Zhu Yabin, Jiang Lin, Sun Canlin, Li Yunxiang, Xie Hong
Department of anesthesiology, The Second Affiliated Hospital of Soochow University, Suzhou, Jiangsu Province, China.
Department of Anesthesiology, The Affiliated Taizhou People's Hospital of Nanjing Medical University, Taizhou School of Clinical Medicine, Nanjing Medical University, Taizhou, Jiangsu Province, China.
Clin Ther. 2025 Feb;47(2):143-147. doi: 10.1016/j.clinthera.2024.11.018. Epub 2024 Dec 6.
Postoperative nausea and vomiting (PONV) is among the most common adverse events, accompanied with impaired prognosis. This study aimed to investigate independent predictors for PONV after laparoscopic surgery for gynecologic cancers and identify a nomogram model.
Elderly patients who underwent laparoscopic surgery for gynecologic cancers between 2021 and 2024 were retrospectively enrolled. The primary observational endpoint was set as the occurrence of PONV within 72 h after surgery. Independent risk factors associated with PONV were identified by binary logistic regression, and further incorporated into the nomogram prediction mode by R.
Of 337 enrolled patients, 104 experienced PONV with an overall incidence of 30.9%. Multivariate logistic regression analysis indicated body mass index (BMI) ≥ 24.0 (OR: 2.67, 95% CI: 1.37-5.23, P = 0.004), Afpel score (OR: 6.54, 95% CI: 3.52-12.15, P < 0.001), anxiety (OR: 3.14, 95% CI: 1.16-8.50, P = 0.025), 5-hydroxytryptamine (5-HT) (OR: 1.05, 95% CI: 1.02-1.07, P < 0.001), prostaglandin E2 (PGE2) (OR: 1.05, 95% CI: 1.01-1.08, P = 0.007), and albumin/fibrinogen ratio (AFR) (OR: 0.40, 95% CI: 0.28-0.56, P < 0.001) were six independent risk factors for PONV. The nomogram model based on these factors has good predictive value for PONV, with an AUC of 0.898.
This study identified an individual nomogram prediction model to visually represent the regression model for predicting PONV after laparoscopic surgery for gynecologic cancers.
