Maurizio Acampa1, Pietro Enea Lazzerini2, Francesca Guideri3, Rossana Tassi3, Ilenia Andreini3, Carlo Domenichelli3, Alessandra Cartocci4, Giuseppe Martini3. 1. Stroke Unit, Department of Neurological and Neurosensorial Sciences, Azienda Ospedaliera Universitaria Senese, "Santa Maria alle Scotte" General Hospital, Siena, Italy. Electronic address: m.acampa@ao-siena.toscana.it. 2. Department of Medical Sciences, Surgery and Neurosciences, University of Siena, Siena, Italy. 3. Stroke Unit, Department of Neurological and Neurosensorial Sciences, Azienda Ospedaliera Universitaria Senese, "Santa Maria alle Scotte" General Hospital, Siena, Italy. 4. Department of Economics and Statistics, University of Siena, Siena, Italy.
Abstract
BACKGROUND: Prolonged screening for the presence of atrial fibrillation (AF) is recommended after cryptogenic stroke (CS) and different electrocardiographic markers of atrial cardiopathy have been proposed as tools to identify patients at high-risk for AF. AIM: The aim of this study was to evaluate the relationship between different electrocardiographic parameters and in-hospital AF occurrence after acute CS. METHOD: In total, 222 patients with CS underwent 12-lead resting electrocardiogram (ECG) at admission and 7-day in-hospital ECG monitoring in order to evaluate the possible occurrence of silent AF. At admission, the following indices were evaluated: maximum and minimum P-wave duration (P max and P min), P-wave dispersion (PWD), P-wave index, P-wave axis, atrial size. Patients were dichotomised into two groups according to the detection of AF during 7-day in-hospital ECG monitoring and a logistic regression model was constructed to determine the predictors of AF. RESULTS: Atrial fibrillation was detected in 44 patients. Those in the AF group had a significantly higher PWD, P-wave index, PR interval, and greater frequency of abnormal P-wave axis than those in the no AF group. The following variables were found to be the main predictors for AF: age (odds ratio [OR] 1.41 for 5 years, 95% confidence interval [CI] 1.15-1.72), PWD (OR 1.92 for 10ms, 95% CI 1.45-2.55), abnormal P-wave axis (OR 3.31, 95% CI 1.49-7.35). CONCLUSIONS: In CS, high PWD and abnormal P-wave axis are independent predictors of AF, representing useful tools to identify patients at high-risk of AF.
BACKGROUND: Prolonged screening for the presence of atrial fibrillation (AF) is recommended after cryptogenic stroke (CS) and different electrocardiographic markers of atrial cardiopathy have been proposed as tools to identify patients at high-risk for AF. AIM: The aim of this study was to evaluate the relationship between different electrocardiographic parameters and in-hospital AF occurrence after acute CS. METHOD: In total, 222 patients with CS underwent 12-lead resting electrocardiogram (ECG) at admission and 7-day in-hospital ECG monitoring in order to evaluate the possible occurrence of silent AF. At admission, the following indices were evaluated: maximum and minimum P-wave duration (P max and P min), P-wave dispersion (PWD), P-wave index, P-wave axis, atrial size. Patients were dichotomised into two groups according to the detection of AF during 7-day in-hospital ECG monitoring and a logistic regression model was constructed to determine the predictors of AF. RESULTS:Atrial fibrillation was detected in 44 patients. Those in the AF group had a significantly higher PWD, P-wave index, PR interval, and greater frequency of abnormal P-wave axis than those in the no AF group. The following variables were found to be the main predictors for AF: age (odds ratio [OR] 1.41 for 5 years, 95% confidence interval [CI] 1.15-1.72), PWD (OR 1.92 for 10ms, 95% CI 1.45-2.55), abnormal P-wave axis (OR 3.31, 95% CI 1.49-7.35). CONCLUSIONS: In CS, high PWD and abnormal P-wave axis are independent predictors of AF, representing useful tools to identify patients at high-risk of AF.
Authors: Marta Rubiera; Ana Aires; Kateryna Antonenko; Sabrina Lémeret; Christian H Nolte; Jukka Putaala; Renate B Schnabel; Anil M Tuladhar; David J Werring; Dena Zeraatkar; Maurizio Paciaroni Journal: Eur Stroke J Date: 2022-06-03
Authors: Jan-Thorben Sieweke; Jan Hagemus; Saskia Biber; Dominik Berliner; Gerrit M Grosse; Sven Schallhorn; Tobias Jonathan Pfeffer; Anselm A Derda; Jonas Neuser; Johann Bauersachs; Udo Bavendiek Journal: Front Cardiovasc Med Date: 2022-03-08
Authors: Maurizio Acampa; Alessandra Cartocci; Carlo Domenichelli; Rossana Tassi; Francesca Guideri; Pietro Enea Lazzerini; Giuseppe Martini Journal: Front Cardiovasc Med Date: 2022-06-20
Authors: Fabienne Kreimer; Assem Aweimer; Andreas Pflaumbaum; Andreas Mügge; Michael Gotzmann Journal: Ann Noninvasive Electrocardiol Date: 2021-05-07 Impact factor: 1.468