葡萄牙 2 型糖尿病及空腹血糖受损风险评分的建立与验证。

The development and validation of the Portuguese risk score for detecting type 2 diabetes and impaired fasting glucose.

机构信息

University of Leicester, Department of Health Sciences, Leicester, UK.

出版信息

Prim Care Diabetes. 2013 Apr;7(1):11-8. doi: 10.1016/j.pcd.2013.01.003. Epub 2013 Jan 26.

DOI:10.1016/j.pcd.2013.01.003

PMID:23357741

Abstract

AIMS

To develop and validate a non-invasive score for detecting undiagnosed impaired fasting glucose (IFG) and type 2 diabetes (T2DM) in a Portuguese population.

METHODS

We used data from 3,374 individuals aged 18-94 years from a Portuguese cross-sectional study. We developed a logistic regression model for predicting IFG/T2DM (diagnosed using fasting glucose). We externally validated the score using data from two cohorts of the EPI-Porto study, cross-sectional (n = 2,131) and data from the 5 year follow-up (n = 1,304).

RESULTS

The final model included age, sex, BMI and hypertension with an area under the ROC curve of 70.1 (95%CI 68.4, 71.7). Using a cut-point which classifies 50% of the EPI-Porto cross-sectional data as high-risk gave sensitivity 73.2% (95%CI 68.5%, 77.6%), specificity 55.5% (53.1%, 57.8%), positive predictive value (PPV) 27.0% (24.3%, 29.8%) and negative predictive value (NPV) 90.2% (88.3%, 92.0%) for IFG/T2DM. Using the same cut-point on the prospective data classified 45% as high-risk; sensitivity 69.1% (63.4%, 74.4%), specificity 63.3% (60.0%, 66.5%), PPV 38.0% (33.9%, 42.4%), and NPV 86.2% (83.3%, 88.8%).

CONCLUSION

The Portuguese risk score can be used to identify those at high risk of both prevalent undiagnosed and incident IFG/T2DM.

摘要

目的

开发并验证一种非侵入性评分系统，用于检测葡萄牙人群中未诊断的空腹血糖受损（IFG）和 2 型糖尿病（T2DM）。

方法

我们使用了来自葡萄牙一项横断面研究的 3374 名 18-94 岁个体的数据。我们建立了一个预测 IFG/T2DM（根据空腹血糖诊断）的逻辑回归模型。我们使用 EPI-Porto 研究的两个队列的数据（横断面研究，n=2131；5 年随访研究，n=1304）对该评分进行了外部验证。

结果

最终模型纳入了年龄、性别、BMI 和高血压，ROC 曲线下面积为 70.1（95%CI 68.4，71.7）。使用将 EPI-Porto 横断面数据的 50%分类为高危的切点，其敏感性为 73.2%（95%CI 68.5%，77.6%），特异性为 55.5%（53.1%，57.8%），阳性预测值（PPV）为 27.0%（24.3%，29.8%），阴性预测值（NPV）为 90.2%（88.3%，92.0%）。在前瞻性数据中使用相同的切点，将 45%分类为高危；敏感性为 69.1%（63.4%，74.4%），特异性为 63.3%（60.0%，66.5%），PPV 为 38.0%（33.9%，42.4%），NPV 为 86.2%（83.3%，88.8%）。