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Such inconsistency may raise questions regarding reliability

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A Bayesian hierarchical model was fitted using the brms framework, specifying percent weight change as a Gaussian outcome with (i) drug-specific smooth dose effects (splines by drug), (ii) treatment duration included as a covariate to account for variability in follow-up time across trials, and (iii) a study-level random intercept to account for between-trial heterogeneity

appetite and behavior shifts become more consistent Months 36: Continued progress with structured followups Maintenance: Sustain results with a personalized plan and ongoing checkins Results vary