Copyright: ©Author(s) 2026. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution-NonCommercial (CC BY-NC 4.0) license. No commercial re-use. See permissions. Published by Baishideng Publishing Group Inc.
World J Gastroenterol. Jun 28, 2026; 32(24): 116003
Published online Jun 28, 2026. doi: 10.3748/wjg.v32.i24.116003
Published online Jun 28, 2026. doi: 10.3748/wjg.v32.i24.116003
Assessment of the value of complication risk prediction models following interventional therapy for hepatocellular carcinoma in nursing decision-making
Hui Wang, Hao-Tian Guo, Jing Shen, Fei Zhang, Yue-Jiao Jiang, Zhen-Xing Liu, Department of Oncology and Vascular Interventional Therapy, Shanxi Provincial People’s Hospital, Taiyuan 030012, Shanxi Province, China
Author contributions: Wang H, Guo HT, and Shen J designed the research study, analyzed the data and wrote the manuscript; Zhang F, Jiang YJ and Liu ZX contributed new reagents and analytic tools; Wang H, Guo HT, Shen J, Zhang F, Jiang YJ and Liu ZX performed the research; all authors have read and approve the final manuscript.
AI contribution statement: This study utilized DeepL for language polishing. Neither the entirety nor any portion of the main text of the manuscript (Abstract, Introduction, Materials and Methods, Results, Discussion, and Conclusion) was generated by AI tools.
Institutional review board statement: The research was reviewed and approved by Shanxi Provincial People’s Hospital, No. 2024-730.
Informed consent statement: All participants provided informed consent.
Conflict-of-interest statement: All authors declare no conflict of interest in publishing the manuscript.
Data sharing statement: No other data available.
Corresponding author: Hui Wang, Chief Nurse, Department of Oncology and Vascular Interventional Therapy, Shanxi Provincial People’s Hospital, No. 29 Shuangta Temple Street, Taiyuan 030012, Shanxi Province, China. 13803435846@163.com
Received: January 13, 2026
Revised: February 5, 2026
Accepted: March 23, 2026
Published online: June 28, 2026
Processing time: 145 Days and 2.1 Hours
Revised: February 5, 2026
Accepted: March 23, 2026
Published online: June 28, 2026
Processing time: 145 Days and 2.1 Hours
Core Tip
Core Tip: This study developed and validated a multidimensional integrated model for predicting the risk of complications following transcatheter arterial chemoembolization in patients with hepatocellular carcinoma. By innovatively incorporating clinical characteristics and procedural parameters with nursing-specific indicators including psychological status, nutrition, and self-care capacity, the model achieved high predictive accuracy (area under the curve = 0.936). The model offers nurses a logical and user-friendly decision-support model that helps them to predict complications early and accurately distribute nursing resources.