Heterogeneity of included studies
The meta-analysis included studies with varying durations, baseline characteristics, and types of AOMs, potentially introducing heterogeneity. The authors used a random-effects model to mitigate this, but it's still a significant concern.
Small number of included studies and limited data
The small number of included studies (n=11) limits the power of the analysis, especially for subgroup analyses, potentially leading to unreliable conclusions. The limited data also affects the reliability of the meta-regression analysis.
Focusing primarily on weight and BMI as outcome measures neglects other important parameters related to weight loss efficacy, such as body composition changes, and metabolic markers like blood pressure, lipids, and glucose. This gives an incomplete picture of AOMs effects after discontinuation.
Exclusion of other weight loss strategies
Excluding studies on lifestyle interventions and bariatric surgery prevents comparisons with other weight loss strategies. This makes it difficult to contextualize how weight regain after AOM discontinuation compares to other approaches.
Some studies didn't primarily focus on weight change after treatment discontinuation. Also, some data were extracted from appendices or ClinicalTrials.gov. This raises concerns about data consistency and potential bias. It makes the data itself less rigorous.