Incidence and follow-up of Braunwald subgroups in unstable angina pectoris

Objectives. This study was performed to establish the prognosis of patients with unstable angina within the subgroups of the Braunwald classification. Background. Among many classifications of unstable angina, the Braunwald classification is frequently used. However, the incidence and risk for each subgroup in clinical practice have not been established. Methods. Prospective data for 417 consecutive patients admitted for suspected unstable angina were analyzed. Patients were classified according to Braunwald criteria and followed up for 6 months. Survival, infarct-free survival and infarct-free survival without intervention are reported for each class. Results. After in-hospital observation the final diagnosis was acute myocardial infarction in 26 patients (6%), noncoronary chest pain in 109 (26%) and definite unstable angina in 282 (68%). Recurrence of chest pain was significantly different for the different severity classes (28%, 45% and 64% for classes I [accelerated angina], II [subacute angina at rest] and III [acute angina at rest], respectively) but not for clinical circumstances (49% and 53% for classes B [primary unstable angina]and C [postinfarction unstable angina], respectively). Six-month and infarct-free survival (96% and 88%, respectively) were not significantly different between severity classes but were significantly different (p = 0.01) between classes B (97% and 89%) and C (89% and 80%). Infarct-free survival without intervention was best for class II (72%), intermediate for class I (53%) and worst for class III (35%). In multivariate analysis, elderly age, male gender, hypertension, class C and maximal (intravenous) therapy were independent predictors for death; elderly age and class C for infarct-free survival; and male gender, class III, class C, electrocardiographic changes and maximal therapy were associated with infarct-free survival without intervention. Conclusions. Braunwald classification is an appropriate instrument to predict outcome. Risk stratification by these criteria provides a tool for patient selection in clinical trials and for evaluation of treatment strategies.

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