Development of a Simple Clinical Tool for Predicting Early Dropout in Cardiac Rehabilitation
| Autor: | Grace LaValley, Michel Farah, Quinn R. Pack, Peter K. Lindenauer, Tara Lagu, Heidi Szalai, Paul Visintainer |
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| Rok vydání: | 2020 |
| Předmět: |
Pulmonary and Respiratory Medicine
medicine.medical_specialty Rehabilitation business.industry medicine.medical_treatment MEDLINE 030204 cardiovascular system & hematology Logistic regression Single Center 03 medical and health sciences Risk model 0302 clinical medicine 030228 respiratory system Internal medicine Referral diagnosis medicine Cardiology and Cardiovascular Medicine Adverse effect business Dropout (neural networks) |
| Zdroj: | Journal of Cardiopulmonary Rehabilitation and Prevention. 41:159-165 |
| ISSN: | 1932-7501 |
| DOI: | 10.1097/hcr.0000000000000541 |
| Popis: | BACKGROUND Nonadherence to cardiac rehabilitation (CR) is common despite the benefits of completing a full program. Adherence might be improved if patients at risk of early dropout were identified and received an intervention. METHODS Using records from patients who completed ≥1 CR session in 2016 (derivation cohort), we employed multivariable logistic regression to identify independent patient-level characteristics associated with attending |
| Databáze: | OpenAIRE |
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