RESUMEN
Heart failure is a prevalent syndrome with high mortality rates, representing a significant economic burden in terms of healthcare. The lack of systematic information about the treatment and adherence of patients with heart failure limits the understanding of these aspects and potentially the improvement of clinical outcomes. OBJECTIVE: To describe the clinical characteristics, therapeutic management, adherence, persistence, and clinical results, as well as the association between these variables, in a cohort of patients with heart failure in Andalusia. DESIGN: This study will be an observational, population-based, retrospective cohort study. Data of patients discharged from an Andalusian hospital with a diagnosis of heart failure between 2014 and 2023 will be extracted from the Andalusian population health database. ANALYSIS: The statistical analysis will incorporate the following strategies: (1) Descriptive analysis of the characteristics of the population cohort, adherence measures, and clinical outcomes. (2) Bivariate analyses to study the association of covariates with adherence, persistence, and clinical results. (3) Multivariate logistic regression and Cox regression analysis including relevant covariates. (4) To evaluate changes over time, multivariate Poisson regression models will be used. By conducting this comprehensive study, we aim to gain valuable insights into the clinical characteristics, treatment management, and adherence of heart failure patients in Andalusia, as well as to identify factors that may influence clinical outcomes. These findings could be critical both for the development of optimised strategies that improve medical care and quality of life of patients and for mitigating the health burden of HF in the region.
RESUMEN
Heart failure is a prevalent syndrome with high mortality rates, representing a significant economic burden in terms of healthcare. The lack of systematic information about the treatment and adherence of patients with heart failure limits the understanding of these aspects and potentially the improvement of clinical outcomes. OBJECTIVE: To describe the clinical characteristics, therapeutic management, adherence, persistence and clinical results, as well as the association between these variables, in a cohort of patients with heart failure in Andalusia. DESIGN: This study will be an observational, population-based, retrospective cohort study. Data of patients discharged from an Andalusian hospital with a diagnosis of heart failure between 2014 and 2023 will be extracted from the Andalusian population health database. ANALYSIS: The statistical analysis will incorporate the following strategies: 1) Descriptive analysis of the characteristics of the population cohort, adherence measures, and clinical outcomes. 2) Bivariate analyses to study the association of covariates with adherence, persistence and clinical results. 3) Multivariate logistic regression and Cox regression analysis including relevant covariates. 4) To evaluate changes over time, multivariate Poisson regression models will be used. By conducting this comprehensive study, we aim to gain valuable insights into the clinical characteristics, treatment management, and adherence of heart failure patients in Andalusia, as well as to identify factors that may influence clinical outcomes. These findings could be critical both for the development of optimized strategies that improve medical care and quality of life of patients and for mitigating the health burden of HF in the region.
RESUMEN
BACKGROUND: Functional impairment is one of the most decisive prognostic factors in patients with complex chronic diseases. A more significant functional impairment indicates that the disease is progressing, which requires implementing diagnostic and therapeutic actions that stop the exacerbation of the disease. OBJECTIVE: This study aimed to predict alterations in the clinical condition of patients with complex chronic diseases by predicting the Barthel Index (BI), to assess their clinical and functional status using an artificial intelligence model and data collected through an internet of things mobility device. METHODS: A 2-phase pilot prospective single-center observational study was designed. During both phases, patients were recruited, and a wearable activity tracker was allocated to gather physical activity data. Patients were categorized into class A (BI≤20; total dependence), class B (20