印度糖尿病风险评分（IDRS）和社区为基础评估清单（CBAC）在代谢综合征预测工具中的应用。

Application of Indian Diabetic Risk Score (IDRS) and Community Based Assessment Checklist (CBAC) as Metabolic Syndrome prediction tools.

机构信息

Department of Community Medicine & Family Medicine, All India Institute of Medical Sciences (AIIMS), Jodhpur, Rajasthan, India.

School of Public Health (SPH), All India Institute of Medical Sciences (AIIMS), Jodhpur, Rajasthan, India.

出版信息

PLoS One. 2023 Mar 27;18(3):e0283263. doi: 10.1371/journal.pone.0283263. eCollection 2023.

DOI:10.1371/journal.pone.0283263

PMID:36972242

原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10042346/

Abstract

BACKGROUND

Indian Diabetic Risk Score (IDRS) and Community Based Assessment Checklist (CBAC) are easy, inexpensive, and non-invasive tools that can be used to screen people for Metabolic Syndrome (Met S). The study aimed to explore the prediction abilities of IDRS and CBAC tools for Met S.

METHODS

All the people of age ≥30 years attending the selected rural health centers were screened for Met S. We used the International Diabetes Federation (IDF) criteria to diagnose the Met S. ROC curves were plotted by taking Met S as dependent variables, and IDRS and CBAC scores as independent/prediction variables. Sensitivity (SN), specificity (SP), Positive and Negative Predictive Value (PPV and NPV), Likelihood Ratio for positive and negative tests (LR+ and LR-), Accuracy, and Youden's index were calculated for different IDRS and CBAC scores cut-offs. Data were analyzed using SPSS v.23 and MedCalc v.20.111.

RESULTS

A total of 942 participants underwent the screening process. Out of them, 59 (6.4%, 95% CI: 4.90-8.12) were found to have Met S. Area Under the Curve (AUC) for IDRS in predicting Met S was 0.73 (95%CI: 0.67-0.79), with 76.3% (64.0%-85.3%) sensitivity and 54.6% (51.2%-57.8%) specificity at the cut-off of ≥60. For the CBAC score, AUC was 0.73 (95%CI: 0.66-0.79), with 84.7% (73.5%-91.7%) sensitivity and 48.8% (45.5%-52.1%) specificity at the cut-off of ≥4 (Youden's Index, 2.1). The AUCs of both parameters (IDRS and CBAC scores) were statistically significant. There was no significant difference (p = 0.833) in the AUCs of IDRS and CBAC [Difference between AUC = 0.00571].

CONCLUSION

The current study provides scientific evidence that both IDRS and CBAC have almost 73% prediction ability for Met S. Though CBAC holds relatively greater sensitivity (84.7%) than IDRS (76.3%), the difference in prediction abilities is not statistically significant. The prediction abilities of IDRS and CBAC found in this study are inadequate to qualify as Met S screening tools.

摘要

背景

印度糖尿病风险评分（IDRS）和基于社区的评估检查表（CBAC）是简单、廉价且非侵入性的工具，可用于筛查代谢综合征（MetS）患者。本研究旨在探讨 IDRS 和 CBAC 工具对 MetS 的预测能力。

方法

所有年龄≥30 岁的人在选定的农村卫生中心接受 MetS 筛查。我们使用国际糖尿病联合会（IDF）标准诊断 MetS。以 MetS 为因变量，以 IDRS 和 CBAC 评分为自变量绘制 ROC 曲线。计算不同 IDRS 和 CBAC 评分截断值的灵敏度（SN）、特异性（SP）、阳性和阴性预测值（PPV 和 NPV）、阳性和阴性检验的似然比（LR+ 和 LR-）、准确性和 Youden 指数。使用 SPSS v.23 和 MedCalc v.20.111 进行数据分析。

结果

共有 942 人接受了筛查。其中，59 人（6.4%，95%CI：4.90-8.12）患有 MetS。IDRS 预测 MetS 的曲线下面积（AUC）为 0.73（95%CI：0.67-0.79），截断值≥60 时的灵敏度为 76.3%（64.0%-85.3%），特异性为 54.6%（51.2%-57.8%）。对于 CBAC 评分，AUC 为 0.73（95%CI：0.66-0.79），截断值≥4 时的灵敏度为 84.7%（73.5%-91.7%），特异性为 48.8%（45.5%-52.1%），Youden 指数为 2.1。两个参数（IDRS 和 CBAC 评分）的 AUC 均有统计学意义。IDRS 和 CBAC 的 AUC 之间无显著差异（p=0.833）[AUC 差异=0.00571]。