Analysis of 109 filial generation of T2DM in predicting diabetes and prediabetes
XING Xinjun;YANG Jinkui
2012, 33(6):
822-826.
doi:10.3969/j.issn.1006-7795.2012.06.024
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Objective Using some data that were easy to access at home, to establish and evaluate a simple tool to identify the type 2 diabetes mellitus(T2DM) and prediabetes(PDM) in the filial generation of T2DM. Methods A total of 109 filial generation of T2DM patients participated in the test. Measuring their blood sugar, age, neck circumference(NC), waist circumference(WC), hip circumference(HC), height, weight. Their waist-hip ratio(WHR) and body mass index(BMI) were calculated. Receiver operating curve(ROC) was used in the analysis and according to the analysis results to establish classification tree. Results For detecting T2DM, the area under receiver operating curve(AUC)of WC was the highest among all of the five risk factors, the AUC=0.770, P=0.000. For detecting T2DM and PDM, AUC of WC was the highest among all of the five risk factors, the AUC=0.770, P=0.000. AUC, sensitivity, specificity, positive predictive value, negative predictive value were 78.4%, 61.1%, 95.6%, 68.8% and 93.5%, respectively for detecting T2DM. AUC, sensitivity, specificity, positive predictive value, negative predictive value were 72.7%, 56.5%, 88.9%, 78.8% and 73.7% respectively for detecting T2DM and PDM. Conclusion WC, which reflects central obesity, has the biggest AUC, can best predict the possibility of suffering T2DM and PDM and is used as the first bifurcation in the classification tree. The classification tree is an easy and feasible tool to detect T2DM and PDM.
