Rationale and design of RECOVER – a prospective, longitudinal cardiac rehabilitation registry
Year: 2026
Type: article
Study design: Study Protocol
Abstract: Background: Cardiac rehabilitation (CR) has been performed in a structured manner since the 1970s, supported by a substantial body of evidence demonstrating its benefits across the heterogeneous pool of cardiac patients. Although therapeutic interventions, pharmacological options, and patient-centered recommendations keep emerging, the majority of CR programs have not changed accordingly. Hence, they are becoming less capable of accounting for an increasingly diverse patient cohort. With a prospective long-term cohort, we aim to achieve an in-depth characterization of CR patients, enabling the delivery of more personalized care in the contemporary era. Methods: In this non-interventional, monocentric, prospective cohort study named RECOVER (Cardiac REhabilitation COhort at the Medicine Campus DaVos to invEstigate Recovery), we plan to include 10,000 patients over 10 years across a broad spectrum of cardiovascular conditions (e.g., cardiac surgery, myocardial infarction, heart failure) with data collected across the full spectrum of inpatient CR. Data acquisition is complemented through extensive biobanking allowing detailed phenotyping and biomarker profiling of patients. Follow-up assessments are conducted at 3 and 6 months, and yearly thereafter, up to 10 years. By harnessing novel devices, digital monitoring is employed to continuously capture a wealth of health-related parameters, such as blood pressure and accelerometry-based physical activity. Addition to the field and limitations: Given the substantial research gap in personalized CR, the RECOVER study provides the opportunity to systematically evaluate recovery patterns and treatment response across distinct cardiovascular subgroups. Due to the unique and highly innovative infrastructure available at the recruiting site, the monocentric design enables performance of an extensive standardized assessment. By incorporating digital technologies in conjunction with deep phenotypic and biomarker data, RECOVER holds promise to enable tailored CR strategies.
Authors: Jan Riess, Elisa Alba Schmidt, Gloria Petrasch, Hadassa Brito Da Silva, Sarah Sichler, Pietro Sartori, Eleonora Di Carluccio, Cornelia Haberfellner, Juliana Senftinger, Miriam Albus, Kathrin Bieri, Claudio Rhyner, Greta Hametner, Luisa M. Prechtl, Meike Distler, Lena Jellestad, Flavio D'Ascenzi, Milena Sokolowska, Hector Rodriguez Cetina Biefer, Omer Dzemali, Roger Von Moos, Raphael Twerenbold, Martin Loidl, Felix C. Tanner, Caroline Lustenberger, Thijs M.H. Eijsvogels, Esmée A. Bakker, Corey R. Tomczak, Aaron Baggish, Simon Kraler, Elmar Aigner, Alex W. Carter, Nicole Bauer, Martin Röösli, Imad El Haddad, Daniel Häuptli, Tsogyal D. Latshang, Jan Steffel, Mark J. Haykowsky, Stefan Blankenberg, Jan Vontobel, Andreas Ziegler, David Niederseer
Institutions: Universität Hamburg, University Medical Center Hamburg-Eppendorf, Hochgebirgsklinik Davos, University of Zurich, CK-CARE, University Hospital Zurich, University of Siena, Triemli Hospital, Kantonsspital Graubünden, University of Salzburg, ETH Zurich, Institute of Human Movement Sciences and Sport, Radboud University Medical Center, University of Saskatchewan, Centre Hospitalier Universitaire Vaudois, University Hospital of Bern, Paracelsus Medical University, London School of Economics and Political Science, Swiss Federal Institute for Forest, Snow and Landscape Research, Swiss Tropical and Public Health Institute, University of Basel, Paul Scherrer Institute, Klinik Hirslanden, University of Alberta, University of KwaZulu-Natal
Language: English
Subfield: Cardiology and Cardiovascular Medicine
Field: Medicine
Domain: Health Sciences
Open Access status: gold
Estimated APC paid: $2,810
OpenAlex ID: W7222921491