Anaemia to predict outcome in patients with acute coronary syndromes

SummaryBackgroundOwing to the heterogeneous population of patients with acute coronary syndromes (ACS), risk stratification with tools such as the GRACE risk score is recommended to guide therapeutic management and improve outcome.AimTo evaluate whether anaemia refines the value of the GRACE risk model to predict midterm outcome after an ACS.MethodsA prospective registry of 1064 ACS patients (63±14years; 73% men; 57% ST-segment elevation myocardial infarction [MI]) was studied. Anaemia was defined as haemoglobin less than 13mg/dL in men or less than 12mg/dL in women. The primary endpoint was 6-month death or rehospitalization for MI.ResultsThe primary endpoint was reached in 132 patients, including 68 deaths. Anaemia was associated with adverse clinical outcomes (hazard ratio 3.008, 95% confidence interval 2.137–4.234; P<0.0001) in univariate analysis and remained independently associated with outcome after adjustment for the Global Registry of Acute Coronary Events (GRACE) risk score (hazard ratio 2.870, 95% confidence interval 1.815–4.538; P<0.0001). Anaemia provided additional prognostic information to the GRACE score as demonstrated by a systematic improvement in global model fit and discrimination (c-statistic increasing from 0.633 [0.571;0.696] to 0.697 [0.638;0.755]). Subsequently, adding anaemia to the GRACE score led to reclassification of 595 patients into different risk categories; 16.5% patients at low risk (≤5% risk of death or rehospitalization for MI) were upgraded to intermediate (>5–10%) or high risk (>10%); 79.5% patients at intermediate risk were reclassified as low (55%) or high risk (24%); and 45.5% patients at high risk were downgraded to intermediate risk. Overall, 174 patients were reclassified into a higher risk category (17.3%) and 421 into a lower risk category (41.9%).ConclusionAnaemia provides independent additional prognostic information to the GRACE score. Combining anaemia with the GRACE score refines its predictive value, which often overestimates the risk