• Dritan Poçi, Marianne Hartford, Thomas Karlsson, Johan Herlitz, Nils Edvardsson, and Kenneth Caidahl.
• Institute of Medicine, Department of Molecular and Clinical Medicine/Cardiology, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden. dritan.poci@orebroll.se
• Chest. 2012 Jun 1;141(6):1431-40.

BackgroundAtrial fibrillation (AF) is common in patients with acute coronary syndromes (ACS). We aimed to describe the value of the CHADS(2) (congestive heart failure, hypertension, age ≥ 75 years, diabetes, prior stroke or transient ischemic attack) score as a risk assessment tool for mortality and stroke in patients with ACS, irrespective of the presence or absence of AF.MethodsConsecutive patients with ACS admitted to the coronary care unit were prospectively included in a risk stratification study. We calculated the CHADS(2) scores from the data collected at admission, and all patients were followed until January 1, 2007, or death.ResultsOf 2,335 patients with ACS in this study, 442 (age 71 ± 8 years, 142 women) had AF. Their mean CHADS(2) score was 1.6 ± 1.4 vs 1.0 ± 1.1 in patients without AF (P < .0001). The all-cause mortality at 10 years was strongly associated with the CHADS(2) score in patients with AF (hazard ratio [HR] and 95% CI per unit increase in the six-grade CHADS(2) score, 1.21 [1.07-1.36]; P = .002), but the same association was also present in patients without AF (HR 1.38 [1.28-1.48], P < .0001), after adjustment for potential confounders. The more complicated GRACE (Global Registry of Acute Coronary Events) risk score provided a better prediction for short- and long-term mortality than the simpler CHADS(2) score (P < .0001). Hospitalization for stroke was significantly associated with the CHADS(2) score in patients without AF (but not in those with AF) after adjustment (HR 1.46 [1.27-1.68], P < .0001).ConclusionsIn patients with ACS, AF is associated with poor prognosis. The CHADS(2) score developed for AF has even greater prognostic value in patients who do not have AF, and it may help to identify patients with high risk for subsequent stroke or death and a need for optimization of risk-reducing treatment.

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