ArticleWorld journal of surgical oncology2023
Construction of pain prediction model for patients undergoing hepatic arterial chemoembolization.
Article in World journal of surgical oncology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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2 citing papers in PubMed, 3 citations in OpenAlex.
- Novel multimodal analgesic regimen for perioperative pain management after hepatic artery infusion chemotherapy in patients with advanced hepatocellular carcinoma.World journal of gastrointestinal surgery · 2025Trial
- Gastrointestinal side effects in hepatocellular carcinoma patients receiving transarterial chemoembolization: a meta-analysis of 81 studies and 9495 patients.Therapeutic advances in medical oncology · 2025Article
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5 authors at 1 institution in 1 country.
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Abstract
objectiveTo construct a predictive model for pain in patients undergoing hepatic arterial chemoembolization (TACE) in interventional operating room.
methodsThrough literature review and expert interviews, a questionnaire was prepared for the assessment of pain factors in patients with hepatic arterial chemoembolization. A prospective cohort study was used to select 228 patients with hepatic arterial chemoembolization in a tertiary and first-class hospital. The data of the patients in the pain group and the non-pain group were compared, and a rapid screening prediction model was constructed by univariate analysis and logistic regression analysis, and its prediction effect was tested.
resultsTumor size, liver cancer stage, and chemoembolization with drug-loaded microspheres and pirarubicin hydrochloride (THP) mixed with lipiodol were independent predictors of pain in patients after hepatic arterial chemoembolization. Finally, the pain prediction model after TACE was obtained. The results of Hosmer-Lemeshow test showed that the model fit was good (χ
conclusionThe rapid screening and prediction model of pain in patients undergoing hepatic arterial chemoembolization has certain efficacy, which is helpful for clinical screening of patients with high risk of pain, and can provide reference for predictive pain management decision-making.
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