Glucagon-Like Peptide-1 Receptor Agonists in Hip and Knee Arthroplasty: A Comprehensive Systematic Review and Meta-Analysis of Perioperative and Postoperative Outcomes

Background: Obesity drives demand for total hip arthroplasty (THA) and total knee arthroplasty (TKA) and increases the risks of infection, wound complications, and revision. Glucagon-like peptide-1 receptor agonists (GLP-1RAs) are increasingly used for metabolic optimization, but their perioperative safety and effect on arthroplasty outcomes remain unclear. This study evaluated associations between perioperative GLP-1RA use and postoperative outcomes following THA and TKA. Methods: A Preferred Reporting Items for Systematic Reviews and Meta-Analyses-compliant systematic review identified studies of adults undergoing primary or revision THA/TKA with perioperative GLP-1RA exposure (0-12 months preoperatively or ≤30 days postoperatively). PubMed, MEDLINE, and EMBASE were searched through August 20, 2025. Data on demographics, surgical and medical complications, and resource use were collected at 90 days and 1-2 years. Fixed- and random-effects meta-analyses pooled odds ratios (ORs) with 95% confidence intervals (CIs). Results: Thirteen retrospective cohorts including 1,408,609 patients (39,614 THA; 1,373,771 TKA) were analyzed. GLP-1RA use was associated with reduced 90-day periprosthetic joint infection (OR: 0.77; 95% CI: 0.66-0.89), lower 90-day all-cause revision (OR: 0.88; 95% CI: 0.82-0.95), and decreased 90-day readmission (OR: 0.79; 95% CI: 0.70-0.89). A 1-year increase in periprosthetic fracture risk was observed (OR: 1.49; 95% CI: 1.08-2.07), mainly in TKA. No associations were seen for venous thromboembolism, pulmonary embolism, renal failure, pneumonia, cardiac arrest, or aspiration. Conclusions: Perioperative GLP-1RA use in THA and TKA improves early infection, revision, and readmission outcomes without increasing short-term medical or aspiration risk. The observed 1-year fracture risk warrants further study. Prospective trials are needed to define optimal timing and patient selection.