Construction and evaluation of nomograph model for individualized prediction of recurrent respiratory tract infection risk in children in chengdu

LI Juan; CAI Hehua; WANG Zhiqiang; CHEN Guihua; WU Xiaoyan; LIU Qianyang

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Journal of Hunan Normal University(Medical Science) ›› 2024, Vol. 21 ›› Issue (1) : 52-57.

Construction and evaluation of nomograph model for individualized prediction of recurrent respiratory tract infection risk in children in chengdu

LI Juan¹, CAI Hehua¹, WANG Zhiqiang¹, CHEN Guihua¹, WU Xiaoyan¹, LIU Qianyang²

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Abstract

Objective To construct an individualized nomogram model for predicting the risk of recurrent respiratory tract infections in urban children in Chengdu, and to evaluate the accuracy and clinical applicability of this nomogram model. Methods Children with respiratory tract infections admitted to our hospital recently were selected as the study subjects. The children were divided into two groups: those with recurrent respiratory tract infections and those with ordinary respiratory tract infections.70% of the subjects were randomly selected as the training set, and the remaining 30% were used as the testing set. Logistic regression analysis was conducted on the training set to identify independent risk factors for recurrent respiratory tract infections in Chengdu children. Based on the identified risk factors, a nomogram model was constructed. The calibration curve was drawn after performing 1000 rounds of bootstrap sampling on the training set. Internal validation of the nomogram model was performed using ROC curves and clinical decision curves, and the clinical efficacy of the model was validated on the testing set. Results Logistic regression analysis on the training set revealed the following independent risk factors for recurrent respiratory tract infections in urban children in Chengdu: history of allergies, history of asthma, low levels of vitamin A and vitamin D, low birth weight, passive smoking, and low hemoglobin levels. The C-index of the nomogram model in the training set was 0.879(95% CI 0.812-0.932). The calibration curve showed that the predicted risk of recurrent respiratory tract infections in children using the nomogram model was close to the actual observed curve. The clinical decision curve indicated that the nomogram model was most applicable when the predicted risk of recurrent respiratory tract infections in urban children in Chengdu was between 0.04 and 0.95. The ROC curve showed an AUC of 0.921(95% CI 0.851-0.968), sensitivity of 0.848, and specificity of 0.872 for the model. In the testing set, the ROC curve showed an AUC of 0.912(95% CI 0.871-0.941), sensitivity of 0.845, and specificity of 0.836. Conclusion The constructed individualized nomogram model for predicting the risk of recurrent respiratory tract infections in urban children in Chengdu demonstrates good accuracy and clinical applicability.

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children / recurrent respiratory tract infection / nomogram model / logistic regression model

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LI Juan, CAI Hehua, WANG Zhiqiang, CHEN Guihua, WU Xiaoyan, LIU Qianyang. Construction and evaluation of nomograph model for individualized prediction of recurrent respiratory tract infection risk in children in chengdu[J]. Journal of Hunan Normal University(Medical Science). 2024, 21(1): 52-57

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