World Journal of Surgical Oncology (Mar 2023)

Construction of pain prediction model for patients undergoing hepatic arterial chemoembolization

  • Ping-Wei Song,
  • Ye-Hui Liu,
  • Tao Wang,
  • Lei Yu,
  • Jing-Li Liu

DOI
https://doi.org/10.1186/s12957-023-02986-y
Journal volume & issue
Vol. 21, no. 1
pp. 1 – 8

Abstract

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Abstract Objective To construct a predictive model for pain in patients undergoing hepatic arterial chemoembolization (TACE) in interventional operating room. Methods Through 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. Results Tumor 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 2 = 13.540, p = 0.095). The area under the receiver operating characteristic curve was 0.798, p < 0.001. Conclusion The 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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