BackgroundHeart failure (HF) is a multifaceted clinical syndrome characterized by different etiologies, risk factors, comorbidities, and a heterogeneous clinical course. The current model, based on data from clinical trials, is limited by the biases related to a highly-selected sample in a protected environment, constraining the applicability of evidence in the real-world scenario. If properly leveraged, the enormous amount of data from real-world may have a groundbreaking impact on clinical care pathways. We present, here, the development of an HF DataMart framework for the management of clinical and research processes.MethodsWithin our institution, Fondazione Policlinico Universitario A. Gemelli in Rome (Italy), a digital platform dedicated to HF patients has been envisioned (GENERATOR HF DataMart), based on two building blocks: 1. All retrospective information has been integrated into a multimodal, longitudinal data repository, providing in one single place the description of individual patients with drill-down functionalities in multiple dimensions. This functionality might allow investigators to dynamically filter subsets of patient populations characterized by demographic characteristics, biomarkers, comorbidities, and clinical events (e.g., re-hospitalization), enabling agile analyses of the outcomes by subsets of patients. 2. With respect to expected long-term health status and response to treatments, the use of the disease trajectory toolset and predictive models for the evolution of HF has been implemented. The methodological scaffolding has been constructed in respect of a set of the preferred standards recommended by the CODE-EHR framework.ResultsSeveral examples of GENERATOR HF DataMart utilization are presented as follows: to select a specific retrospective cohort of HF patients within a particular period, along with their clinical and laboratory data, to explore multiple associations between clinical and laboratory data, as well as to identify a potential cohort for enrollment in future studies; to create a multi-parametric predictive models of early re-hospitalization after discharge; to cluster patients according to their ejection fraction (EF) variation, investigating its potential impact on hospital admissions.ConclusionThe GENERATOR HF DataMart has been developed to exploit a large amount of data from patients with HF from our institution and generate evidence from real-world data. The two components of the HF platform might provide the infrastructural basis for a combined patient support program dedicated to continuous monitoring and remote care, assisting patients, caregivers, and healthcare professionals.
Background Current guidelines recommend that patients with heart failure and a reduced ejection fraction (HFrEF) should receive four foundational treatments, i.e. renin-angiotensin system inhibitor (RASi) or angiotensin-receptor neprilysin inhibitor (ARNi), β-blocker, mineralocorticoid receptor antagonist (MRA) and sodium-glucose cotransporter 2 inhibitor (SGLT2i). There is emerging consensus that simultaneous initiation or rapid sequencing provide greater benefit, enhancing tolerability of these therapies and improving outcomes. However, implementation of a comprehensive approach is limited by common underuse and underdosing, and paucity of data exists on initiating the four pharmacological pillars of HFrEF during hospitalization or at discharge. Aim To investigate the feasibility of a comprehensive pharmacological approach in patients with HFrEF at discharge after an episode of heart failure (HF) hospitalization in a tertiary referral center. Methods In-patients with HFrEF and a first HF hospitalization (2019-2021) were categorized according to the number/type of treatments prescribed at discharge. Prevalence of contraindications and cautions for HFrEF treatments – as defined by current European Society of Cardiology (ESC) guidelines on HF – was as assessed. Logistic regression models were fitted to assess predictors of number of treatments prescribed and risk of re-hospitalization. Results Among 305 patients with HFrEF, 49.2% received at least two current recommended drugs. A β-blocker was prescribed in 93.4% of patients, and a RASi/ARNi in 68.2%. Based on current recommendations, 46.2% of patients could receive four foundational drugs. An MRA was prescribed in 32.5% of patients and 100% of patients did not show contraindications to MRA use. Renal dysfunction was present in 13.1% of patients, while hypotension in 11.8%. Bradycardia and renal dysfunction were associated with lower number of drugs prescribed [adjusted OR (95% CI) 0.18 (0.06-0.50), and 0.50 (0.39-0.64), respectively]. A higher number of drugs used was associated with no rehospitalization during the 30 days after discharge [OR (95% CI) 0.22 (0.10-0.49) per number of pillars increase]. Conclusions Based on the presence/absence of contraindications, a quadruple therapy could be implementable in a contemporary cohort of HFrEF in-patients at discharge. Renal dysfunction and bradycardia were the main prevalent conditions limiting the achievement of a more comprehensive therapeutic approach. Use of a higher number of drugs was associated with lower risk of re-hospitalization within 30 days after discharge.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.