Mycoplasma pneumoniae infection prediction model for hospitalized community-acquired pneumonia children.
Mycoplasma pneumoniae
community-acquired pneumonia
nomogram
prediction model
Journal
Pediatric pulmonology
ISSN: 1099-0496
Titre abrégé: Pediatr Pulmonol
Pays: United States
ID NLM: 8510590
Informations de publication
Date de publication:
12 2021
12 2021
Historique:
revised:
20
08
2021
received:
03
05
2021
accepted:
04
09
2021
pubmed:
22
9
2021
medline:
25
12
2021
entrez:
21
9
2021
Statut:
ppublish
Résumé
We sought to develop a nomogram to predict Mycoplasma pneumoniae (Mp) infection among hospitalized children with community-acquired pneumonia (CAP) and compare it with another model developed from age and duration of fever. Data on 5904 CAP children who were enrolled at Shanghai Children's Medical Center were retrospectively collected and divided into a training set (n = 4133) and a validation set (n = 1771). The model's performance was determined by concordance index (C-index), calibration curves, Brier scores, and decision curve analyses (DCAs). Akaike information criterion (AIC) and Bayesian information criterion (BIC) were used for model comparisons. Incorporating five factors (age, duration of fever, erythrocyte sedimentation rate, leukocyte count, and neutrophil proportion), the nomogram achieved good C-index values of 0.74 (95% confidence interval [CI]: 0.72-0.76) and 0.75 (95% CI: 0.73-0.78) and good Brier scores of 0.14 (95% CI: 0.13-0.15) and 0.17 (95% CI: 0.15-0.18) in predicting Mp infection in the training and validation cohorts, respectively, and had moderate fitted calibration plots. The DCAs showed good clinical usefulness of the nomogram. Patients were effectively divided into low, medium, and high risk groups by two cut-off score points of the nomogram, 210 and 300. With the lower AIC (3673.5) and BIC (3774.7) value, the model of five predictors is the better model. By using five predictor variables, a simple nomogram of good predictive accuracy for Mp infection and moderate agreements between the actual outcome and the predicted probability was constructed. It could serve as a tool to aid physicians in clinical decision-making processes.
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
4020-4028Informations de copyright
© 2021 Wiley Periodicals LLC.
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