Gianfranco Piccirillo1, Federica Moscucci2, Marco Valerio Mariani1, Claudia Di Iorio1, Marcella Fabietti1, Fabiola Mastropietri1, Davide Crapanzano1, Gaetano Bertani1, Teresa Sabatino1, Giulia Zaccagnini1, Ilaria Lospinuso1, Pietro Rossi3, Damiano Magrì4. 1. Dipartimento di Scienze Cliniche, Internistiche, Anestesiologiche e Cardiovascolari, Policlinico Umberto I, "La Sapienza" University of Rome, Viale del Policlinico N. 155, 00185 Roma, Italy. 2. Dipartimento di Scienze Cliniche, Internistiche, Anestesiologiche e Cardiovascolari, Policlinico Umberto I, "La Sapienza" University of Rome, Viale del Policlinico N. 155, 00185 Roma, Italy. Electronic address: federica.moscucci@uniroma1.it. 3. Division of Cardiology, S. Giovanni Calibita Fatebenefratelli Hospital, Isola Tiberina, Piazza Ponte dei Quattro Capi, 39 186 Roma, Italy. 4. Dipartimento di Medicina Clinica e Molecolare, S. Andrea Hospital, "Sapienza" University of Rome, Via di Grottarossa 1035/1039, k00189 Rome, Italy.
Abstract
BACKGROUND/AIM: Heart failure is a leading cause of morbidity and mortality worldwide and it is a major cause of emergency department access for cardiovascular disease patients. Aim of this study was to identify the electrocardiographic (ECG) markers, based on short-term temporal repolarization dispersion, capable to individuate decompensated chronic heart failure (CHF) patients at high mortality risk. METHODS: We obtained the following variables from an ECG recording, monitored via mobile phone, during 5-minute recordings in decompensated CHF patients: RR, QT end (QTe), QT peak (QTp) and T peak to T end (Te) and we calculated mean, standard deviation (SD) and normalized index (N). RESULTS: In-hospital mortality occurred for 25 subjects on 101 studied (25%). Deceased patients showed higher QTeSD (p < 0.01), Te mean (p < 0.01), TeSD (p < 0.05), QTeVN (p < 0.05) than the surviving group. Logistic multivariable analysis evidenced that Te mean was a significant predictor of in-hospital mortality (odd ratio: 0.09, 95% confidence limit: 0.02-0.35, p: 0.001). At multiple regression analysis, TeSD was significantly and positively related only to the NT-pro BNP levels (r: 0.540; p < 0.001). The Te mean (AUC: 0.677 p < 0.01) and TeSD (AUC: 0.647, p: 0.05) showed significant sensitivity/specificity for the event. CONCLUSIONS: The Te mean and TeSD seem to be a promising noninvasive clinical marker able to identify patients with decompensated CHF at high risk of in-hospital mortality.
BACKGROUND/AIM: Heart failure is a leading cause of morbidity and mortality worldwide and it is a major cause of emergency department access for cardiovascular diseasepatients. Aim of this study was to identify the electrocardiographic (ECG) markers, based on short-term temporal repolarization dispersion, capable to individuate decompensated chronic heart failure (CHF) patients at high mortality risk. METHODS: We obtained the following variables from an ECG recording, monitored via mobile phone, during 5-minute recordings in decompensated CHF patients: RR, QT end (QTe), QT peak (QTp) and T peak to T end (Te) and we calculated mean, standard deviation (SD) and normalized index (N). RESULTS: In-hospital mortality occurred for 25 subjects on 101 studied (25%). Deceased patients showed higher QTeSD (p < 0.01), Te mean (p < 0.01), TeSD (p < 0.05), QTeVN (p < 0.05) than the surviving group. Logistic multivariable analysis evidenced that Te mean was a significant predictor of in-hospital mortality (odd ratio: 0.09, 95% confidence limit: 0.02-0.35, p: 0.001). At multiple regression analysis, TeSD was significantly and positively related only to the NT-pro BNP levels (r: 0.540; p < 0.001). The Te mean (AUC: 0.677 p < 0.01) and TeSD (AUC: 0.647, p: 0.05) showed significant sensitivity/specificity for the event. CONCLUSIONS: The Te mean and TeSD seem to be a promising noninvasive clinical marker able to identify patients with decompensated CHF at high risk of in-hospital mortality.
Authors: Esther Pueyo; Juan Pablo Martínez; Saúl Palacios; Iwona Cygankiewicz; Antoni Bayés de Luna Journal: Sci Rep Date: 2021-10-15 Impact factor: 4.379