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ORIGINAL RESEARCH article

Front. Pediatr.
Sec. Pediatric Pulmonology
Volume 12 - 2024 | doi: 10.3389/fped.2024.1422074
This article is part of the Research Topic Pulmonary infection in children View all 4 articles

Risk Association Model for Atelectasis Complication in Mycoplasma Pneumoniae Pneumonia Patients Following Standardized Treatment

Provisionally accepted
  • 1 The Affiliated Wuxi People's Hospital, Wuxi Children's Hospital of Nanjing Medical University, Wuxi, Liaoning Province, China
  • 2 Affiliated Children's Hospital of Jiangnan University (Wuxi Children's Hospital), Wuxi, Liaoning Province, China
  • 3 Pediatric Respiratory Medicine of Zhumadian Central Hospital, Henan, China
  • 4 Department of Respiratory Medicine, Children’s Hospital of Nanjing Medical University, Nanjing, Jiangsu Province, China

The final, formatted version of the article will be published soon.

    Background: Mycoplasma pneumoniae pneumonia (MPP) is a common disease of childhood pneumonia, and atelectasis is a serious comorbidity. Traditional diagnostic methods for MPP are limited by low accuracy, emphasizing the need for improved diagnostic approaches. This study aimed to establish a predictive scoring model for early detection of MPP complicated with atelectasis following standardized treatment. Methods: A total of 572 children were retrospectively enrolled, including 40 patients with MPP complicated by atelectasis despite standardized treatment and 532 patients in the non-atelectasis group. Clinical, laboratory, and imaging data within 24 hours of admission were collected, including demographic information and various biomarkers. Multivariate logistic regression analysis was employed to identify risk factors and construct a predictive model, evaluated using receiver operating characteristic (ROC) curve analysis. Results: Significant differences were observed between the MPP complicated with atelectasis group and the non-atelectasis group in terms of age, hospital admission time, fever duration, neutrophil percentage and count, CRP, ALT, and LDH levels (P<0.05). According to the multivariate logistic regression analysis, length of fever, neutrophil ratio, platelet count, ALT, LDH, age were incorporated into the nomogram. The predictive model exhibited a sensitivity of 87.97% and specificity of 77.50% according to the ROC curve. Conclusion: Our study presents a preliminary risk association model incorporating clinical indicators such as fever duration, neutrophil ratio, platelet count, ALT value, LDH value, and age to aid in the early prediction of atelectasis in children with MPP. Given the methodological limitations, the generalizability of our findings is constrained, and this model should be viewed as an initial framework for clinical assessment rather than a definitive tool.

    Keywords: Children, M. pneumoniae, M. pneumoniae pneumonia, Atelectasis, Association model

    Received: 23 Apr 2024; Accepted: 12 Nov 2024.

    Copyright: © 2024 Xu, Fan, Wang, Qian, Jiang, Zhu, Zhao, Liu, Guo and Li. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

    * Correspondence:
    Minhao Fan, Affiliated Children's Hospital of Jiangnan University (Wuxi Children's Hospital), Wuxi, Liaoning Province, China
    Jun Qian, Affiliated Children's Hospital of Jiangnan University (Wuxi Children's Hospital), Wuxi, Liaoning Province, China
    Yi Jiang, Affiliated Children's Hospital of Jiangnan University (Wuxi Children's Hospital), Wuxi, Liaoning Province, China
    Yun Guo, Affiliated Children's Hospital of Jiangnan University (Wuxi Children's Hospital), Wuxi, Liaoning Province, China
    Ling Li, The Affiliated Wuxi People's Hospital, Wuxi Children's Hospital of Nanjing Medical University, Wuxi, Liaoning Province, China

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