Stroke Risk Stratification in Individuals with Atrial Fibrillation: Head to Head Comparison in a Population-Based Study

Meytal Avgil Tsadok Chief Physician Office, Clalit Research Institute, Clalit Health Services, Tel Aviv, Israel Adi Berliner Senderey Chief Physician Office, Clalit Research Institute, Clalit Health Services, Tel Aviv, Israel Orna Reges Chief Physician Office, Clalit Research Institute, Clalit Health Services, Tel Aviv, Israel Morton Leibowitz Chief Physician Office, Clalit Research Institute, Clalit Health Services, Tel Aviv, Israel Ran Balicer Chief Physician Office, Clalit Research Institute, Clalit Health Services, Tel Aviv, Israel Moshe Hoshen Chief Physician Office, Clalit Research Institute, Clalit Health Services, Tel Aviv, Israel Moti Haim Chief Physician Office, Clalit Research Institute, Clalit Health Services, Tel Aviv, Israel Cardiology Department, Soroka Medical Center, Beer Sheva, Israel

Background: Different risk stratification scores have been developed to guide clinicians for stroke prevention strategies in patients with atrial fibrillation (AF)

In this study we estimated the area under the curve (AUC) and the net reclassification improvement (NRI) of CHADS2, CHA2DS2-VASc and R2CHADS2 in a single, large population-based AF cohort.

Methods: This retrospective cohort study is based on the electronic medical records of Clalit Health Services. Data from all Clalit members with first AF diagnosis between 2004 and 2015 were extracted. Demographic data and comorbidities were used to calculate the three risk scores and the performance of the scores to predict stroke outcome was compared using AUC and NRI.

Results: Of the 89,213 Clalit members with AF, 53.3% were ≥75 years and 47.7% were men. The proportions of Clalit members at high risk stratum were 66.2%, 86.7% and 71.1% in the CHADS2, CHA2DS2-VASc and R2CHADS2, respectively, with stroke incidence rate of 2.9, 2.4 and 2.8 per 100 person years. AUCs were 0.61 for CHADS2 and CHA2DS2-VASc and 0.59 in R2CHADS2. NRI analyses demonstrated a net improvement of 8.9% (95%CI: 6.0%, 11.0%) when CHA2DS2-VASc was compared to CHADS2, while there was a net reduction of 8.3% (95%CI: -5.7%, -11.0%) when R2CHADS2 was compared to CHADS2. Results of AUC analysis remained similar in subpopulation of AF patients who did not purchased anticoagulation therapy within the first three months after the index date, but NRI analysis demonstrated improvement of 13.2% (95%CI: 9.8-16.6%) and a net reduction of 12.3% (95%CI: -9.0,-15.7%) when CHA2DS2-VASc and R2CHADS2 were compared to CHADS2, respectively.

Conclusion: Current stroke stratification scores have comparable but limited ability to predict stroke in members with AF. Stroke prevention strategies may vary depending on the applied stratification. There is a need for a better stroke risk stratification score in patients with AF.









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