📇 Rhumatologue · BAYONNE CEDEX · (64) · Salarié
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1 raison identifiée
Délais de RDV courts dans la région
166.7 rhumatos / 100 000 hab. — département bien doté
✨ Génération du profil synthétique IA en cours…
Articles déposés en accès libre sur l'archive ouverte des universités françaises (HAL) — gage d'activité de recherche en France.
Données ANS publiques (Licence Ouverte 2.0) · Enrichissements MonRhumato 100 % opt-in · Toute personne référencée peut demander la suppression ou la rectification.
Source : HAL — archive ouverte CCSD/CNRS (couvre articles, chapitres EMC, communications congrès, thèses).
CH COTE BASQUE
13 AV DE L'INTERNE JACQUES LOEB BP 8, 64109 BAYONNE CEDEX
Secteur de conventionnement non disponible (médecin hospitalier ou non présent dans l'Annuaire santé CNAM des libéraux conventionnés).
Lien Doctolib = recherche Google site:doctolib.fr (le 1er résultat est presque toujours le profil correct s'il existe).
BMC emergency medicine · 2021
Abstract Background Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) can be associated with myocardial injury. Identification of at-risk patients and mechanisms underlying cardiac involvement in COVID-19 remains unclear. During hospitalization for COVID-19, high troponin level has been found to be an independent variable associated with in-hospital mortality and a greater risk of complications. Electrocardiographic (ECG) abnormalities could be a useful tool to identify patients at risk of poor prognostic. The aim of our study was to assess if specific ECGs patterns could be related with in-hospital mortality in COVID-19 patients presenting to the ED in a European country. Methods From February 1st to May 31st, 2020, we conducted a multicenter study in three hospitals in France. We included adult patients (≥ 18 years old) who visited the ED during the study period, with ECG performed at ED admission and diagnosed with COVID-19. Demographic, comorbidities, drug exposures, signs and symptoms presented, and outcome data were extracted from electronic medical records using a standardized data collection form. The relationship between ECG abnormalities and in-hospital mortality was assessed using univariate and multivariable logistic regression analyses. Results An ECG was performed on 275 patients who presented to the ED. Most of the ECGs were in normal sinus rhythm (87%), and 26 (10%) patients had atrial fibrillation/flutter on ECG at ED admission. Repolarization abnormalities represented the most common findings reported in the population (40%), with negative T waves representing 21% of all abnormalities. We found that abnormal axis (adjusted odds ratio: 3.9 [95% CI, 1.1–11.5], p = 0.02), and left bundle branch block (adjusted odds ratio: 7.1 [95% CI, 1.9–25.1], p = 0.002) were significantly associated with in-hospital mortality. Conclusions ECG performed at ED admission may be useful to predict death in COVID-19 patients. Our data suggest that the presence of abnormal axis and left bundle branch block on ECG indicated a higher risk of in-hospital mortality in COVID-19 patients who presented to the ED. We also confirmed that ST segment elevation was rare in COVID-19 patients.
Source PubMed · Recherche par auteur (homonymes possibles, vérifier l'affiliation).
BMC emergency medicine · 2021 · Journal Article
De Carvalho H, Leonard-Pons L, Segard J, Goffinet N, et al.
Electrocardiographic abnormalities in COVID-19 patients visiting the emergency department: a multicenter retrospective study
Abstract Background Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) can be associated with myocardial injury. Identification of at-risk patients and mechanisms underlying cardiac involvement in COVID-19 rema
Electrocardiographic abnormalities in COVID-19 patients visiting the emergency department: a multicenter retrospective study
Abstract Background Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) can be associated with myocardial injury. Identification of at-risk patients and mechanisms underlying cardiac involvement in COVID-19 rema
Source : DataCite — DOIs pour datasets, logiciels, protocoles, registres patient. Hors articles (déjà couverts).