ArticleBioengineering (Basel, Switzerland)2023
Postoperative Nausea and Vomiting Prediction: Machine Learning Insights from a Comprehensive Analysis of Perioperative Data.
Article in Bioengineering (Basel, Switzerland), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to 2 registered trials, which are not on this map. Cited by 10 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Effect of Oliceridine Analgesia on Postoperative Nause and Vomiting in Laparoscopic Colorectal Surgery: A Randomized Trial
Risk Factors Analysis for Clinical Important Postoperative Nausea and Vomiting in Patients Undergoing Laparoscopic Gastrointestinal Surgery Based on LASSO and Stepwise Regression
Who cites it
10 citing papers in PubMed, 9 citations in OpenAlex.
- Review
- Prediction of Postoperative Vomiting Within 24 Hours Using Machine Learning With Large Language Model-Enhanced Interpretability: Development and Validation Study.JMIR medical informatics · 2026Article
- Machine Learning-Based Prediction of Early Patient-Controlled Analgesia Discontinuation After Total Knee Arthroplasty: A Retrospective Cohort Study.Journal of clinical medicine · 2026Article
- Interpretable machine learning for postoperative nausea and vomiting prediction in elderly orthopedic patients: a comparative study.BMC medical informatics and decision making · 2026Article
- Application of machine learning for the prediction of post-operative nausea and vomiting in adult surgical patients - A systematic review.Indian journal of anaesthesia · 2026Article
- A dynamic nomogram for predicting postoperative nausea and vomiting after laparoscopic surgery: a prospective study.BMC anesthesiology · 2026Article
- Explainable Machine Learning for Prediction of Early Postoperative Nausea and Vomiting After General Anesthesia.Journal of multidisciplinary healthcare · 2026Article
- Development and prospective evaluation of a machine learning model to predict vomiting among pediatric cancer and hematopoietic cell transplant patients.BMC cancer · 2025Article
- Article
- Factors associated with acute clinically important postoperative nausea and vomiting in high-risk patients undergoing laparoscopic gastrointestinal surgery: a secondary analysis of the FDP-PONV trial.Frontiers in medicine · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors at 1 institution in 1 country.
Funding
Abstract
Postoperative nausea and vomiting (PONV) are common complications after surgery. This study aimed to present the utilization of machine learning for predicting PONV and provide insights based on a large amount of data. This retrospective study included data on perioperative features of patients, such as patient characteristics and perioperative factors, from two hospitals. Logistic regression algorithms, random forest, light-gradient boosting machines, and multilayer perceptrons were used as machine learning algorithms to develop the models. The dataset of this study included 106,860 adult patients, with an overall incidence rate of 14.4% for PONV. The area under the receiver operating characteristic curve (AUROC) of the models was 0.60-0.67. In the prediction models that included only the known risk and mitigating factors of PONV, the AUROC of the models was 0.54-0.69. Some features were found to be associated with patient-controlled analgesia, with opioids being the most important feature in almost all models. In conclusion, machine learning provides valuable insights into PONV prediction, the selection of significant features for prediction, and feature engineering.
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What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.