Resident Cedars-Sinai Medical Center Yorba Linda, CA, US
Introduction: Malnutrition is a known risk factor for adverse surgical outcomes, including prolonged hospital stays. In patients undergoing complex procedures such as multilevel scoliosis surgery, understanding the impact of malnutrition on length of stay (LOS) can inform preoperative planning and postoperative care strategies. This study evaluates whether incorporating malnutrition status improves the prediction of patients in the top quartile of LOS.
Methods: Using the Nationwide Readmissions Database (NRD), we identified 8,122 patients who underwent multilevel scoliosis surgery. Patients were categorized as malnourished (n=441) or not malnourished (n=7,681) based on ICD-10 codes indicating vitamin and mineral deficiencies. The top quartile of LOS was defined as >7 days for patients without malnutrition and >16 days for those with malnutrition. Two mixed-effects models were developed: one agnostic to malnutrition status and the other incorporating it. Fixed effects included age, sex, insurance status, NRD discharge weighting, and median income by ZIP code. Random effects accounted for hospital characteristics. Predictive performance was assessed using AUC, and statistical significance was defined as a p-value < 0.05.
Results: The model agnostic to malnutrition status achieved an AUC of 0.842, indicating strong predictive capability for prolonged LOS. Incorporating malnutrition status increased the AUC to 0.910, demonstrating significantly improved model performance (p < 0.001). These findings suggest that malnourished patients are more likely to experience extended hospital stays, even when accounting for other demographic and socioeconomic factors.
Conclusion : Malnutrition is a significant predictor of prolonged LOS in patients undergoing multilevel scoliosis surgery. The inclusion of malnutrition status substantially enhances the predictive accuracy of models, emphasizing the importance of nutritional assessment and intervention in perioperative care. These results highlight the need for proactive identification and management of malnutrition to improve outcomes and optimize hospital resource use.