Evidence map›Paper›PMID 42609430›Full record

ArticleJournal of hepatocellular carcinoma2026

Construction and Validation of a Risk Prediction Model for Postoperative Nausea and Vomiting in Patients with Liver Cancer.

Dandan Geng, Jun Wang, Yan Zhu, Jin Gao, Yuxia Zhang, Xiao Chen, Jingxian Yu

Abstract read
In one paragraph

Article in Journal of hepatocellular carcinoma, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

7 authors.

Dandan Geng *Department of Nursing, Zhongshan Hospital, Fudan University, Shanghai, 200032, People's Republic of China.ORCID 0000-0002-2036-8967
Jun Wang *Department of Nursing, Fudan University Shanghai Cancer Center, Shanghai Medical College, Fudan University, Shanghai, 200032, People's Republic of China.ORCID 0009-0009-8666-6711
Yan ZhuDepartment of Nursing, Zhongshan Hospital, Fudan University, Shanghai, 200032, People's Republic of China.
Jin GaoDepartment of Nursing, Zhongshan Hospital, Fudan University, Shanghai, 200032, People's Republic of China.
Yuxia ZhangDepartment of Nursing, Zhongshan Hospital, Fudan University, Shanghai, 200032, People's Republic of China.
Xiao ChenDepartment of Nursing, Zhongshan Hospital, Fudan University, Shanghai, 200032, People's Republic of China.
Jingxian YuDepartment of Nursing, Zhongshan Hospital, Fudan University, Shanghai, 200032, People's Republic of China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Postoperative nausea and vomiting (PONV) is a common and distressing complication following liver cancer surgery. This study aimed to develop and validate a risk prediction model for PONV in patients undergoing hepatectomy for hepatocellular carcinoma. Methods: This prospective study enrolled patients who underwent liver resection between February 2024 and December 2024. Based on risk factors identified through univariate and binary logistic regression analyses, a nomogram prediction model was constructed. The model's discrimination was evaluated using the area under the receiver operating characteristic curve (AUC-ROC) and the consistency index (C-index). Calibration was assessed with calibration curves, and internal validation was performed via the bootstrap method. Results: A total of 512 patients were included in the modeling cohort. The incidence of PONV was 47.5%. Significant predictors incorporated into the nomogram included age, gender, duration of surgery (min), time of hepatic portal vein occlusion during operation (min), and history of PONV. The model demonstrated an AUC of 0.717 (95% CI: 0.673-0.761), with a sensitivity of 69.9% and a specificity of 62.0% at the optimal cut-off value of 0.413. Bootstrap internal validation yielded a C-index of 0.717, and the calibration curve indicated good agreement between predicted and observed outcomes. Conclusion: The developed risk warning model shows an acceptable predictive effect in identifying the risk of PONV in patients with liver cancer. It can assist clinical medical staff in early risk assessment and individualized intervention, and has certain predictive value.

Indexed as

liver cancerpostoperative nausea and vomitingpredictive modelrisk factors

Identifiers

PMID42609430
PMCPMC13478232

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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.