ArticlePloS one2024
Machine learning-based identification of the risk factors for postoperative nausea and vomiting in adults.
Article in PloS one, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
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Who cites it
15 citing papers in PubMed.
- Effects of Glycopyrronium Bromide as an Adjuvant Treatment in the Prevention of Nausea and Vomiting After Abdominal, Thyroid, and Breast Surgery: A Multicenter Randomized Controlled Trial.Drug design, development and therapy · 2025Trial
- 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
- Article
- Machine Learning-Based Prediction of Early Patient-Controlled Analgesia Discontinuation After Total Knee Arthroplasty: A Retrospective Cohort Study.Journal of clinical medicine · 2026Article
- Article
- Assessment of Pain Intensity Using Deep Learning Models in Non-Communicative Intensive Care Patients.Nursing in critical care · 2026Article
- DSPONVNet: a multimodal deep learning model integrating intraoperative monitoring and clinical features for predicting postoperative nausea and vomiting risk.BMC medical research methodology · 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
- Laparoscopic Reversal of Roux-en-Y Gastric Bypass for Isolated Refractory Postoperative Nausea: A Case Report.Cureus · 2026Article
- Article
- Observational
- Effects of Transcutaneous Electrical Acupoint Stimulation on Recovery After Gynecological Laparoscopic Surgery: A Randomized, Single-Blind, Controlled Trial.Journal of pain research · 2025Article
- Artificial intelligence revolutionizing anesthesia management: advances and prospects in intelligent anesthesia technology.Frontiers in medicine · 2025Review
- Article
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Postoperative nausea and vomiting (PONV) is a common adverse effect of anesthesia. Identifying risk factors for PONV is crucial because it is associated with a longer stay in the post-anesthesia care unit, readmissions, and perioperative costs. This retrospective study used artificial intelligence to analyze data of 37,548 adult patients (aged ≥20 years) who underwent surgery under general anesthesia at Tohoku University Hospital from January 1, 2010 to December 31, 2019. To evaluate PONV, patients who experienced nausea and/or vomiting or used antiemetics within 24 hours after surgery were extracted from postoperative medical and nursing records. We create a model that predicts probability of PONV using the gradient tree boosting model, which is a widely used machine learning algorithm in many applications due to its efficiency and accuracy. The model implementation used the LightGBM framework. Data were available for 33,676 patients. Total blood loss was identified as the strongest contributor to PONV, followed by sex, total infusion volume, and patient's age. Other identified risk factors were duration of surgery (60-400 min), no blood transfusion, use of desflurane for maintenance of anesthesia, laparoscopic surgery, lateral positioning during surgery, propofol not used for maintenance of anesthesia, and epidural anesthesia at the lumbar level. The duration of anesthesia and the use of either sevoflurane or fentanyl were not identified as risk factors for PONV. We used artificial intelligence to evaluate the extent to which risk factors for PONV contribute to the development of PONV. Intraoperative total blood loss was identified as the potential risk factor most strongly associated with PONV, although it may correlate with duration of surgery, and insufficient circulating blood volume. The use of sevoflurane and fentanyl and the anesthesia time were not identified as risk factors for PONV in this study.
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