Amb motiu del tancament d'estiu, la validació de documents es reprendrà a partir del 28 d'agost de 2026. Disculpeu les molèsties.
Con motivo del cierre de verano, la validación de documentos se reanudará a partir del 28 de agosto de 2026. Disculpad las molestias
Due to the summer closure, document validation will resume starting August 28, 2026. We apologize for any inconvenience.

Document type

Article

Version

Accepted version

Publication date

All rights reserved

Please use this identifier to cite or link to this item: https://hdl.handle.net/2445/126452

Chronotropic incompetence predicts mortality in severe obstructive pulmonary disease

Journal Title

Director/Tutor

Journal ISSN

Volume Title

Abstract

We evaluated the prevalence of chronotropic incompetence (CI), a marker of autonomic dysfunction, and its prognostic value in patients with chronic obstructive pulmonary disease (COPD). We performed a retrospective analysis of 449 patients with severe COPD who underwent a cardiopulmonary exercise test, after excluding patients with lung volume reduction surgery, left ventricular dysfunction and those not in sinus rhythm. CI was defined as percent predicted heart rate reserve (%HRR). Events were defined as death or lung transplant during a median follow-up of 68 months. Median age was 61 years; median percent predicted forced expiratory volume in one second (%FEV1) of 25% and median %HRR of 33%. The hazard ratio for an event in the lowest quartile of %HRR, taking the highest quartile as reference, was of 3.2 (95% confidence interval: 2.1-4.8; p < 0.001). In a multivariate regression model, %HRR was an independent predictor of events. In conclusion, Cl was an independent and powerful outcome predictor in patients with severe COPD. (C) 2013 Elsevier B.V. All rights reserved.

Citation

Citation

GONZÁLEZ-COSTELLO, José, et al. Chronotropic incompetence predicts mortality in severe obstructive pulmonary disease. Respiratory Physiology & Neurobiology. 2013. Vol. 188, num. 2, pags. 113-118. [consulted: 16 of August of 2026]. Available at: https://hdl.handle.net/2445/126452

Export metadata

JSON - METS

Share record