Development of the Novel Pneumonia Risk Score to Predict Radiographic Pneumonia in Children

Community-Acquired Pneumonia Diagnosis Following Emergency Department Visits for Respiratory Illness

Community-acquired pneumonia (CAP) is often considered for children presenting to the emergency department (ED) with respiratory symptoms. It is unclear how often children are diagnosed with CAP following an ED visit for respiratory illness. We performed a retrospective case-control study to evaluate 7-day CAP diagnosis among children 3 months to 18 years discharged from the ED with respiratory illness from 2011 to 2021 and who receive care at 4 hospital-affiliated primary care clinics. Logistic regression was performed to assess for predictors of 7-day CAP diagnosis. Seventy-four (0.7%, 95% confidence interval [CI] = 0.6%, 0.9%) of 10 329 children were diagnosed with CAP within 7 days, and fever at the index visit was associated with increased odds of diagnosis (odds ratio [OR] = 3.32, 95% CI = 1.75-6.28). Community-acquired pneumonia diagnosis after discharge from the ED with respiratory illness is rare, even among children who are febrile at time of initial evaluation.

Cost of Pediatric Pneumonia Episodes With or Without Chest Radiography

BACKGROUND AND OBJECTIVES

Despite its routine use, it is unclear whether chest radiograph (CXR) is a cost-effective strategy in the workup of community-acquired pneumonia (CAP) in the pediatric emergency department (ED). We sought to assess the costs of CAP episodes with and without CXR among children discharged from the ED.

METHODS

This was a retrospective cohort study within the Healthcare Cost and Utilization Project State ED and Inpatient Databases of children aged 3 months to 18 years with CAP discharged from any EDs in 8 states from 2014 to 2019. We evaluated total 28-day costs after ED discharge, including the index visit and subsequent care. Mixed-effects linear regression models adjusted for patient-level variables and illness severity were performed to evaluate the association between CXR and costs.

RESULTS

We evaluated 225c781 children with CAP, and 86.2% had CXR at the index ED visit. Median costs of the 28-day episodes, index ED visits, and subsequent visits were $314 (interquartile range [IQR] 208-497), $288 (IQR 195-433), and $255 (IQR 133-637), respectively. There was a $33 (95% confidence interval [CI] 22-44) savings over 28-days per patient for those who received a CXR compared with no CXR after adjusting for patient-level variables and illness severity. Costs during subsequent visits ($26 savings, 95% CI 16-36) accounted for the majority of the savings as compared with the index ED visit ($6, 95% CI 3-10).

CONCLUSIONS

Performance of CXR for CAP diagnosis is associated with lower costs when considering the downstream provision of care among patients who require subsequent health care after initial ED discharge.

Community-Acquired Pneumonia in Children

ABSTRACT

Community-acquired pneumonia (CAP) is the most common cause of childhood mortality globally. In the United States, CAP is a leading cause of pediatric hospitalization and antibiotic use and is associated with substantial morbidity. There has been a dramatic shift in microbiological etiologies for CAP in children over time as pneumococcal pneumonia has become less common and viral etiologies have become predominant. There is no commonly agreed on approach to the diagnosis of CAP in children. When indicated, antimicrobial treatment should consist of narrow-spectrum antibiotics. In this article, we will describe the current understanding of the microbiological etiologies, clinical presentation, diagnostic approach, risk factors, treatment, and future directions in the diagnosis and management of pediatric CAP.

The development of a novel natural language processing tool to identify pediatric chest radiograph reports with pneumonia

Objective

Chest radiographs are frequently used to diagnose community-acquired pneumonia (CAP) for children in the acute care setting. Natural language processing (NLP)-based tools may be incorporated into the electronic health record and combined with other clinical data to develop meaningful clinical decision support tools for this common pediatric infection. We sought to develop and internally validate NLP algorithms to identify pediatric chest radiograph (CXR) reports with pneumonia.

Materials and methods

We performed a retrospective study of encounters for patients from six pediatric hospitals over a 3-year period. We utilized six NLP techniques: word embedding, support vector machines, extreme gradient boosting (XGBoost), light gradient boosting machines Naïve Bayes and logistic regression. We evaluated their performance of each model from a validation sample of 1,350 chest radiographs developed as a stratified random sample of 35% admitted and 65% discharged patients when both using expert consensus and diagnosis codes.

Results

Of 172,662 encounters in the derivation sample, 15.6% had a discharge diagnosis of pneumonia in a primary or secondary position. The median patient age in the derivation sample was 3.7 years (interquartile range, 1.4-9.5 years). In the validation sample, 185/1350 (13.8%) and 205/1350 (15.3%) were classified as pneumonia by content experts and by diagnosis codes, respectively. Compared to content experts, Naïve Bayes had the highest sensitivity (93.5%) and XGBoost had the highest F1 score (72.4). Compared to a diagnosis code of pneumonia, the highest sensitivity was again with the Naïve Bayes (80.1%), and the highest F1 score was with the support vector machine (53.0%).

Conclusion

NLP algorithms can accurately identify pediatric pneumonia from radiography reports. Following external validation and implementation into the electronic health record, these algorithms can facilitate clinical decision support and inform large database research.

Validation of Prediction Models for Pneumonia Among Children in the Emergency Department

BACKGROUND

Several prediction models have been reported to identify patients with radiographic pneumonia, but none have been validated or broadly implemented into practice. We evaluated 5 prediction models for radiographic pneumonia in children.

METHODS

We evaluated 5 previously published prediction models for radiographic pneumonia (Neuman, Oostenbrink, Lynch, Mahabee-Gittens, and Lipsett) using data from a single-center prospective study of patients 3 months to 18 years with signs of lower respiratory tract infection. Our outcome was radiographic pneumonia. We compared each model's area under the receiver operating characteristic curve (AUROC) and evaluated their diagnostic accuracy at statistically-derived cutpoints.

RESULTS

Radiographic pneumonia was identified in 253 (22.2%) of 1142 patients. When using model coefficients derived from the study dataset, AUROC ranged from 0.58 (95% confidence interval, 0.52-0.64) to 0.79 (95% confidence interval, 0.75-0.82). When using coefficients derived from original study models, 2 studies demonstrated an AUROC >0.70 (Neuman and Lipsett); this increased to 3 after deriving regression coefficients from the study cohort (Neuman, Lipsett, and Oostenbrink). Two models required historical and clinical data (Neuman and Lipsett), and the third additionally required C-reactive protein (Oostenbrink). At a statistically derived cutpoint of predicted risk from each model, sensitivity ranged from 51.2% to 70.4%, specificity 49.9% to 87.5%, positive predictive value 16.1% to 54.4%, and negative predictive value 83.9% to 90.7%.

CONCLUSIONS

Prediction models for radiographic pneumonia had varying performance. The 3 models with higher performance may facilitate clinical management by predicting the risk of radiographic pneumonia among children with lower respiratory tract infection.

Significance of Sonographic Subcentimeter, Subpleural Consolidations in Pediatric Patients Evaluated for Pneumonia

OBJECTIVES

To investigate the rates of radiographic pneumonia and clinical outcomes of children with suspected pneumonia and subcentimeter, subpleural consolidations on point-of-care lung ultrasound.

STUDY DESIGN

We enrolled a prospective convenience sample of children aged 6 months to 18 years undergoing chest radiography (CXR) for pneumonia evaluation in a single tertiary-care pediatric emergency department. Point-of-care lung ultrasound was performed by an emergency medicine physician with subsequent expert review. We determined rates of radiographic pneumonia and clinical outcomes in the children with subcentimeter, subpleural consolidations, stratified by the presence of larger (>1 cm) sonographic consolidations. The children were followed prospectively for 2 weeks to identify a delayed diagnosis of pneumonia.

RESULTS

A total of 188 patients, with a median age of 5.8 years (IQR, 3.5-11.0 years), were evaluated. Of these patients, 62 (33%) had subcentimeter, subpleural consolidations on lung ultrasound, and 23 (37%) also had larger (>1 cm) consolidations. Patients with subcentimeter, subpleural consolidations and larger consolidations had the highest rates of definite radiographic pneumonia (61%), compared with 21% among children with isolated subcentimeter, subpleural consolidations. Overall, 23 children with isolated subcentimeter, subpleural consolidations (59%) had no evidence of pneumonia on CXR. Among 16 children with isolated subcentimeter, subpleural consolidations and not treated with antibiotics, none had a subsequent pneumonia diagnosis within the 2-week follow-up period.

CONCLUSIONS

Children with subcentimeter, subpleural consolidations often had radiographic pneumonia; however, this occurred most frequently when subcentimeter, subpleural consolidations were identified in combination with larger consolidations. Isolated subcentimeter, subpleural consolidations in the absence of larger consolidations should not be viewed as synonymous with pneumonia; CXR may provide adjunctive information in these cases.