors of diabetes to develop a categorization point scoring system, the Non-invasive Diabetes Score (NDS). This NDS was validated in a cross-sectional study of 2,746 participants in Shaanxi, China. HK participants tested to not have diabetes at baseline were assessed for subsequent incident diabetes rates.

RESULTS

In the HK cohort, hypertension, age and body mass index were the key independent risk factors selected to develop the NDS, with ≥28 out of 50 NDS points considered as high risk. The area under the receiver operating characteristic curve for undiagnosed diabetes was 0.818 and 0.720 for the HK and Shaanxi cohort, respectively. The negative predictive value was 97.4% (HK) and 95.8% (Shaanxi); the number needed to screen to identify one case of diabetes was five (HK) and 11 (Shaanxi), respectively. Among those that tested non-diabetes at baseline, individuals with NDS ≥28 had a threefold risk of incident diabetes during the subsequent 20.9 years, compared with those with NDS <28 (P < 0.001), with a steeper rise in incident diabetes observed in those with NDS at higher tertiles.

CONCLUSIONS

This new three-component risk score is a user-friendly tool for diabetes screening, and might inform the subsequent testing interval for high-risk non-diabetes individuals.

摘要

目的/引言:旨在为中国人开发一种新的非侵入性糖尿病风险评分,评估初始检测无糖尿病但高风险评分者的糖尿病发病风险。

材料与方法

共纳入 2609 名无已知糖尿病(年龄 25-74 岁)的香港参与者进行口服葡萄糖耐量试验,调查糖尿病的独立危险因素以开发分类点评分系统,即无创糖尿病评分(NDS)。该 NDS 在 2746 名中国陕西的横断面研究中进行了验证。对香港基线时未检出糖尿病的参与者进行评估,以确定后续糖尿病发病率。

结果

在香港队列中,高血压、年龄和体重指数是选择来开发 NDS 的关键独立危险因素,NDS 评分≥28 分被认为是高风险。未诊断糖尿病的 NDS 曲线下面积为 0.818 和 0.720,分别为香港和陕西队列。阴性预测值为 97.4%(香港)和 95.8%(陕西);需要筛查的人数以识别一例糖尿病的人数为 5(香港)和 11(陕西)。在基线时检测为非糖尿病的个体中,NDS≥28 的个体在随后的 20.9 年中发生糖尿病的风险增加了三倍,与 NDS<28 的个体相比(P<0.001),NDS 较高的个体中观察到糖尿病发病率的上升更为陡峭。

结论

这种新的三因素风险评分是一种用于糖尿病筛查的用户友好工具,可能为高风险非糖尿病个体的后续检测间隔提供信息。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ef16/7078083/c959f953a8e4/JDI-11-341-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ef16/7078083/c959f953a8e4/JDI-11-341-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ef16/7078083/c959f953a8e4/JDI-11-341-g001.jpg

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2
Cardiovascular, respiratory, and related disorders: key messages from Disease Control Priorities, 3rd edition.心血管、呼吸及相关疾病:《疾病控制优先领域》第三版要点。
Lancet. 2018 Mar 24;391(10126):1224-1236. doi: 10.1016/S0140-6736(17)32471-6. Epub 2017 Nov 3.
3
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