A clinically practicable diagnostic score for @entity209 improves its predictivity of XXXX : the Gruppo Italiano per lo Studio della Sopravvivenza nell'Infarto miocardico (GISSI)-Prevenzione scoring.

@entity1 @entity101 @entity6 @entity1674 @entity855 @entity209 @entity583 @entity15 @entity165
BACKGROUND: @entity209 ( @entity15 ) is associated with late-onset @entity6 . However, diagnostic criteria for individual components of @entity15 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 @entity15 ( @entity15 ), aimed at predicting @entity6 by giving appropriate weight to the individual components of @entity15 . METHODS: Of 11,323 @entity1 with prior @entity583 and followed up for 3.5 years in the GISSI-Prevenzione study, 3855 subjects with @entity6 at baseline or missing information for relevant variables were excluded. A Cox proportional hazards model including age, sex, glycemia, high-density lipoprotein @entity165 , @entity1674 , @entity101 , 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 @entity15 diagnosis ( @entity15 ). The prognostic performance of the @entity15 was compared with that of the diagnostic criteria of @entity15 , as defined by National @entity165 Education Program Adult Treatment Panel III ( @entity15 - @entity855 ). RESULTS: Of 7468 @entity1 , 940 developed @entity6 . The risk of getting @entity6 significantly and progressively increased in the quintiles of the score reaching > 6-fold higher risk in the last one. The predictive capability of @entity15 was significantly higher than that of the @entity15 - @entity855 (AUC = 0.650 vs 0.587, sensitivity 67% vs 52%, specificity 63% vs 66%, P = .0002). The @entity15 , but not the @entity15 - @entity855 , was significantly associated with mortality. CONCLUSION: @entity15 improves the prediction of @entity6 development by using the full informative content of individual components for diagnosis of @entity15 .
