ArticlePlastic and reconstructive surgery2023
A Personalized Opioid Prescription Model for Predicting Postoperative Discharge Opioid Needs.
Article in Plastic and reconstructive surgery, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed.
- Suzetrigine: What Should Plastic Surgeons Know?Plastic and reconstructive surgery. Global open · 2026Article
- Predicting opioid consumption after surgical discharge: a multinational derivation and validation study using a foundation model.NPJ digital medicine · 2025Article
- Use of Muscle Relaxants for Acute Postoperative Pain: A Practical Review.Plastic and reconstructive surgery. Global open · 2024Review
- Surgeons' knowledge regarding perioperative pain management in patients with opioid use disorder: a survey among 260 members of the American College of Surgeons.Patient safety in surgery · 2024Article
- Methods in regression analysis in surgical oncology research-best practice guidelines.Journal of surgical oncology · 2024Article
- Precision Opioid Prescription in ICU Surgery: Insights from an Interpretable Deep Learning Framework.Journal of surgery (Lisle, IL) · 2024Article
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Authors and funding
8 authors.
Funding
Abstract
backgroundOpioid overprescribing after surgery is common. There is currently no universal predictive tool available to accurately anticipate postdischarge opioid need in a patient-specific manner. This study examined the efficacy of a patient-specific opioid prescribing framework for estimating postdischarge opioid consumption.
methodsA total of 149 patients were evaluated for a single-center retrospective cohort study of plastic and reconstructive surgery patients. Patients with length of stay of 2 to 8 days and quantifiable inpatient opioid consumption (n = 116) were included. Each patient's daily postoperative inpatient opioid consumption was used to generate a personalized logarithmic regression model to estimate postdischarge opioid need. The validity of the personalized opioid prescription (POP) model was tested through comparison with actual postdischarge opioid consumption reported by patients 4 weeks after surgery. The accuracy of the POP model was compared with two other opioid prescribing models.
resultsThe POP model had the strongest association (R2 = 0.899; P < 0.0001) between model output and postdischarge opioid consumption when compared to a procedure-based (R2 = 0.226; P = 0.025) or a 24-hour (R2 = 0.152; P = 0.007) model. Accuracy of the POP model was unaffected by age, gender identity, procedure type, or length of stay. Odds of persistent use at 4 weeks increased, with a postdischarge estimated opioid need at a rate of 1.16 per 37.5 oral morphine equivalents (P = 0.010; 95% CI, 1.04 to 1.30).
conclusionsThe POP model accurately estimates postdischarge opioid consumption and risk of developing persistent use in plastic surgery patients. Use of the POP model in clinical practice may lead to more appropriate and personalized opioid prescribing.
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