Influencing factors and predictive model construction of recurrence within one year after discontinuation of medication in children with cough variant asthma after regular treatment

QIU Ye; YANG Xiaoqian; CAO Yachuan; CUI Ying

doi:10.7619/jcmp.20232424

Journal of Clinical Medicine in Practice > 2023 > 27(24): 42-47. > DOI: 10.7619/jcmp.20232424

QIU Ye, YANG Xiaoqian, CAO Yachuan, CUI Ying. Influencing factors and predictive model construction of recurrence within one year after discontinuation of medication in children with cough variant asthma after regular treatment[J]. Journal of Clinical Medicine in Practice, 2023, 27(24): 42-47. DOI: 10.7619/jcmp.20232424

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Influencing factors and predictive model construction of recurrence within one year after discontinuation of medication in children with cough variant asthma after regular treatment

1.
Department of Pediatrics, the First Hospital Affiliated to Suzhou University, Suzhou, Jiangsu, 215006
2.
Department of Pediatrics, the Fourth People's Hospital of Wuxi in Jiangsu Province, Wuxi, Jiangsu, 214062

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Received Date: July 30, 2023
Revised Date: October 07, 2023
Available Online: January 04, 2024

Graphical Abstract

Abstract

Abstract

Objective
To analyze the influencing factors of recurrence within one year after discontinuation of regular treatment of children's cough variant asthma (CVA) and to construct a predictive model, in order to provide guidance for doctors to evaluate the risk of recurrence after CVA treatment in children and develop prevention strategies.
Methods
A total of 215 children with CVA were selected as the study objects. According to whether recurrence occurred within one year after discontinuation of regular treatment, the patients were divided into recurrence group (n=89) and non-recurrence group (n=126). Data of two groups were collected for univariate and multivariate Logistic regression analysis to screen out the influencing factors of recurrence in children with CVA. The GBM prediction model was constructed by using R software to run the gradient boosting model (GBM) algorithm. Receiver operating characteristic (ROC) curve was used to analyze and compare the predictive efficiency of GBM model and Logistic regression model.
Results
The recurrence rate of 215 children with CVA within one year after regular treatment was 41.40%(89/215). Allergy history (OR=2.870, 95%CI, 1.442 to 5.714), repeated respiratory infection history (OR=4.132, 95%CI, 2.045 to 8.348), parents' cognitive level of CVA prevention and control (OR=1.063, 95%CI, 1.011 to 1.118), eosinophils (OR=0.801, 95%CI, 0.674 to 0.952), forced expiratory flow at 50% of vital capacity (FEF₅₀) (OR=1.055, 95%CI, 1.012 to 1.099), maximal midexpiratory flow rate 75/25 (MMEF_75/25) (OR=1.054, 95%CI, 1.009 to 1.102), and fractional exhaled nitric oxide (FeNO) (OR=0.883, 95%CI, 0.834 to 0.935) were influencing factors for recurrence within one year after regular treatment of children's CVA (P < 0.05). According to ROC curve analysis, the area under the curve of GBM model was 0.872, which was larger than 0.827 of Logistic regression model.
Conclusion
GBM prediction model is established based on the influencing factors of recurrence within one year after regular treatment of CVA in children, which can be used as a reference for clinical measures to prevent recurrence in children after treatment of CVA.
- children,
- cough variant asthma,
- recurrence,
- influential factors,
- prediction model

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References (25)

References

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Influencing factors and predictive model construction of recurrence within one year after discontinuation of medication in children with cough variant asthma after regular treatment