Relationship Between Comorbidity Burden and Short-Term Outcomes Across 4680 Consecutive Spinal Fusions.

ABSTRACT

OBJECTIVE: Preoperative management requires the identification and optimization of modifiable medical comorbidities, though few studies isolate comorbid status from related patient-level variables. This study evaluates Charlson Comorbidity Index (CCI)-an easily derived measure of aggregate medical comorbidity-to predict outcomes from spinal fusion surgery. Coarsened exact matching is employed to control for key patient characteristics and isolate CCI. METHODS: We retrospectively assessed 4680 consecutive patients undergoing single-level, posterior-only lumbar fusion at a single academic center. Logistic regression evaluated the univariate relationship between CCI and patient outcomes. Coarsened exact matching generated exact demographic matches between patients with high comorbid status (CCI >6) or no medical comorbidities (matched n = 524). Patients were matched 11 on factors associated with surgical outcomes, and outcomes were compared between matched cohorts. Primary outcomes included surgical complications, discharge status, 30- and 90-day risk of readmission, emergency department (ED) visits, reoperation, and mortality. RESULTS: Univariate regression of increasing CCI was significantly associated with non-home discharge, as well as 30- and 90-day readmission, ED visits, and mortality (all P < 0.05). Subsequent isolation of comorbidity between otherwise exact-matched cohorts found comorbid status did not affect readmissions, reoperations, or mortality; high CCI score was significantly associated with non-home discharge (OR = 2.50, P < 0.001) and 30-day (OR = 2.44, P = 0.02) and 90-day (OR = 2.29, P = 0.008) ED evaluation. CONCLUSIONS: Comorbidity, measured by CCI, did not increase the risk of readmission, reoperation, or mortality. Single-level, posterior lumbar fusions may be safe in appropriately selected patients regardless of comorbid status. Future studies should determine whether CCI can guide discharge planning and postoperative optimization.