eHealth interventions and patients with metabolic dysfunction-associated steatotic liver disease: a systematic review and meta-analysis

Abstract

Objective: Metabolic dysfunction-associated steatotic liver disease (MASLD) is a growing global health concern, with increasing mortality rates driven by the obesity pandemic. Weight loss has been shown to improve MASLD outcomes, yet the effectiveness of eHealth interventions in MASLD management remains uncertain. We aimed to evaluate the effectiveness of eHealth interventions compared with standard care in improving health outcomes among patients with MASLD.

Design: A systematic review and meta-analysis were conducted in accordance with Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines.

Data sources: Relevant studies were retrieved from PubMed, Cochrane Central and Embase databases from inception to 26 April 2024.

Eligibility criteria: Only double-arm clinical trials involving human participants diagnosed with MASLD were included. Eligible studies were limited to those published in English.

Data extraction and synthesis: eHealth interventions-including internet-based platforms, smartwatches, telephone follow-ups and mobile applications for dietary and exercise modifications-were compared against traditional intervention methods. The primary outcomes assessed were changes in body weight, abdominal/waist circumference, aspartate aminotransferase (AST) and alanine transaminase (ALT). Secondary outcomes were changes in body mass index (BMI), diastolic blood pressure, systolic blood pressure, MASLD fibrosis score, high-density lipoprotein, gamma-glutamyl transferase and triglycerides.

Results: 11 studies met the inclusion criteria, of which 10 provided relevant outcomes and were included. The mean age of participants across the studies ranged from 39.3 to 57.9 years, with intervention durations spanning 3 to 24 months. Our results indicate significant improvements with eHealth interventions compared with control comparators, including reductions in AST (standardised mean difference (SMD): -0.35 (95% CI -0.61, -0.10); p<0.05), ALT (SMD: -0.38 (95% CI -0.65, -0.11); p<0.05), weight loss (SMD: -0.38 (95% CI -0.60, -0.17); p<0.05) and BMI (SMD: -0.37 (95% CI -0.54, -0.21); p<0.05).

Conclusions: The utilisation of eHealth interventions showed significant improvements in outcomes related to AST, ALT, abdominal circumference, weight loss and BMI. However, future studies with larger sample sizes and longer follow-ups are warranted to assess the sustainability of these outcomes.

Keywords: META-ANALYSIS; Mobile Applications; NONALCOHOLIC STEATOHEPATITIS; Non-alcoholic Fatty Liver Disease; OBESITY.

Figure 1. Forest plot assessing the effect of eHealth interventions versus standard care on (A) weight loss, (B) abdominal/waist circumference, (C) aspartate aminotransferase levels and (D) alanine aminotransferase levels in patients with MASLD. MASLD, metabolic dysfunction-associated steatotic liver disease.

Figure 2. Forest plot assessing the effect of eHealth interventions versus standard care on (A) body mass index, (B) diastolic blood pressure, (C) systolic blood pressure, (D) MASLD fibrosis score (E) high-density lipoprotein levels, (F) gamma-glutamyl transferase levels, and (G) triglyceride levels in patients with MASLD. MASLD, metabolic dysfunction-associated steatotic liver disease.

Figure 3. Forest plot for subgroup analyses of eHealth interventions on weight loss, including (A) comprehensive lifestyle interventions (CLI) versus partial lifestyle interventions (PLI), (B) eHealth interventions at 3-month vs 6-month follow-up, (C) frequency of contact (daily vs monthly) and (D) mobile phone applications versus other eHealth interventions in patients with MASLD. MASLD, metabolic dysfunction-associated steatotic liver disease.