Predicting paediatric pneumonia severity in the emergency department: a multinational prospective cohort study of the
Todd A Florin1, Daniel J Tancredi2, Lilliam Ambroggio3
1Department of Pediatrics, Northwestern University Feinberg School of Medicine, Chicago, IL, USA; Division of Pediatric Emergency Medicine, Ann and Robert H. Lurie Children's Hospital of Chicago, Chicago, IL, USA; Stanley Manne Children's Research Institute, Chicago, IL, USA.
Insights
New risk models accurately predict pediatric community-acquired pneumonia (CAP) severity in emergency departments. These tools aid clinicians in determining hospitalization needs for children with CAP, improving management in well-resourced settings.
Area of Science:
- Pediatric emergency medicine
- Infectious disease epidemiology
- Clinical risk prediction modeling
Background:
- Risk stratification tools for pediatric community-acquired pneumonia (CAP) are limited in well-resourced settings.
- Accurate prediction of CAP severity is crucial for appropriate clinical decision-making and resource allocation.
Purpose of the Study:
- To prospectively develop and validate risk prediction models for differentiating mild CAP from moderate or severe CAP in children.
- To aid clinicians in emergency departments (EDs) in determining the need for hospitalization.
Main Methods:
- Prospective cohort study involving 73 EDs across 14 countries from February 2019 to June 2021.
- Included children aged 3 months to <14 years with a clinical diagnosis of CAP, excluding those with recent hospitalization or chronic complex conditions.
- Developed logistic regression models with bootstrap validation to predict CAP severity (mild, moderate, severe) based on clinical and demographic data.
Main Results:
- The final model accurately discriminated between mild CAP and moderate/severe CAP (c-statistic 0.82).
- Key predictors for moderate/severe CAP included abdominal pain, refusal to drink, prior antibiotic use, chest retractions, elevated respiratory/heart rates, and hypoxemia.
- Congestion/rhinorrhoea was negatively associated with moderate/severe CAP.
Conclusions:
- Accurate and pragmatic risk prediction models for pediatric CAP severity have been developed.
- These models, upon external validation, can support individualized risk assessments in clinical practice.
- Implementation in well-resourced health systems has the potential to enhance the management of pediatric CAP.
Background:
Risk stratification tools for paediatric community-acquired pneumonia (CAP) in well-resourced settings are scarce. We prospectively developed models to predict CAP severity within a multinational cohort of paediatric emergency departments (EDs). Our primary objective was to develop a risk prediction model to discriminate between mild CAP and moderate or severe CAP to assist clinicians in determining the need for hospitalisation.
Methods:
This prospective cohort study was conducted from Feb 6, 2019, to June 30, 2021, at 73 EDs in 14 countries. Children aged 3 months to <14 years with clinical diagnoses of CAP were included. Children were excluded if they were recently hospitalised or had a chronic complex condition (eg, immunodeficiency). The primary outcome was severity, defined as mild (CAP treated in the outpatient setting or hospitalisation <24 h with no use of oxygen or intravenous fluids during that time), moderate (hospitalisation <24 h with oxygen or fluids, or hospitalisation ≥24 h regardless of interventions but without an outcome qualifying as severe CAP), or severe (chest drainage, intensive care unit admission >24 h, positive-pressure ventilation, septic shock, vasoactive infusions, extracorporeal membrane oxygenation, or death) occurring within 7 days of the ED visit. Models were developed using logistic regression with bootstrap validation.
Findings:
Of 2222 children in the overall study population (1103 [49·7%] female, 1119 [50·3%] male; median age 3 years [IQR 1-5]), 1290 (58·1%) had mild CAP, 812 (36·5%) moderate, and 120 (5·4%) severe. Primary analyses were performed in 1901 patients with complete data: 1011 (53·2%) mild, 772 (40·6%) moderate, and 118 (6·2%) severe CAP. Congestion or rhinorrhoea was negatively associated with moderate or severe CAP (adjusted odds ratio 0·59 [95% CI 0·46-0·76]), while abdominal pain (1·52 [1·17-1·97]), refusal to drink (1·57 [1·24-2·00]), antibiotics before ED visit (1·64 [1·29-2·10]), chest retractions (2·86 [2·24-3·65]), respiratory rate above the 95th percentile for age (1·63 [1·29-2·06]), heart rate above the 95th percentile for age (1·64 [1·27-2·12]), and hypoxaemia (oxygen saturation 90-92%, 3·24 [2·46-4·27]; <90%, 13·39 [8·64-20·73]) were positively associated. The model accurately discriminated between mild CAP and moderate or severe CAP (c-statistic 0·82 [95% CI 0·80-0·84]). Similar results were found in those with radiographic CAP, with decreased breath sounds and multifocal opacities on radiography as additional predictors (c-statistic 0·82 [0·80-0·85]).
Interpretation:
We developed accurate, pragmatic severity risk prediction models among children with CAP. After future external validation, these models have the potential to provide individualised risk assessments that can be incorporated into clinical judgement in well-resourced health systems to improve management.
Funding:
Division of Emergency Medicine at Cincinnati Children's Hospital Medical Center, Division of Emergency Medicine at Ann & Robert H. Lurie Children's Hospital of Chicago, and Department of Emergency Medicine at University of California, Davis.
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