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. 2022 Jan 1;149(1):e2021051405.
doi: 10.1542/peds.2021-051405.

A Prediction Model for Pediatric Radiographic Pneumonia

Sriram Ramgopal  1 , Lilliam Ambroggio  2 , Douglas Lorenz  3 , Samir S Shah  4 , Richard M Ruddy  5 , Todd A Florin  1
Affiliations

A Prediction Model for Pediatric Radiographic Pneumonia

Sriram Ramgopal et al. Pediatrics. .

Abstract

Background: Chest radiographs (CXRs) are frequently used in the diagnosis of community-acquired pneumonia (CAP). We sought to construct a predictive model for radiographic CAP based on clinical features to decrease CXR use.

Methods: We performed a single-center prospective study of patients 3 months to 18 years of age with signs of lower respiratory infection who received a CXR for suspicion of CAP. We used penalized multivariable logistic regression to develop a full model and bootstrapped backward selection models to develop a parsimonious reduced model. We evaluated model performance at different thresholds of predicted risk.

Results: Radiographic CAP was identified in 253 (22.2%) of 1142 patients. In multivariable analysis, increasing age, prolonged fever duration, tachypnea, and focal decreased breath sounds were positively associated with CAP. Rhinorrhea and wheezing were negatively associated with CAP. The bootstrapped reduced model retained 3 variables: age, fever duration, and decreased breath sounds. The area under the receiver operating characteristic for the reduced model was 0.80 (95% confidence interval: 0.77-0.84). Of 229 children with a predicted risk of <4%, 13 (5.7%) had radiographic CAP (sensitivity of 94.9% at a 4% risk threshold). Conversely, of 229 children with a predicted risk of >39%, 140 (61.1%) had CAP (specificity of 90% at a 39% risk threshold).

Conclusions: A predictive model including age, fever duration, and decreased breath sounds has excellent discrimination for radiographic CAP. After external validation, this model may facilitate decisions around CXR or antibiotic use in CAP.

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Conflict of interest statement

FINANCIAL DISCLOSURE: The authors have indicated they have no financial relationships relevant to this article to disclose.

Figures

FIGURE 1
FIGURE 1
ROC curves for the full and reduced models. The solid points indicate various risk cut points for the reduced model (performance at each cut point noted in the inlaid table). AUC, area under the receiver operating characteristic.
FIGURE 2
FIGURE 2
Model performance by risk thresholds. Intervals were calculated by dividing the cohort into 10 groups of approximately equal size. Within each bar, the darker and lighter shades indicate the proportions of patients in each band with and without radiographic disease, respectively.
See this image and copyright information in PMC

Comment in

References

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