Abstract

Background: The CHA2DS2-VASc score is an established clinical prediction tool for assessing stroke risk in patients with atrial fibrillation. However, its potential utility in predicting outcomes following primary percutaneous coronary intervention (PCI) in ST-segment elevation myocardial infarction (STEMI) has not been extensively explored. The no-reflow phenomenon and in-hospital mortality are critical endpoints in the management of STEMI patients undergoing PCI. Objective: This study aimed to evaluate the independent predictive value of the CHA2DS2-VASc score for suboptimal reperfusion and short-term mortality in patients with acute STEMI undergoing primary PCI. Methods: In a prospective cohort study involving 116 patients with confirmed STEMI at the National Institute of Cardiovascular Diseases in Karachi, participants were categorized based on their CHA2DS2-VASc score into low (<3) and high (≥3) risk groups. Primary PCI was performed following standard treatment protocols, and variables such as initial TIMI flow, thrombus grade, and lesion complexity were documented. Statistical analysis, including multivariate regression, was conducted using SPSS Version 25. Results: Patients with a high CHA2DS2-VASc score (≥3) exhibited a significantly increased risk of no-reflow (p-value range 0.00-0.03) and in-hospital mortality (11.1%) compared to those with a low score (<3; 1.3% mortality). Other significant findings included an association between high CHA2DS2-VASc scores and larger stent lengths (28.75±5.67 mm), smaller stent diameters (2.69±0.6 mm), higher creatinine levels (1.00±0.202 mg/dL), and increased incidence of diabetes mellitus (36.1%). The odds ratio for mortality associated with a high CHA2DS2-VASc score was 1.58 (95% CI: 1.14–2.13, p-value < 0.00). Conclusion: The CHA2DS2-VASc score is a significant independent predictor of both no-reflow post-PCI and short-term in-hospital mortality in STEMI patients. These findings suggest the score's potential role in the pre-PCI risk stratification, which could guide clinical decision-making and potentially improve patient outcomes.

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