Predictors of Operative Time and Length of Stay in Robot-assisted Transforaminal Lumbar Interbody Fusions

Introduction: Prolonged operative time and post-operative length of stay are associated with increased complications and cost after lumbar fusions. With the application of robotic technology to transforaminal lumbar interbody fusions (TLIF), operative times and post-operative length of stay have changed, and accurate predictions are crucial in improving operating room and hospital resource allocation. This study aims to identify predictors of operative time and length of stay in robot-assisted TLIF procedures.

Methods: From a single-center retrospective review, 142 patients were identified as undergoing TLIF for degenerative pathologies. Pre-operative demographics, assessments of motor and sensory neurological deficits, and comorbidities were extracted. Univariable analysis was performed using the Kruskal-Wallis test and significant variables (p < 0.1) were included in the multivariable analysis. All p-values < 0.05 were considered statistically significant.

Results: In univariable analysis, sex, BMI, Karnofsky score, revision status, indication, spinal level, incision type, and number of screws were associated with operative time in robot-assisted TLIFs, while race, BMI, smoking history, ASA status, Karnofsky scale, CCI, revision status, indication, incision type, and number of screws were associated with length of stay (all p< 0.1). Multivariable analysis showed that the number of screws (β=8.28 min, p=0.002), indication of deformity (β=51.3 min, p=0.005), midline incision (β=41.8 min, p< 0.001), and body mass index ≥ 30 kg/m² (β=23.3 min, p=0.001) were independently associated with operative time. Similarly, the number of screws (β=0.205 days, p=0.008) and Charlson Comorbidity Index (β=0.262 days, p=0.017) were independently associated with post-operative length of stay.

Conclusion : This study shows significant predictors of surgical operative time and post-operative length of stay in robot-assisted TLIF procedures. These findings can help with surgical planning and operating room allocation.