慢性阻塞性肺疾病急性发作患者院内病情加重风险列线图预测模型的构建

doi:10.3969/j.issn.1006-5253.2020.05.006

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Abstract Objective To construct a prediction model for the risk of exacerbation of inpatients with acute exacerbation of chronic obstructive pulmonary disease (AECOPD). Methods A retrospective observational cohort study was carried out on the patients with AECOPD in the department of respiratory medicine of a hospital from January 2015 to December 2018. The general clinical data of the patients at admission and the peripheral blood related indexes such as leukocyte count (WBC), C-reactive protein (CRP), red blood cell distribution width (RDW), procalcitonin (PCT) were collected, and the exacerbation of patients in hospital was recorded. SPSS 25.0 and R 3.6.1 software were applied for statistical analysis to construct the prediction model of nomograph and evaluate it. Results We collected 419 AECOPD inpatients who met the inclusion criteria, 43 patients exacerbated in hospital and 376 patients did not. LASSO regression was used to screen out WBC, CRP, RDW, and PCT as the risk factors of exacerbation in hospital of AECOPD patients. Logistic regression analysis showed that elevated WBC, elevated CRP, elevated RDW and elevated PCT were all independent risk factors affecting the exacerbation in hospital of AECOPD patients. According to the variables selected by logistic regression model, the prediction model of nomograph was established. The C-index was 0.887, and the distinguishing ability of the model was good. The AUC calculated by ROC curve was 0.887, and the accuracy of the model was good. The evaluation of calibration curve and decision curve showed that the consistency and benefit of the model were still available. Conclusion WBC elevation, CRP elevation, RDW elevation and PCT elevation are the risk factors for the exacerbation in hospital of AECOPD patients. The prediction model based on these four indexes is accurate and has certain reference value for the rapid and simple risk analysis in clinical work. It could be further verified by the data of multi-center and larger samples.

Key words： acute exacerbation of chronic obstructive pulmonary disease exacerbation in hospital nomograph prediction model red blood cell distribution width

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Wang Xiuqing. Construction of prediction model for the risk of exacerbation of inpatients with acute exacerbation of chronic obstructive pulmonary disease#br#[J]. journal1, 2020, 27(5): 408-412.

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http://manu58.magtech.com.cn/Jwk_zgyytj/EN/10.3969/j.issn.1006-5253.2020.05.006 OR http://manu58.magtech.com.cn/Jwk_zgyytj/EN/Y2020/V27/I5/408

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