Background: In patients undergoing pancreatoduodenectomy, non-home discharge is common and often results in an unnecessary delay in hospital discharge. This study aimed to develop and validate a preoperative prediction model to identify patients with a high likelihood of non-home discharge following pancreatoduodenectomy.
Methods: Patients undergoing pancreatoduodenectomy from 2013 to 2018 were identified using an institutional database. Patients were categorized according to discharge location (home vs. non-home). Preoperative risk factors, including social determinants of health associated with non-home discharge, were identified using Pearson's chi-squared test and then included in a multiple logistic regression model. A training cohort composed of 80% of the sampled patients was used to create the prediction model, and validation carried out using the remaining 20%. Statistical significance was defined as P < 0.05.
Results: Seven hundred sixty-six pancreatoduodenectomy patients met the study criteria for inclusion in the analysis (non-home, 126; home, 640). Independent predictors of non-home discharge on multivariable analysis were age, marital status, mental health diagnosis, functional health status, dyspnea, and chronic obstructive pulmonary disease. The prediction model was then used to generate a nomogram to predict likelihood of non-home discharge. The training and validation cohorts demonstrated comparable performances with an identical area under the curve (0.81) and an accuracy of 84%.
Conclusion: A prediction model to reliably assess the likelihood of non-home discharge after pancreatoduodenectomy was developed and validated in the present study.
Keywords: Nomogram; Pancreatoduodenectomy; Patient discharge.