A Contemporary, Population-Based Analysis of the Incidence, Cost, Outcomes, and Preoperative Risk Prediction of Postoperative Delirium Following Major Urologic Cancer Surgeries

Abstract

Introduction

Postoperative delirium is associated with poor outcomes and increased healthcare costs across numerous surgical and medical disciplines. Although characterized in other surgical fields, the population-based incidence, outcomes, and cost of delirium have not been assessed in major urologic cancer surgeries. We sought to evaluate the incidence, outcomes, and cost of postoperative delirium after major urologic cancer surgeries, specifically after radical prostatectomy (RP), radical nephrectomy (RN), partial nephrectomy (PN), and radical cystectomy (RC) in the USA. We have also developed a preoperative risk prediction model specific to major urologic cancer surgeries to identify patients at high risk for postoperative delirium.

Methods

Using the Premier Hospital Database, we retrospectively identified patients who underwent radical prostatectomy (RP), radical nephrectomy (RN), partial nephrectomy (PN), and radical cystectomy (RC) from 2003 to 2013. Postoperative delirium was identified using ICD-9 codes, as well as postoperative use of antipsychotics, sitters, and restraints. We constructed regression models to assess for mortality, discharge disposition, length of stay (LOS), and direct hospital costs.

A preoperative risk stratification scoring system was also developed using known risk factors of delirium. The entire cohort was randomly divided into training (70%) and validation (30%) cohorts. Preoperative patient, hospital, and surgical characteristics associated with delirium were analyzed using multivariate regression, and a risk prediction score was developed using the training cohort. Its performance was quantified using Receiver Operating Characteristic (ROC) analysis in both cohorts.

Results

We identified 165,387 patients representing a weighted total of 1,097,355 patients. 30,063 (2.7%) experienced postoperative delirium. The greatest incidence of delirium occurred after RC, with 6,268 cases (11%). Delirious patients had greater adjusted odds of in-hospital mortality (OR 3.65; p <0.001), 90-day mortality (OR 1.47; p = 0.013), discharge with home health services (OR 2.25; p <0.001), discharge to skilled nursing facilities (OR 4.64; p <0.001), and 0.9-day increase in median LOS (p <0.001). Delirious patients also experienced a $2,697 increase in direct admission costs (p <0.001), with the greatest costs in RC patients ($30,859 vs. $26,607; p<0.001). The largest driver of costs was in room and board across all surgeries (p<0.001).

Our training and validation cohorts consisted of a weighted total of 767,408 and 329,926 patients, respectively. Our final model revealed many factors that increase risk for delirium, which were used to create a preoperative risk score. The additive score was predictive of delirium in both the training (OR: 1.35, 95% CI, 1.32-1.37, p<0.001) and validation cohorts (OR: 1.34, 95% CI 1.31-1.36, p<0.001). The score also demonstrated good discrimination in predicting delirium in the training (AUC: 0.74, 95% CI, 0.74-0.76) and validation (AUC: 0.75, 95% CI, 0.73-0.76) cohorts.

Conclusion

Patients with postoperative delirium experienced worse outcomes, prolonged LOS, and increased admission costs following major urologic cancer surgeries. In particular, the largest incidence and costs occurred in delirious patients after RC. Moreover, the results of the pre-operative risk prediction tool for delirium following major urologic cancer surgeries are promising given their consistency with published delirium risk factors and ease of use. Further testing will shed light on its clinical utility.