Probability Score to Predict Spontaneous Conversion to Sinus Rhythm in Patients with Symptomatic Atrial Fibrillation When Less Could Be More?

Author:

Mariani Marco Valerio1ORCID,Pierucci Nicola1,Trivigno Sara1ORCID,Cipollone Pietro1,Piro Agostino1ORCID,Chimenti Cristina1,Della Rocca Domenico Giovanni2ORCID,Miraldi Fabio3,Vizza Carmine Dario1ORCID,Lavalle Carlo1

Affiliation:

1. Department of Cardiovascular, Respiratory, Nephrological, Aenesthesiological and Geriatric Sciences, “Sapienza” University of Rome, 00161 Rome, Italy

2. Texas Cardiac Arrhythmia Institute, St. David’s Medical Center, Austin, TX 78705, USA

3. Cardio Thoracic-Vascular and Organ Transplantation Surgery Department, Policlinico Umberto I Hospital, 00161 Rome, Italy

Abstract

Background: The probability of spontaneous conversion (SCV) to sinus rhythm (SR) in patients presenting to the emergency department (ED) with hemodynamically stable, symptomatic atrial fibrillation (AF) is not well known. Objective: To develop and validate a score to determine the probability of SCV to SR in patients presenting to the ED with hemodynamically stable, symptomatic AF. Methods: This retrospective, observational study enrolled consecutive patients admitted with AF to the ED. Variables associated to SCV during a 6 h “wait-and-see” approach were used to develop and validate a score to determine the probability of SCV to SR in AF patients. The study was divided in two phases: (1) score development and (2) validation of the predictive score. Results: Out of 748 eligible patients, 446 patients were included in the derivation cohort, whereas 302 patients were included in the validation cohort. In the derivation cohort, based on multivariable logistic analysis, a probability score weight was developed including: previous SCV (3 points), AF-related symptom duration < 24 h (5 points), age ≥ 65 years (3 points) and female sex (2 points). The score allowed us to divide patients in three groups based on the probability of SCV to SR during the 6 h observation period. The probability prediction model showed an area under the curve (AUC) of 0.707 and 0.701 in the derivation and validation cohorts, respectively. Conclusions: The proposed score allowed us to predict SCV probability with good accuracy and may help physicians in tailoring AF management in an effective and timely manner.

Publisher

MDPI AG

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