ArticleJournal of inflammation research2023
Risk Prediction Model for Necrotizing Pneumonia in Children with
Article in Journal of inflammation research, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 30 papers.
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Who cites it
30 citing papers in PubMed, 29 citations in OpenAlex.
- Construction of a risk prediction model for multiple bronchoalveolar lavages in children with necrotizing pneumonia based on LASSO regression.Pediatric research · 2026Article
- Construction of a risk prediction model for severe community-acquired pneumonia in children in Qinghai region.BMJ paediatrics open · 2026Review
- Early Prediction of Necrotizing Pneumonia in Children with Mycoplasma Pneumoniae Pneumonia: Development and Temporal Validation of a Clinical Model.Children (Basel, Switzerland) · 2026Article
- Analysis of the pathogens and clinical characteristics of pediatric necrotizing pneumonia patients in a tertiary grade a hospital from 2019 to 2025: a retrospective study design.European journal of clinical microbiology & infectious diseases : official publication of the European Society of Clinical Microbiology · 2026Article
- Clinical analysis of Mycoplasma pneumoniae necrotizing pneumonia in children.BMC infectious diseases · 2026Article
- Development and validation of a predictive nomogram for early detection of necrotizing pneumonia in children with refractoryFrontiers in pediatrics · 2026Article
- Clinical Prediction of Necrotizing Pneumonia in Children With Mycoplasma pneumoniae: A Model Based on Early Response to Therapy.Canadian respiratory journal · 2026Article
- Exploring Clinical Characteristics and Risk Factors ofJournal of inflammation research · 2026Article
- Lung ultrasound radiomics for identifying severeFrontiers in pediatrics · 2026Article
- Non-linear associations between inflammatory biomarkers andFrontiers in pediatrics · 2026Article
- A machine learning-based predictive model for multilobar pulmonary consolidation induced by macrolide-resistantMicrobiology spectrum · 2025Article
- Clinical profile and risk factors for respiratory failure in children withBiomolecules & biomedicine · 2025Article
- Establishment and validation of a predictive model for Lobar pneumonia caused by Mycoplasma pneumoniae infection in children.Scientific reports · 2025Article
- Development and validation of a nomogram for predicting necrotizing pneumonia in children with refractory Mycoplasma pneumoniae pneumonia.Italian journal of pediatrics · 2025Article
- Chest CT characterization of children with necrotizing pneumonia due to Mycoplasma pneumoniae infection.Scientific reports · 2025Article
- Pulmonary embolism in children with mycoplasma pneumonia: can it be predicted?European journal of clinical microbiology & infectious diseases : official publication of the European Society of Clinical Microbiology · 2025Article
- Improvement of IL-4, IL-6, IL-10, TNF-α and IFN-γ in children with mycoplasma pneumonia through the combination of video scenario-based breathing training and antibiotics.Sleep & breathing = Schlaf & Atmung · 2025Article
- Biomarkers associated with the diagnosis and prognosis ofFrontiers in cellular and infection microbiology · 2025Review
- Pulmonary embolism complicatingFrontiers in pediatrics · 2025Article
- D-dimer serves as predictor of plastic bronchitis or necrotizing pneumonia in children withFrontiers in pediatrics · 2025Article
Corrections and comments
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Authors and funding
2 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Objective: To analyze the predictive factors for necrotizing pneumonia (NP) in children with Methods: The clinical data with MPP at the Children's Hospital of Kunming Medical University from January 2014 to November 2022 were retrospectively analyzed. Eighty-four children with MPP who developed NP were divided into the necrotizing group, and 168 children who did not develop NP were divided into the non-necrotizing group by propensity-score matching. LASSO regression was used to select the optimal factors, and multivariate logistic regression analysis was used to establish a clinical prediction model. The receiver operating characteristic (ROC) curve and calibration curve were used to evaluate the discrimination and calibration of the nomogram. Clinical decision curve analysis was used to evaluate the clinical predictive value. Results: LASSO regression analysis showed that bacterial co-infection, chest pain, LDH, CRP, duration of fever, and D-dimer were the influencing factors for NP in children with MPP (P < 0.05). The results of ROC analysis showed that the AUC of the prediction model established in this study for predicting necrotizing MPP was 0.870 (95% CI: 0.813-0.927, P < 0.001) in the training set and 0.843 (95% CI: 0.757-0.930, P < 0.001) in the validation set. The Bootstrap repeated sampling for 1000 times was used for internal validation, and the calibration curve showed that the model had good consistency. The Hosmer-Lemeshow test showed that the predicted probability of the model had a good fit with the actual probability in the training set and the validation set (P values of 0.366 and 0.667, respectively). The clinical decision curve showed that the model had good clinical application value. Conclusion: The prediction model based on bacterial co-infection, chest pain, LDH, CRP, fever duration, and D-dimer has a good predictive value for necrotizing MPP.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.