Abstract
INTRODUCTION
Opiates are commonly used for the initial treatment of degenerative lumbar stenosis (DLS). However, current evidence suggests that overuse of opioids may alter pain-modulatory systems and increase pain sensitivity, which may worsen the underlying condition. As such, patients undergoing operative treatment for DLS with concomitant opioid use represent a clinically challenging population. Moreover, patients with Workers' compensation (WC) are a clinically distinct population with variable outcomes. Our objective was to investigate the impact of prolonged opioid use in the preoperative treatment plan for WC patients with DLS.
METHODS
1901 WC subjects from the Ohio Bureau of Workers' Compensation (BWC) with DLS were identified. 140 subjects were then identified that were on opioid therapy before index surgery. The Short-Term Opioid (STO) use group included 60 subjects who received opioids for less than 3 months and a Long-Term Opioid (LTO) use group included 80 subjects who received opioids for greater than 3 months before their surgery. Our primary outcome was if patients were able to make a stable return to work (RTW). A multivariate regression analysis was used to examine the relationship of duration of opioid therapy with RTW.
RESULTS
>Patients in the STO cohort had a significantly higher RTW rate compared to the LTO cohort (25/60[42%] vs. 18/80[23%]; P = 0.01). A logistic regression was performed to examine the effect of preoperative opioid therapy duration on RTW status. Our regression model showed that opioid use greater than 3 months remained a significant negative predictor of RTW(OR: 0.35, 95% CI: 0.13-0.89; P = 0.02). Costs accrued over the 3 years after index surgery was significantly higher in the LTO cohort.
CONCLUSION
Prolonged preoperative opioid use was associated with poor clinical outcomes after lumbar decompression. These results suggest that a shorter course of opioid therapy and earlier surgical intervention may improve outcomes and lower postoperative morbidity in patients with DLS.
