Preoperative sleep medication use and outcomes following lumbar spine surgery

Although postoperative sleep disruption adversely affects recovery, the prognostic impact of preoperative sleep disturbance remains underexplored. This study investigates whether preoperative sleep disturbance, proxied by long-term sleep medication prescriptions, is associated with poorer postoperative outcomes following lumbar spine surgery.

A retrospective cohort analysis was conducted using the Merative MarketScan Databases (2000-2021). Adults undergoing lumbar fusion or decompression for degenerative disorders were included. Patients were stratified by preoperative polypharmacy and sleep medication use (defined as consistent use ≥6 months). Primary outcomes were healthcare utilization (length of stay [LOS], payments, readmissions), complications, mental health diagnoses, and opioid use over 24 months. Adjusted regression analyses controlled for demographic factors and comorbidity burden.

Among 118,434 patients, 15.8% were preoperative sleep medication users. In patients without polypharmacy (n = 37,682), sleep medication use was associated with significantly higher hospitalization costs, long-term healthcare payments, and markedly increased rates of high postoperative opioid utilization (19% vs. 10% at 6 months, q = 0.0002). In the polypharmacy cohort (n = 80,752), sleep medication use was linked to worse outcomes across all domains: longer LOS, lower home discharge rates, higher costs, increased complications (e.g., surgical site infection, renal injury), significantly elevated rates of depression and anxiety, and substantially higher short- and long-term opioid use (61% vs. 49% high use at 6 months, q = 0.0002).

Preoperative sleep medication use is a significant marker for increased postoperative healthcare utilization, complications, mental health diagnoses, and prolonged opioid use after lumbar spine surgery, with effects most pronounced in patients with polypharmacy. These findings highlight the need to integrate sleep health assessment into preoperative optimization strategies.