Clinical tool for prognostication of discharge outcomes following craniotomy for meningioma

Abstract

Background: Patients' comorbidities might affect the immediate postoperative morbidity and discharge disposition after surgical resection of intracranial meningioma.

Objective: To study the impact of comorbidities on outcomes and provide a web-based application to predict time to favorable discharge.

Methods: A retrospective review of the prospectively collected national inpatient sample (NIS) database was conducted for the years 2009-2013. Time to favorable discharge was defined as hospital length of stay (LOS). A favorable discharge was defined as a discharge to home and a non-home discharge destination was defined as an unfavorable discharge. Cox proportional hazards model was built. Full model for time to discharge and separate reduced models were built.

Results: Of 10,757 patients who underwent surgery for meningioma, 6554 (60%) had a favorable discharge. The median hospital LOS was 3 days (interquartile range [IQR] 2-5). In the full model, several clinical and socioeconomic factors were associated with a higher likelihood of unfavorable discharge. In the reduced model, 13 modifiable comorbidities were negatively associated with a favorable discharge except for drug abuse and obesity, which are not associated with discharge. Both models accurately predicted time to favorable discharge (c-index:0.68-0.71).

Conclusion: We developed a web application using robust prognostic model that accurately predicts time to favorable discharge after surgery for meningioma. Using this tool will allow physicians to calculate individual patient discharge probabilities based on their individual comorbidities and provide an opportunity to timely risk stratify and address some of the modifiable factors prior to surgery.

Keywords: Discharge; Meningioma; NIS; Operative; Outcomes; Prediction.