Predicting Length of Stay After Thoracolumbar Trauma: A Single-Center, Retrospective Analysis.

BACKGROUND

Length of stay (LOS) is a meaningful outcome measure for more efficient and effective quality of care. However, algorithms to predict LOS have yet to be created for patients who undergo surgical management for traumatic spinal fractures.

OBJECTIVES

The objectives of this study were to (1) identify preoperative, perioperative, and postoperative factors associated with increased LOS and (2) create predictive formulas to estimate LOS in thoracolumbar trauma patients who undergo surgical correction.

METHODS

This is a retrospective case series of 196 patients operated for thoracolumbar spine trauma from January 2012 to December 2017 at a level 1 trauma and academic institution. Bivariate analysis between LOS and various preoperative, perioperative, and postoperative factors was conducted to identify significant associations. Multivariate analysis was conducted to create models capable of predicting LOS.

RESULTS

LOS was significantly associated with various preoperative (eg, Charlson Comorbidity Index, Glasgow Coma Scale [GCS], injury severity score), operative (eg, length of surgery, number of instrumented segments, surgical technique), and postoperative variables (eg, complications, discharge location). Multivariate analysis of preoperative variables identified 5 significant independent predictors that could predict LOS with strong correlation with observed LOS ( = 0.63). With all variables considered, multivariate analysis identified 8 variables (GCS, American Society of Anesthesiologists score, neurological status, polytrauma, packed red blood cell transfusion, number of unique postoperative complications, skin complications, and discharge facility) that could predict LOS with strong correlation ( = 0.80).

CONCLUSIONS

Various preoperative, perioperative, and postoperative factors are significantly associated with LOS in traumatic thoracolumbar spine patients. We developed models with good predictive capacity for LOS. If validated, these models should help in risk stratifying patients for increased LOS and consequently improve perioperative patient counseling.

CLINICAL RELEVANCE

This article contributes to identifying and predicting patients who are high risk for extended LOS after traumatic thoracolumbar injuries.