Study Design: A retrospective, propensity score-matched cohort study using a large national claims database (2010–2023). Objective: To evaluate the association between preoperative glucagon-like peptide-1 (GLP-1) receptor agonist use and postoperative outcomes following cervical spine fusion (CSF), stratified by body mass index (BMI). Background: Cervical spine fusion is a standard treatment for degenerative spine conditions, but it carries risks of complications and revision surgeries, particularly in obese patients. GLP-1 receptor agonists are known for their metabolic benefits, yet their role in improving spinal surgical outcomes remains unclear, especially across BMI categories. Materials and Methods: Patients undergoing anterior or posterior CSF were identified from the PearlDiver Mariner170 database. GLP-1 RA users were matched 1:4 to non-users by age, sex, and Charlson Comorbidity Index within six BMI strata. Outcomes included 90-day postoperative complications and revision surgeries at two and 10 years. Statistical significance was determined using Cox proportional hazards models and χ 2 tests with Bonferroni correction ( P ≤ 0.00026). Results: Of 452,869 CSF patients, 33,715 (7.4%) used GLP-1 RAs preoperatively. After matching, 32,453 users and 129,622 controls were analyzed. GLP-1 RA use was associated with significantly fewer 90-day complications—including surgical site infections, pneumonia, deep vein thrombosis, and pulmonary embolism—across all BMI groups ≥25 ( e.g ., surgical site infection in BMI 30–34.9: 0.2% vs . 1.0%, P < 0.001). However, GLP-1 RA use did not correlate with reduced revision rates at either two or 10 years in any BMI category. Conclusion: Preoperative GLP-1 RA use is associated with substantial reductions in 90-day postoperative complications following CSF, particularly among overweight and obese patients. However, these agents do not influence long-term revision risk. The short-term benefits may stem from anti-inflammatory and metabolic effects of GLP-1 RAs, supporting their use as a perioperative optimization strategy in high-risk populations.
Kishan et al. (Thu,) studied this question.
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