Abstract:
Objective
To study the risk prediction model for respiratory failure in patients with chronic obstructive pulmonary disease （COPD）.
Methods
Relevant literature on risk prediction models for respiratory failure in COPD patients published from the establishment of the databases to September 2024 was retrieved from CNKI，Wanfang Data Knowledge Service Platform，VIP Database，China Biomedical Database，PubMed，Cochrane Library，EMbase，and Web of Science.Meta-analysis was conducted on the predictive value of common predictors in the included models using Revman 5.3 software.
Results
A total of 5 articles were included，with a sample size ranging from 177 to 25，638 cases，and the number of outcome events ranging from 44 to 3，844 cases.The number of potential predictors ranged from 14 to 42.The top six common predictors among the models were serum albumin level，force expiratory volume in 1 second（FEV1），the number of annual acute exacerbation of chronic obstructive pulmonary disease（AECOPD） episodes，white blood cell count，C-reactive protein，and the duration of COPD.A total of 29，316 COPD patients were included，among whom 4，084 （13.93%） developed respiratory failure.Five risk prediction models were included，and the area under the curve （AUC） of all models ranged from 0.645 to 0.950，with four models having an AUC≥0.8.The prediction model risk of bias assessment tool （PROBAST） results showed that all five included articles had a high risk of bias，mainly due to the lack of reporting on the handling of missing data and incomplete model performance evaluation.Meta-analysis results indicated that white blood cell count （OR ＝1.97，95%CI： 1.33-2.92） was a predictor of respiratory failure in COPD patients.
Conclusion
The existing risk prediction models for respiratory failure in COPD patients have a high risk of bias.Future studies should follow the PROBAST guidelines to improve research design，develop，update，and validate such models，and further verify their applicability and safety in clinical practice.
Key words:
Acute exacerbation of chronic obstructive pulmonary disease,
Respiratory failure,
Risk prediction
Xin Liu, Xueping Liu, Yuding Jiao, Maoling Ren, Yongqin He. Meta-analysis of risk prediction models for patients with chronic obstructive pulmonary disease complicated with respiratory failure[J]. Chinese Journal of Lung Diseases(Electronic Edition), 2025, 18(01): 110-114.