General Session: MIS-2
Presented by: K. Kudaravalli - View Audio/Video Presentation (Members Only)
B. Mayo(1), D. Massel(1), D. Bohl(1), A. Narain(1), F. Hijji(1), K. Kudaravalli(1), K. Yom(1), K. Singh(1)
(1) Rush University Medical Center, Orthopaedic Surgery, Chicago, IL, United States
Introduction: Transforaminal lumbar interbody fusion (TLIF) is a common surgical treatment for degenerative lumbar disease. With an increasing focus on cost reduction, limiting the number of overnight stays has become a primary focus for hospitals and physicians alike. The risk factors for a long hospitalization following TLIF have not been well described in the literature. The purpose of the study is to describe the risk factors for a longer hospital stay following TLIF.
Methods: A prospectively maintained surgical database of patients who underwent a primary, one-level TLIF with unilateral cage for degenerative spinal pathology between 2010-2015 was reviewed. Both bivariate and stepwise multivariate Poisson regression with robust error variance were used to assess risk factors for discharge day after postoperative day 2. Potential risk factors included demographic, comorbidity, and procedural characteristics, as well as post-operative hourly narcotic consumption and mean postoperative inpatient pain score.
Results: A total of 253 patients were included in this analysis. On bivariate regression, female gender (RR=1.56; p=0.006), workers' compensation (RR=1.42; p=0.032), hypertension (RR=1.40; p=0.037), and average reported inpatient pain score ≥5 (RR=1.52; p=0.016) were found to be associated with an overnight stay. On multivariate stepwise regression, female gender (RR=1.72; p=0.001), workers' compensation (RR=1.77; p=0.001) and hypertension (RR=1.55; p=0.006) were found to be independently associated with a length of stay longer than 2 overnight stays.
Conclusions: The results of this study suggest that workers' compensation, female gender, and hypertension are independently associated with a longer length of stay following TLIF. Surgeons can use this information to better counsel their patients about the expected length of stay following TLIF. Further studies are needed to determine specific characteristics about these populations that lead to longer length of stays.