A Simple Score for Predicting Paroxysmal Atrial Fibrillation in Patients with Embolic Stroke of Undetermined Source in a Tunisian Cohort Study.

Abstract

Background: The annualized recurrent stroke rate in patients with Embolic Stroke of Undetermined Source (ESUS) under antiplatelet therapy is around 4.5%. Only a fraction of these patients will develop atrial fibrillation (FA), to which a stroke can be attributed retrospectively. The challenge is to identify patients at risk of occult AF during follow-up.

Objective: This work aims to determine clinical factors and electrocardiographic and ultrasound parameters that can predict occult AF in patients with ESUS and build a simple predictive score applicable worldwide.

Methods: This is a single-center, registry-based retrospective study conducted at the stroke unit of Sahloul University Hospital, Sousse, Tunisia, between January 2016 and December 2020. Consecutive patients meeting ESUS criteria were monitored for a minimum of one year, with a standardized follow-up consisting of outpatient visits, including ECG every three months and a new 24-hour Holter monitoring in case of palpitations. We performed multivariate stepwise regression to identify predictors of new paroxysmal AF among initial clinical, electrocardiographic (ECG and 24-hour Holter monitoring) and echocardiographic parameters. The coefficient of each independent covariate of the fitted multivariable model was used to generate an integerbased point-scoring system.

Results: Three hundred patients met the criteria for ESUS. Among them, 42 (14%) patients showed at least one episode of paroxysmal AF during a median follow-up of two years. In univariate analysis, age, gender, coronary artery disease, history of ischemic stroke, higher NIHSS at admission and lower NIHSS at discharge, abnormal P-wave axis, prolonged P-wave duration, premature atrial contractions (PAC) frequency of more than 500/24 hours, and left atrial (LA) mean area of more than 20 cm² were associated with the risk of occurrence of paroxysmal AF. We proposed an AF predictive score based on (1.771 x NIHSS score at admission) + (10.015 x P-wave dispersion; coded 1 if yes and 0 if no) + (9.841x PAC class; coded 1 if ≥500 and 0 if no) + (9.828x LA class surface; coded 1 if ≥20 and 0 if no) + (0.548xNIHSS score at discharge) + 0.004. A score of ≥33 had a sensitivity of 76% and a specificity of 93%.

Conclusion: In this cohort of patients with ESUS, NIHSS at both admission and discharge, Pwave dispersion, PAC≥500/24h on a 24-hour Holter monitoring, and LA surface area≥20 cm² provide a simple AF predictive score with very reasonable sensitivity and specificity and is applicable almost worldwide. An external validation of this score is ongoing.