Predicting opioid consumption after surgical discharge: a multinational derivation and validation study using a foundation model.
Publication/Presentation Date
8-26-2025
Abstract
Opioids are frequently overprescribed after surgery. We applied a tabular foundation model to predict the risk of post-discharge opioid consumption. The model was trained and internally validated on an 80:20 training/test split of the 'Opioid PrEscRiptions and usage After Surgery' (ACTRN12621001451897p) study cohort, including adult patients undergoing general, orthopaedic, gynaecological and urological operations (n = 4267), with external validation in a distinct cohort of patients discharged after general surgical procedures (n = 826). The area under the receiver operator curve was 0.84 (95% confidence interval [CI] 0.81-0.88) at internal testing and 0.77 (95% CI 0.74-0.80) at external validation. Brier scores were 0.13 (95% CI 0.12-0.14) and 0.19 (95% CI 0.17-0.2). Patients with a < 50% predicted risk of opioid consumption consumed a median of 0 oral morphine equivalents in the first week after surgery. Applying this model would reduce opioid prescriptions by 4.5% globally, and counterfactual modelling suggests without increasing time in severe pain (-4.3%, 95% CI -17.7 to 8.6).
Volume
8
Issue
1
First Page
547
Last Page
547
ISSN
2398-6352
Published In/Presented At
Varghese, C., Peters, L., Gaborit, L., Xu, W., Kalyanasundaram, K., Basam, A., Park, M., Wells, C., McLean, K. A., Schamberg, G., O'Grady, G., Wright, D., Martin, J., Harrison, E., Pockney, P., & TASMAN Collaborative (2025). Predicting opioid consumption after surgical discharge: a multinational derivation and validation study using a foundation model. NPJ digital medicine, 8(1), 547. https://doi.org/10.1038/s41746-025-01798-6
Disciplines
Medicine and Health Sciences
PubMedID
40858986
Department(s)
Department of Surgery, Department of Surgery Faculty, Department of Surgery Residents, Fellows and Residents
Document Type
Article