ArticleBMC anesthesiology2023
Risk estimation for postoperative nausea and vomiting: development and validation of a nomogram based on point-of-care gastric ultrasound.
Article in BMC anesthesiology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 1 of them a synthesis that pooled it.
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Who cites it
6 citing papers in PubMed, 1 synthesis or guideline pooled it, 6 citations in OpenAlex.
- The Efficacy of Aprepitant in Preventing Post-bariatric Surgery Nausea and Vomiting: Evidence from Clinical Trials.Obesity surgery · 2024Pooled it
- A dynamic nomogram for predicting postoperative nausea and vomiting after laparoscopic surgery: a prospective study.BMC anesthesiology · 2026Article
- Construction and Validation of a Risk Prediction Model for Postoperative Nausea and Vomiting in Patients with Liver Cancer.Journal of hepatocellular carcinoma · 2026Article
- Constructing a nomogram model for patients with cervical spondylotic myelopathy.Scientific reports · 2025Article
- Construction and validation of an ultrasound-based nomogram model for predicting dysphagia in patients with chronic obstructive pulmonary disease.Frontiers in medicine · 2025Article
- Association of tongue diagnosis-guided acupuncture with postoperative nausea and vomiting in high-risk laparoscopic surgery patients.American journal of translational research · 2025Article
Corrections and comments
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Authors and funding
10 authors at 3 institutions in 2 countries.
Funding
Abstract
backgroundWe aimed to develop a nomogram that can be combined with point-of-care gastric ultrasound and utilised to predict postoperative nausea and vomiting (PONV) in adult patients after emergency surgery.
methodsImaging and clinical data of 236 adult patients undergoing emergency surgery in a university hospital between April 2022 and February 2023 were prospectively collected. Patients were divided into a training cohort (n = 177) and a verification cohort (n = 59) in a ratio of 3:1, according to a random number table. After univariate analysis and multivariate logistic regression analysis of the training cohort, independent risk factors for PONV were screened to develop the nomogram model. The receiver operating characteristic curve, calibration curve, decision curve analysis (DCA) and clinical impact curve (CIC) were used to evaluate the prediction efficiency, accuracy, and clinical practicability of the model.
resultsUnivariate analysis and multivariate logistic regression analysis showed that female sex, history of PONV, history of migraine and gastric cross-sectional area were independent risk factors for PONV. These four independent risk factors were utilised to construct the nomogram model, which achieved significant concordance indices of 0.832 (95% confidence interval [CI], 0.771-0.893) and 0.827 (95% CI, 0.722-0.932) for predicting PONV in the training and validation cohorts, respectively. The nomogram also had well-fitted calibration curves. DCA and CIC indicated that the nomogram had great clinical practicability.
conclusionsThis study demonstrated the prediction efficacy, differentiation, and clinical practicability of a nomogram for predicting PONV. This nomogram may serve as an intuitive and visual guide for rapid risk assessment in patients with PONV before emergency surgery.
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