重度支气管哮喘并发肺部感染的危险因素及其预测模型构建

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Abstract Objective To investigate the risk factors of pulmonary infection in patients with severe bronchial asthma and to construct a nomogram prediction model. Methods One hundred and seventy-six patients with severe bronchial asthma treated in the 908th Hospital of the Chinese PLA Joint Logistics Support Force from January 2019 to October 2021 were selected and divided into infected group (n=54) and uninfected group (n=122) according to whether they had concomitant lung infection. The clinical data of the two groups were collected, and the factors related to pulmonary infection were analyzed; the predictive value of indicators was inferred from ROC curves; independent risk factors were analyzed by logistic regression; the predictive model of column line graph was constructed by R language software 4.0 “rms” package, and the calibration and decision curves were internally validated and the predictive efficacy was evaluated. Results The differences between the two groups were statistically significant (P<0.05) in terms of age, history of diabetes, duration of disease, duration of antibiotic use, duration of glucocorticoid use, mechanical ventilation, duration of mechanical ventilation, and hypoproteinemia. The AUCs for age, duration of illness, duration of antibiotic use, duration of glucocorticoid use, and duration of mechanical ventilation were 0.795, 0.714, 0.799, 0.828, and 0.830, respectively, with optimal cutoff values of 60 years, 4 years, 11 days, 8 days, and 6 days, respectively. Age, history of diabetes, duration of antibiotic use, duration of glucocorticoid use, mechanical ventilation, and hypoproteinemia were independent risk factors for pulmonary infections complicated with severe bronchial asthma. The column line graph model predicted a C-index of 0.876 (95% CI: 0.735-0.962) with a threshold >0.18 for concurrent pulmonary infections in patients with severe bronchial asthma, and the column line graph model provided a net clinical benefit, and all net clinical benefits were higher than the independent predictors. Conclusions The prediction and nomogram model based on age, diabetes history, duration of antibiotic use, duration of glucocorticoid use, mechanical ventilation and hypoalbuminemia can be of great significance for the prediction and early intervention of patients with severe clinical bronchial asthma complicated by pulmonary infection.

Key words： severe bronchial asthma lung infection independent risk factors column chart prediction model

Received: 13 September 2022

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	Articles by authors
	LAN Jing
	RUAN Chunhua
	QU Zhengyu
	XIA Guoji

Cite this article:

LAN Jing,RUAN Chunhua,QU Zhengyu等. Risk factors of severe bronchial asthma complicated with pulmonary infection and construction of prediction model[J]. Med. J. Chin. Peop. Armed Poli. Forc., 2023, 34(4): 310-314.

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http://journal08.magtechjournal.com/Jwk_wjyx/EN/ OR http://journal08.magtechjournal.com/Jwk_wjyx/EN/Y2023/V34/I4/310

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