Evaluation of the Efficacy of Pharmacological Interventions in the Prevention of Acute Mountain Sickness: A Network Meta-Analysis

Acute mountain sickness (AMS) is a common altitude-related condition affecting individuals ascending to high elevations, presenting with headache, nausea, fatigue, and dizziness. Although several pharmacological agents have been proposed for AMS prophylaxis, their comparative effectiveness remains insufficiently established. A systematic review and network meta-analysis were conducted in accordance with Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Major electronic databases were searched for randomized controlled trials (RCTs) assessing pharmacological interventions for AMS prophylaxis. Data from 46 eligible studies were extracted using Microsoft Excel (Microsoft Corp., Redmond, WA, USA) and analyzed with R software (R Foundation for Statistical Computing, Vienna, Austria). The primary outcome was AMS incidence. Network geometry was mapped using network plots; treatment effects were calculated as odds ratios (ORs) with 95% confidence intervals (CIs); and interventions were ranked using surface under the cumulative ranking (SUCRA) probabilities. Risk of bias was assessed, and certainty of evidence was determined by CINeMA (Confidence in Network Meta-Analysis). The analysis incorporated 46 studies evaluating multiple pharmacological agents. SUCRA rankings identified inhaled budesonide as the most efficacious agent for AMS prevention, followed by acetazolamide and theophylline. Most studies demonstrated low risk of bias. Acetazolamide exhibited narrower CIs, reflecting a more robust and reliable evidence base. CINeMA showed overall moderate certainty of evidence. Inhaled budesonide had the highest probability of being the most effective pharmacological agent for AMS prevention, with acetazolamide and theophylline also demonstrating substantial efficacy. Acetazolamide remains the best-evidenced option. Additional high-quality RCTs are required to consolidate treatment hierarchies and evaluate agents with limited current data.