BACKGROUND: Metabolic syndrome (MS) is associated with late-onset diabetes. However, diagnostic criteria for individual components of MS are based on categorical/arbitrary cut points and, therefore, do not exploit the information yield of each factor. We aimed to generate a diagnostic score for MS (MS-Score), aimed at predicting diabetes by giving appropriate weight to the individual components of MS. METHODS: Of 11,323 patients with prior myocardial infarction and followed up for 3.5 years in the GISSI-Prevenzione study, 3855 subjects with diabetes at baseline or missing information for relevant variables were excluded. A Cox proportional hazards model including age, sex, glycemia, high-density lipoprotein cholesterol, triglycerides, hypertension, and body mass index was fitted to create a diagnostic score. A cutoff point of 28 of the score was the best compromise between sensitivity and specificity for MS diagnosis (MS-Score). The prognostic performance of the MS-Score was compared with that of the diagnostic criteria of MS, as defined by National Cholesterol Education Program Adult Treatment Panel III (MS-ATP). RESULTS: Of 7468 patients, 940 developed diabetes. The risk of getting diabetes significantly and progressively increased in the quintiles of the score reaching > 6-fold higher risk in the last one. The predictive capability of MS-Score was significantly higher than that of the MS-ATP (AUC = 0.650 vs 0.587, sensitivity 67% vs 52%, specificity 63% vs 66%, P = .0002). The MS-Score, but not the MS-ATP, was significantly associated with mortality. CONCLUSION: MS-Score improves the prediction of diabetes development by using the full informative content of individual components for diagnosis of MS.
BACKGROUND:Metabolic syndrome (MS) is associated with late-onset diabetes. However, diagnostic criteria for individual components of MS are based on categorical/arbitrary cut points and, therefore, do not exploit the information yield of each factor. We aimed to generate a diagnostic score for MS (MS-Score), aimed at predicting diabetes by giving appropriate weight to the individual components of MS. METHODS: Of 11,323 patients with prior myocardial infarction and followed up for 3.5 years in the GISSI-Prevenzione study, 3855 subjects with diabetes at baseline or missing information for relevant variables were excluded. A Cox proportional hazards model including age, sex, glycemia, high-density lipoprotein cholesterol, triglycerides, hypertension, and body mass index was fitted to create a diagnostic score. A cutoff point of 28 of the score was the best compromise between sensitivity and specificity for MS diagnosis (MS-Score). The prognostic performance of the MS-Score was compared with that of the diagnostic criteria of MS, as defined by National Cholesterol Education Program Adult Treatment Panel III (MS-ATP). RESULTS: Of 7468 patients, 940 developed diabetes. The risk of getting diabetes significantly and progressively increased in the quintiles of the score reaching > 6-fold higher risk in the last one. The predictive capability of MS-Score was significantly higher than that of the MS-ATP (AUC = 0.650 vs 0.587, sensitivity 67% vs 52%, specificity 63% vs 66%, P = .0002). The MS-Score, but not the MS-ATP, was significantly associated with mortality. CONCLUSION: MS-Score improves the prediction of diabetes development by using the full informative content of individual components for diagnosis of MS.
Authors: X Lin; K Song; N Lim; X Yuan; T Johnson; A Abderrahmani; P Vollenweider; H Stirnadel; S S Sundseth; E Lai; D K Burns; L T Middleton; A D Roses; P M Matthews; G Waeber; L Cardon; D M Waterworth; V Mooser Journal: Diabetologia Date: 2009-01-13 Impact factor: 10.122
Authors: Evan P Pasha; Alex C Birdsill; Stephanie Oleson; Andreana P Haley; Hirofumi Tanaka Journal: Am J Hypertens Date: 2017-12-08 Impact factor: 3.080