Which heart failure patients benefit most from non-invasive telemedicine? An overview of current evidence and future directions.
Jorna van EijkKim LuijkenJaap TrappenburgTiny JaarsmaFolkert W AsselbergsPublished in: Netherlands heart journal : monthly journal of the Netherlands Society of Cardiology and the Netherlands Heart Foundation (2024)
Telemedicine in heart failure (HF) management may positively impact health outcomes, but varied effects in studies hinder guidance in HF guidelines. Evidence on the effectiveness of telemedicine in HF subpopulations is limited. We conducted a scoping review to evaluate and synthesise evidence on the effectiveness of telemedicine across HF subpopulations that could guide telemedicine strategies in routine practice. Meta-analyses concerning randomised controlled trials (RCTs) with subgroup analyses on telemedicine effectives were identified in PubMed. We identified 15 RCTs, encompassing 21 different subgroups based on characteristics of HF patients. Findings varied across studies and no definite evidence was found about which patients benefit most from telemedicine. Subgroup definitions were inconsistent, not always a priori defined and subgroups contained few patients. Some studies found heterogeneous effects of telemedicine on mortality and hospitalisation across subgroups defined by: New York Heart Association (NYHA) classification, previous HF decompensation, implantable device, concurrent depression, time since hospital discharge and duration of HF. Patients represented in the RCTs were mostly male, aged 65-75 years, with HF with reduced ejection fraction and NYHA class II/III. Traditional RCTs have not been able to provide clinicians with guidance; continuous real-world evidence generation could enhance monitoring and identify who benefits from telemedicine.
Keyphrases
- end stage renal disease
- ejection fraction
- heart failure
- chronic kidney disease
- newly diagnosed
- peritoneal dialysis
- randomized controlled trial
- acute heart failure
- primary care
- healthcare
- type diabetes
- coronary artery disease
- depressive symptoms
- squamous cell carcinoma
- machine learning
- clinical practice
- atrial fibrillation
- quality improvement
- palliative care
- radiation therapy
- cardiovascular events
- left ventricular
- rectal cancer
- meta analyses
- patient reported outcomes
- double blind