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ORIGINAL RESEARCH article

Front. Med.

Sec. Intensive Care Medicine and Anesthesiology

Volume 12 - 2025 | doi: 10.3389/fmed.2025.1582546

Construction and validation of a web-based dynamic predictive model for the risk of postoperative nausea and vomiting in patients undergoing day-case hysteroscopic surgery

Provisionally accepted
Jiang  LiuJiang Liu1Lifang  HanLifang Han2Fengxian  ZhangFengxian Zhang3Yan  JiangYan Jiang4Lin  ChengLin Cheng3Sifan  QinSifan Qin3Shirong  FangShirong Fang4*
  • 1Central South University, Changsha, Hunan Province, China
  • 2Second People’s Hospital of Weifang, Weifang, Shandong Province, China
  • 3Shandong Second Medical University, Weifang, Shandong Province, China
  • 4Weifang People's Hospital, Weifang, Shandong Province, China

The final, formatted version of the article will be published soon.

Objectives: This study aimed to develop and validate a predictive risk model for postoperative nausea and vomiting (PONV) in patients undergoing day-case hysteroscopic surgery.Methods: The candidate predictors were identified by systematic literature review. Patients who met the study criteria were divided into training group and validation group. The time-period validation was used for the external validation of the model. The candidate predictors with statistical significance through lasso regression analyses were included in multifactor logistic regression analyses. The calibration and receiver operating characteristic (ROC) curves were utilized to assess the accuracy of model. Decision curve analysis (DCA) was used to assess the clinical benefit of Nomogram. All statistical analyses were constructed by RStudio software (version 4.2.1). Results: A total of five predictors were included in the PONV risk prediction model: 1) motion sickness (OR, 8.53; 95% CI, 6.21-11.81), 2) anesthesia time (OR, 4.20; 95% CI, 2.09-8.65), 3) fasting time (OR, 1.17; 95% CI, 1.13-1.22), 4) anxiety score (OR, 1.10; 95% CI, 1.08-1.12) and 5) artificial airway (OR, 0.54; 95% CI, 0.39-0.74). The area under the ROC curve for the training cohort and validation cohort was 85.0% (95% CI: 82.6%-87.5%) and 80.3% (76.2%-84.3%), respectively.Conclusion: The predictive model demonstrated potential in predicting the risk of PONV in patients undergoing day-case hysteroscopic surgery.

Keywords: Postoperative Nausea and Vomiting, PONV, Day-case hysteroscopic surgery, predictive model, risk score

Received: 03 Apr 2025; Accepted: 12 Jun 2025.

Copyright: © 2025 Liu, Han, Zhang, Jiang, Cheng, Qin and Fang. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

* Correspondence: Shirong Fang, Weifang People's Hospital, Weifang, 261000, Shandong Province, China

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