Predictive value of an early comprehensive assessment model for refractory mycoplasma pneumoniae pneumonia and internal validation

Abstract Background Refractory mycoplasma pneumoniae pneumonia (RMPP) can result in severe complications and long-term effects. Early identification of RMPP and appropriate treatments can effectively alleviate complications and restrict the progression of sequelae. There is currently a dearth of a c...

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Main Authors: Xiangtao Wu, Weihong Lu, Weiqing Liu, Yishuai Ren, Shuangshuang Fan, Yali Xu, Ruigui Zhang, Xue Liu, Mengzhu Wang, Tuanjie Wang, Xingliang Zhang, Shaoru He, Shujun Li
Format: Article
Language:English
Published: BMC 2025-05-01
Series:BMC Infectious Diseases
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Online Access:https://doi.org/10.1186/s12879-025-11133-9
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author Xiangtao Wu
Weihong Lu
Weiqing Liu
Yishuai Ren
Shuangshuang Fan
Yali Xu
Ruigui Zhang
Xue Liu
Mengzhu Wang
Tuanjie Wang
Xingliang Zhang
Shaoru He
Shujun Li
author_facet Xiangtao Wu
Weihong Lu
Weiqing Liu
Yishuai Ren
Shuangshuang Fan
Yali Xu
Ruigui Zhang
Xue Liu
Mengzhu Wang
Tuanjie Wang
Xingliang Zhang
Shaoru He
Shujun Li
author_sort Xiangtao Wu
collection DOAJ
description Abstract Background Refractory mycoplasma pneumoniae pneumonia (RMPP) can result in severe complications and long-term effects. Early identification of RMPP and appropriate treatments can effectively alleviate complications and restrict the progression of sequelae. There is currently a dearth of a comprehensive and efficient model for predicting and evaluating RMPP. Methods The development cohort consisted of patients with mycoplasma pneumoniae pneumonia (MPP) who underwent fiberoptic bronchoscopy between January 2019 and October 2021. Multivariable logistic regression analysis was used to identify independent risk factors for RMPP, and a nomogram model was developed that included initial admission examinations and clinical characteristics. The accuracy of the model was validated using a validation cohort of patients enrolled between November 2021 and April 2023. Result 373 patients were enrolled including 229 cases of the development cohort and 144 cases of the validation cohort. Multivariable Logistic regression analysis showed that the six independent risk factors for RMPP were age (OR = 1.151, 95% confidence interval (CI) 1.014–1.306), acute physiology and chronic health evaluation (APACHE) II score(OR = 0.872, 95% CI 0.792–0.961), computed tomography (CT) total score(OR = 1.407, 95% CI 1.258–1.575), secretion color(OR = 2.719, 95% CI 1.562–4.734), mucosal edema(OR = 5.064, 95% CI 2.748-9.300), and procalcitonin (PCT) (OR = 0.871, 95% CI 0.806–0.941). The Area Under Curve (AUC) of the model in the development cohort and validation cohort was 0.913(95%CI 0.875–0.951) and 0.811(95%CI 0.739–0.883), respectively. Hosmer-Lemeshow test showed that the model’s goodness of fit had good consistency in the development cohort and validation cohort (χ2 = 10.546, P = 0.229; χ2 = 7.894, P = 0.342). The DCA of the development and validation cohorts showed clear net benefits using the nomogram to predict RMPP. Conclusion We developed a nomogram model that integrates clinical, imaging, and bronchoscopic features to enable early and accurate prediction of the risk of RMPP in children. This model provides a quantitative tool for personalized intervention and demonstrates significant clinical application value.
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spelling doaj-art-679cb8ae0a16418abe11ba2c575cafc52025-08-20T02:05:45ZengBMCBMC Infectious Diseases1471-23342025-05-0125111210.1186/s12879-025-11133-9Predictive value of an early comprehensive assessment model for refractory mycoplasma pneumoniae pneumonia and internal validationXiangtao Wu0Weihong Lu1Weiqing Liu2Yishuai Ren3Shuangshuang Fan4Yali Xu5Ruigui Zhang6Xue Liu7Mengzhu Wang8Tuanjie Wang9Xingliang Zhang10Shaoru He11Shujun Li12Department of Pediatrics, First Affiliated Hospital of Xinxiang Medical UniversityDepartment of Pediatrics, First Affiliated Hospital of Xinxiang Medical UniversityDepartment of Pediatrics, First Affiliated Hospital of Xinxiang Medical UniversityDepartment of Pediatrics, First Affiliated Hospital of Xinxiang Medical UniversityDepartment of Pediatrics, First Affiliated Hospital of Xinxiang Medical UniversityDepartment of Pediatrics, First Affiliated Hospital of Xinxiang Medical UniversityDepartment of Neonatology, Guangdong Provincial People′s Hospital(Guangdong Academy of Medical Sciences), Southern Medical UniversityDepartment of Pediatrics, First Affiliated Hospital of Xinxiang Medical UniversityDepartment of Pediatrics, First Affiliated Hospital of Xinxiang Medical UniversityDepartment of Pediatrics, First Affiliated Hospital of Xinxiang Medical UniversityDepartment of Respiratory Medicine, Institute of Pediatrics, Shenzhen Children’s HospitalDepartment of Neonatology, Guangdong Provincial People′s Hospital(Guangdong Academy of Medical Sciences), Southern Medical UniversityDepartment of Pediatrics, First Affiliated Hospital of Xinxiang Medical UniversityAbstract Background Refractory mycoplasma pneumoniae pneumonia (RMPP) can result in severe complications and long-term effects. Early identification of RMPP and appropriate treatments can effectively alleviate complications and restrict the progression of sequelae. There is currently a dearth of a comprehensive and efficient model for predicting and evaluating RMPP. Methods The development cohort consisted of patients with mycoplasma pneumoniae pneumonia (MPP) who underwent fiberoptic bronchoscopy between January 2019 and October 2021. Multivariable logistic regression analysis was used to identify independent risk factors for RMPP, and a nomogram model was developed that included initial admission examinations and clinical characteristics. The accuracy of the model was validated using a validation cohort of patients enrolled between November 2021 and April 2023. Result 373 patients were enrolled including 229 cases of the development cohort and 144 cases of the validation cohort. Multivariable Logistic regression analysis showed that the six independent risk factors for RMPP were age (OR = 1.151, 95% confidence interval (CI) 1.014–1.306), acute physiology and chronic health evaluation (APACHE) II score(OR = 0.872, 95% CI 0.792–0.961), computed tomography (CT) total score(OR = 1.407, 95% CI 1.258–1.575), secretion color(OR = 2.719, 95% CI 1.562–4.734), mucosal edema(OR = 5.064, 95% CI 2.748-9.300), and procalcitonin (PCT) (OR = 0.871, 95% CI 0.806–0.941). The Area Under Curve (AUC) of the model in the development cohort and validation cohort was 0.913(95%CI 0.875–0.951) and 0.811(95%CI 0.739–0.883), respectively. Hosmer-Lemeshow test showed that the model’s goodness of fit had good consistency in the development cohort and validation cohort (χ2 = 10.546, P = 0.229; χ2 = 7.894, P = 0.342). The DCA of the development and validation cohorts showed clear net benefits using the nomogram to predict RMPP. Conclusion We developed a nomogram model that integrates clinical, imaging, and bronchoscopic features to enable early and accurate prediction of the risk of RMPP in children. This model provides a quantitative tool for personalized intervention and demonstrates significant clinical application value.https://doi.org/10.1186/s12879-025-11133-9Refractory mycoplasma pneumoniae pneumoniaEarly comprehensive assessmentInternal validationChildren
spellingShingle Xiangtao Wu
Weihong Lu
Weiqing Liu
Yishuai Ren
Shuangshuang Fan
Yali Xu
Ruigui Zhang
Xue Liu
Mengzhu Wang
Tuanjie Wang
Xingliang Zhang
Shaoru He
Shujun Li
Predictive value of an early comprehensive assessment model for refractory mycoplasma pneumoniae pneumonia and internal validation
BMC Infectious Diseases
Refractory mycoplasma pneumoniae pneumonia
Early comprehensive assessment
Internal validation
Children
title Predictive value of an early comprehensive assessment model for refractory mycoplasma pneumoniae pneumonia and internal validation
title_full Predictive value of an early comprehensive assessment model for refractory mycoplasma pneumoniae pneumonia and internal validation
title_fullStr Predictive value of an early comprehensive assessment model for refractory mycoplasma pneumoniae pneumonia and internal validation
title_full_unstemmed Predictive value of an early comprehensive assessment model for refractory mycoplasma pneumoniae pneumonia and internal validation
title_short Predictive value of an early comprehensive assessment model for refractory mycoplasma pneumoniae pneumonia and internal validation
title_sort predictive value of an early comprehensive assessment model for refractory mycoplasma pneumoniae pneumonia and internal validation
topic Refractory mycoplasma pneumoniae pneumonia
Early comprehensive assessment
Internal validation
Children
url https://doi.org/10.1186/s12879-025-11133-9
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