Effectiveness and Cost-Effectiveness of Self-Management Interventions for Adults Living with Heart Failure to Improve Patient-Important Outcomes: An Evidence Map of Randomized Controlled Trials.
Marilina SanteroYang SongJessica BeltranMelixa Medina-AedoCarlos Canelo-AybarClaudia ValliClaudio RochaMontserrat León GarciaKarla SalasChrysoula KaloterakiEna Pery Niño de Guzmán QuispeMarta BallesterAna Isabel GonzalezRune PoortvlietMarieke van der GaagCristina SpoialaPema GurungFabienne WillemenIza CoolsJulia BleekerAngelina K KanchevaJulia ErtlTajda LaureIvana KanchevaKevin Pacheco-BarriosJessica Hanae Zafra TanakaSofia TsokaniAreti Angeliki VeronikiGeorgios SeitidisChristos ChristogiannisKaterina-Maria KontouliOliver GröneRosa SuñolCarola OrregoMonique HeijmansPablo Alonso-CoelloPublished in: Healthcare (Basel, Switzerland) (2024)
Self-management interventions (SMIs) may enhance heart failure (HF) outcomes and address challenges associated with disease management. This study aims to review randomized evidence and identify knowledge gaps in SMIs for adult HF patients. Within the COMPAR-EU project, from 2010 to 2018, we conducted searches in the databases MEDLINE, CINAHL, Embase, Cochrane, and PsycINFO. We performed a descriptive analysis using predefined categories and developed an evidence map of randomized controlled trials (RCTs). We found 282 RCTs examining SMIs for HF patients, comparing two to four interventions, primarily targeting individual patients (97%) globally (34 countries, only 31% from an European country). These interventions involved support techniques such as information sharing (95%) and self-monitoring (62%), often through a mix of in-person and remote sessions (43%). Commonly assessed outcomes included quality of life, hospital admissions, mortality, exercise capacity, and self-efficacy. Few studies have focused on lower socio-economic or minority groups. Nurses (68%) and physicians (30%) were the primary providers, and most studies were at low risk of bias in generating a random sequence for participant allocation; however, the reporting was noticeably unclear of methods used to conceal the allocation process. Our analysis has revealed prevalent support techniques and delivery methods while highlighting methodological challenges. These findings provide valuable insights for researchers, clinicians, and policymakers striving to optimize SMIs for individuals living with HF.
Keyphrases
- heart failure
- end stage renal disease
- ejection fraction
- newly diagnosed
- physical activity
- healthcare
- randomized controlled trial
- prognostic factors
- systematic review
- peritoneal dialysis
- acute heart failure
- metabolic syndrome
- type diabetes
- machine learning
- mental health
- left ventricular
- cross sectional
- patient reported outcomes
- palliative care
- cardiovascular disease
- insulin resistance
- cardiovascular events
- atrial fibrillation
- case control
- open label
- adipose tissue
- health information
- quality improvement
- high intensity
- coronary artery disease
- double blind
- deep learning
- phase iii
- neural network
- glycemic control