Development and temporal validation of a clinical nomogram to predict delayed discharge after bariatric surgery

Enhanced recovery after surgery (ERAS) pathways have reduced hospital stays after bariatric surgery, yet a subset of patients still require prolonged hospitalization. We aimed to identify predictors of delayed discharge and develop a validated clinical nomogram to estimate the likelihood of > 1 day postoperative stay.

We performed a retrospective cohort study of consecutive adults undergoing primary or revisional minimally invasive sleeve gastrectomy or Roux-en-Y gastric bypass at a single military treatment facility from 01/01/2022 to 12/31/2024. Demographic, comorbidity, operative, and perioperative data were abstracted. The 2023 cohort served as the development set for univariable and multivariable logistic regression to identify predictors of delayed discharge (> 1 day). A clinical nomogram was constructed from independent predictors and internally validated via bootstrap resampling (200 iterations). Temporal validation was performed on 2022 and 2024 cohorts.

Among 281 patients (mean age 47.2 ± 11.3 years; mean BMI 40.5 ± 6.0 kg/m²; 26.7% male), 141 (50.2%) experienced delayed discharge. Independent predictors included operative time > 150 min (OR 3.00, 95% CI 1.14-8.09), overnight hydromorphone use (OR 3.78, 95% CI 1.40-11.0), ≥ 1 overnight antiemetic dose (OR 2.55, 95% CI 1.04-6.27), postoperative day (POD) 0 oral intake < 200 mL (OR 2.43, 95% CI 1.01-6.01), and POD 1 hemoglobin decrease ≥ 2 g/dL (OR 4.16, 95% CI 1.25-15.3). The final five-variable model demonstrated strong discrimination (AUC 0.77; bias-corrected C-index 0.74) and calibration (Hosmer-Lemeshow p = 0.17). Temporal validation confirmed robust performance (AUC 0.77-0.87). In sensitivity analysis, model discrimination remained high for both primary (AUC 0.79) and revisional cases (AUC 0.88). A web-based Shiny risk calculator was developed for bedside use ( https://michaeltolson.shinyapps.io/bariatric-delayed-discharge-2023/ ).

A five-variable nomogram accurately predicts delayed discharge following bariatric surgery and demonstrated strong temporal validation. This tool may aid individualized discharge planning.