Research progress on risk prediction models of postoperative pulmonary complications after lung cancer surgery
- VernacularTitle:肺癌术后肺部并发症风险预测模型的研究进展
- Author:
Ting DENG
1
;
Jiamei SONG
1
;
Jin LI
2
;
Xiaoyan WU
2
;
Lishan WU
2
;
Shaolin CHEN
1
Author Information
1. 1. Nursing Department, Affiliated Hospital of Zunyi Medical University, Zunyi, 563000, Guizhou, P. R. China 2. School of Nursing, Zunyi Medical University, Zunyi, 563000, Guizhou, P. R. China
2. Department of Thoracic Surgery, Affiliated Hospital of Zunyi Medical University, Zunyi, 563000, Guizhou, P. R. China
- Publication Type:Journal Article
- Keywords:
Lung cancer;
postoperative pulmonary complications;
risk prediction models;
review
- From:
Chinese Journal of Clinical Thoracic and Cardiovascular Surgery
2025;32(02):263-269
- CountryChina
- Language:Chinese
-
Abstract:
Risk prediction models for postoperative pulmonary complications (PPCs) can assist healthcare professionals in assessing the likelihood of PPCs occurring after surgery, thereby supporting rapid decision-making. This study evaluated the merits, limitations, and challenges of these models, focusing on model types, construction methods, performance, and clinical applications. The findings indicate that current risk prediction models for PPCs following lung cancer surgery demonstrate a certain level of predictive effectiveness. However, there are notable deficiencies in study design, clinical implementation, and reporting transparency. Future research should prioritize large-scale, prospective, multi-center studies that utilize multiomics approaches to ensure robust data for accurate predictions, ultimately facilitating clinical translation, adoption, and promotion.
