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A Simplified Risk Score to Predict In-Hospital Newly-Diagnosed Atrial Fibrillation in Acute Ischemic Stroke Patients.
PURPOSE: Atrial fibrillation (AF) is a significant cause of stroke, and newly diagnosed AF (NDAF) is typically detected in the early period of stroke onset. We aimed to identify the factors associated with in-hospital NDAF in acute ischemic stroke patients and developed a simplified clinical prediction model.
METHODS: Patients with cryptogenic stroke aged 18 years or older who were admitted between January 2017 and December 2021 were recruited. NDAF was determined by inpatient cardiac telemetry. Univariable and multivariable regression analyses were used to evaluate the factors associated with in-hospital NDAF. The predictive model was developed using regression coefficients.
RESULTS: The study enrolled 244 eligible participants, of which 52 NDAFs were documented (21.31%), and the median time to detection was two days (1-3.5). After multivariable regression analysis, parameters significantly associated with in-hospital NDAF were elderly (>75 years) (adjusted Odds ratio, 2.99; 95% confident interval, 1.51-5.91; P = 0.002), female sex (2.08; 1.04-4.14; P = 0.04), higher admission national institute of health stroke scale (1.04; 1.00-1.09; P = 0.05), and presence of hyperdense middle cerebral artery sign (2.33; 1.13-4.79; P = 0.02). The area under the receiver operating characteristic curve resulted in 0.74 (95% CI 0.65-0.80), and the cut-point of 2 showed 87% sensitivity and 42% specificity.
CONCLUSION: The validated and simplified risk scores for predicting in-hospital NDAF primarily rely on simplified parameters and high sensitivity. It might be used as a screening tool for in-hospital NDAF in stroke patients who initially presumed cryptogenic stroke.
METHODS: Patients with cryptogenic stroke aged 18 years or older who were admitted between January 2017 and December 2021 were recruited. NDAF was determined by inpatient cardiac telemetry. Univariable and multivariable regression analyses were used to evaluate the factors associated with in-hospital NDAF. The predictive model was developed using regression coefficients.
RESULTS: The study enrolled 244 eligible participants, of which 52 NDAFs were documented (21.31%), and the median time to detection was two days (1-3.5). After multivariable regression analysis, parameters significantly associated with in-hospital NDAF were elderly (>75 years) (adjusted Odds ratio, 2.99; 95% confident interval, 1.51-5.91; P = 0.002), female sex (2.08; 1.04-4.14; P = 0.04), higher admission national institute of health stroke scale (1.04; 1.00-1.09; P = 0.05), and presence of hyperdense middle cerebral artery sign (2.33; 1.13-4.79; P = 0.02). The area under the receiver operating characteristic curve resulted in 0.74 (95% CI 0.65-0.80), and the cut-point of 2 showed 87% sensitivity and 42% specificity.
CONCLUSION: The validated and simplified risk scores for predicting in-hospital NDAF primarily rely on simplified parameters and high sensitivity. It might be used as a screening tool for in-hospital NDAF in stroke patients who initially presumed cryptogenic stroke.
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