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Construction of pain prediction model for patients undergoing hepatic arterial chemoembolization

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 ar...

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Autores principales: Song, Ping-Wei, Liu, Ye-Hui, Wang, Tao, Yu, Lei, Liu, Jing-Li
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10026457/
https://www.ncbi.nlm.nih.gov/pubmed/36941629
http://dx.doi.org/10.1186/s12957-023-02986-y
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author Song, Ping-Wei
Liu, Ye-Hui
Wang, Tao
Yu, Lei
Liu, Jing-Li
author_facet Song, Ping-Wei
Liu, Ye-Hui
Wang, Tao
Yu, Lei
Liu, Jing-Li
author_sort Song, Ping-Wei
collection PubMed
description 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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spelling pubmed-100264572023-03-21 Construction of pain prediction model for patients undergoing hepatic arterial chemoembolization Song, Ping-Wei Liu, Ye-Hui Wang, Tao Yu, Lei Liu, Jing-Li World J Surg Oncol Research 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. BioMed Central 2023-03-20 /pmc/articles/PMC10026457/ /pubmed/36941629 http://dx.doi.org/10.1186/s12957-023-02986-y Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research
Song, Ping-Wei
Liu, Ye-Hui
Wang, Tao
Yu, Lei
Liu, Jing-Li
Construction of pain prediction model for patients undergoing hepatic arterial chemoembolization
title Construction of pain prediction model for patients undergoing hepatic arterial chemoembolization
title_full Construction of pain prediction model for patients undergoing hepatic arterial chemoembolization
title_fullStr Construction of pain prediction model for patients undergoing hepatic arterial chemoembolization
title_full_unstemmed Construction of pain prediction model for patients undergoing hepatic arterial chemoembolization
title_short Construction of pain prediction model for patients undergoing hepatic arterial chemoembolization
title_sort construction of pain prediction model for patients undergoing hepatic arterial chemoembolization
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10026457/
https://www.ncbi.nlm.nih.gov/pubmed/36941629
http://dx.doi.org/10.1186/s12957-023-02986-y
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