2026-06-14T03:43:12Zhttps://repisalud.isciii.es/rest/oai/request

oai:repisalud.isciii.es:20.500.12105/71602025-05-21T13:23:17Zcom_20.500.12105_2052com_20.500.12105_2051col_20.500.12105_19612col_20.500.12105_19619

00925njm 22002777a 4500 dc García-Olmos, Luis author Rodríguez-Salvanés, Francisco author Batlle-Pérez, Maurice author Aguilar-Torres, Río author Porro-Fernández, Carlos author García-Cabello, Alfredo author Carmona, Montserrat author Ruiz-Alonso, Sergio author Garrido-Elustondo, Sofía author Alberquilla, Angel author Sanchez-Gomez, Luis Maria author Sánchez-de-Madariaga, Ricardo author Monge-Navarrete, Elena author Benito-Ortiz, Luis author Baños-Pérez, Nicolás author Simón-Puerta, Amaya author López Rodríguez, Ana Belén author Martínez-Álvarez, Miguel Ángel author Velilla-Celma, María Ángeles author Bernal-Gómez, María Isabel author 2017-06-08 BACKGROUND: Chronic heart failure (CHF) reduces quality of life and causes hospitalisation and death. Identifying predictive factors of such events may help change the natural history of this condition. AIM: To develop and validate a stratification system for classifying patients with CHF, according to their degree of disability and need for hospitalisation due to any unscheduled cause, over a period of 1 year. METHODS AND ANALYSIS: Prospective, concurrent, cohort-type study in two towns in the Madrid autonomous region having a combined population of 1 32 851. The study will include patients aged over 18 years who meet the following diagnostic criteria: symptoms and typical signs of CHF (Framingham criteria) and left ventricular ejection fraction (EF)<50% or structural cardiac lesion and/or diastolic dysfunction in the presence of preserved EF (EF>50%).Outcome variables will be(a) Disability, as measured by the WHO Disability Assessment Schedule V.2.0 Questionnaire, and (b) unscheduled hospitalisations. The estimated sample size is 557 patients, 371 for predictive model development (development cohort) and 186 for validation purposes (validation cohort). Predictive models of disability or hospitalisation will be constructed using logistic regression techniques. The resulting model(s) will be validated by estimating the probability of outcomes of interest for each individual included in the validation cohort. ETHICS AND DISSEMINATION: The study protocol has been approved by the Clinical Research Ethics Committee of La Princesa University Teaching Hospital (PI-705). All results will be published in a peer-reviewed journal and shared with the medical community at conferences and scientific meetings. BMJ Open. 2017 Jun 8;7(6):e014840 10.1136/bmjopen-2016-014840 2044-6055 BMJ open 28600367 http://hdl.handle.net/20.500.12105/7160 Development and validation of a risk stratification model for prediction of disability and hospitalisation in patients with heart failure: a study protocol