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

12-lead ECG Cryptogenic embolism stroke anticoagulants. echocardiography transthoracic holter ECG paroxysmal atrial fibrillation

Journal

Current neurovascular research
ISSN: 1875-5739
Titre abrégé: Curr Neurovasc Res
Pays: United Arab Emirates
ID NLM: 101208439

Informations de publication

Date de publication:
06 Feb 2024
Historique:
received: 30 12 2023
accepted: 22 01 2024
medline: 7 2 2024
pubmed: 7 2 2024
entrez: 7 2 2024
Statut: aheadofprint

Résumé

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. 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. 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. 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%. 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.

Sections du résumé

BACKGROUND 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 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 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 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 CONCLUSIONS
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.

Identifiants

pubmed: 38321906
pii: CNR-EPUB-138350
doi: 10.2174/0115672026301430240201094411
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Informations de copyright

Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.net.

Auteurs

Sana Ben Amor (S)

Stroke Unit, Neurology Department, Centre Hospitalier Sahloul, Sousse, Tunisia.
Faculty of medicine Ibn El Jazzar, University of Sousse, Sousse, Tunisia.

Assil Achour (A)

Cardiology Department, Centre Hospitalier Sahloul, Sousse, Tunisia.
Faculty of medicine Ibn El Jazzar, University of Sousse, Sousse, Tunisia.

Aymen Elhraiech (A)

Cardiology Department, Centre Hospitalier Sahloul, Sousse, Tunisia.
Faculty of medicine Ibn El Jazzar, University of Sousse, Sousse, Tunisia.

Emna Jarrar (E)

Stroke Unit, Neurology Department, Centre Hospitalier Sahloul, Sousse, Tunisia.
Faculty of medicine Ibn El Jazzar, University of Sousse, Sousse, Tunisia.

Hela Ghali (H)

Department of Prevention and Security of Care, Sahloul University Hospital, Sousse, Tunisia.
Faculty of medicine Ibn El Jazzar, University of Sousse, Sousse, Tunisia.

Ons Ben Ameur (O)

Stroke Unit, Neurology Department, Centre Hospitalier Sahloul, Sousse, Tunisia.
Faculty of medicine Ibn El Jazzar, University of Sousse, Sousse, Tunisia.

Neserine Amara (N)

Stroke Unit, Neurology Department, Centre Hospitalier Sahloul, Sousse, Tunisia.
Faculty of medicine Ibn El Jazzar, University of Sousse, Sousse, Tunisia.

Anis Hassine (A)

Stroke Unit, Neurology Department, Centre Hospitalier Sahloul, Sousse, Tunisia.
Faculty of medicine Ibn El Jazzar, University of Sousse, Sousse, Tunisia.

Houyem Saied (H)

Department of Prevention and Security of Care, Sahloul University Hospital, Sousse, Tunisia.
Faculty of medicine Ibn El Jazzar, University of Sousse, Sousse, Tunisia.

Eleys Neffati (E)

Cardiology Department, Centre Hospitalier Sahloul, Sousse, Tunisia.
Faculty of medicine Ibn El Jazzar, University of Sousse, Sousse, Tunisia.

Didier Smadja (D)

Stroke Unit, Centre Hospitalier Sud-Francilien, Corbeil-Essonnes, France.
Paris-Saclay University, France.
INSERM U-1266, Paris-Cité, France.

Classifications MeSH