Emergency Department Markers of Severe Pediatric Pneumonia
Bibliographic record
Abstract
OBJECTIVE: Pneumonia is a common infection in childhood. We tested the utility of initial clinical assessment tools and of early laboratory markers for predicting severe disease among children admitted with pneumonia. METHODS: This was a retrospective cohort study of previously healthy children admitted to a children's hospital with pneumonia from June 2017 to June 2021. We tested the predictive utility of the Canadian Triage and Acuity Scale (CTAS) score and of the pediatric assessment triangle (PAT) upon first patient contact. We also evaluated the predictive value of elevated WBC, ANC, CRP, lower serum albumin, and phosphorus drawn in the ED, with severe pneumonia defined as concurrent sepsis, need for pleural drainage, or intensive care during index admission. Analyses were bivariate. RESULTS: During the study period, 554 children admitted with pneumonia were included in the analysis [median age, 25.5 mo (IQR: 14.3 to 63.0); 58.3% males]. Seventy-four (13.3%) had severe pneumonia.Severe pneumonia was diagnosed in 17% of children classified as CTAS 2 (emergent), 13% with CTAS 3 (urgent), 13% with CTAS 4 (less urgent), and 0% with CTAS 5 (nonurgent). Among children with an abnormal PAT, 20% had severe pneumonia versus 5% among those with a normal PAT. The receiver operating characteristic area under the curve (95% CIs) was 0.73 (0.66-0.80) for serum albumin, 0.66 (0.61-0.72) for CRP, 0.61 (0.58-0.66) for phosphorus, 0.58 (0.51-0.64) for ANC, and 0.55 (0.49-0.62) for WBC. The AUC for PAT was 0.71 (95% CI: 0.65-0.77) and for CTAS was 0.56 (95% CI: 0.49-0.62). CONCLUSIONS: For the prediction of severe pediatric pneumonia, no single marker offered robust utility. CTAS showed no clear utility, while PAT was comparable to albumin, the best-performing laboratory marker. Hypoalbuminemia was marginally superior to elevated CRP. The remaining laboratory markers had at best moderate accuracy in isolation.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".