Invasive Group A Streptococcal Infections in Pediatric Critical Care: A Retrospective Cohort Study
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVE: The reported rising global rates of invasive group A Streptococcus (iGAS) infection raise concern for disease related increase in critical illness and fatalities. An enhanced understanding of various presentations to health care and clinical course could improve early recognition and therapy in children with iGAS. The objective of this study was to describe the epidemiology of iGAS infections among children admitted to critical care. METHODS: A retrospective cohort study of children admitted to the PICU at The Hospital for Sick Children, in Toronto, Canada, between March 2022 and June 2023. Eligible patients were 0 to 18 years, with a diagnosis of iGAS infection. We describe the proportion of children admitted to the PICU with iGAS over the study period, their clinical characteristics, the frequency and timing of therapies, discharge versus baseline function, and PICU mortality. RESULTS: Among the 1820 children admitted to the PICU, 29 (1.6%) patients had iGAS infection. Of these 29 patients, 80% (n = 23) survived to hospital discharge. Patients who survived generally had favorable functional outcomes. Despite the high severity of illness and mortality described in this cohort, 61% returned to their baseline functional status by hospital discharge. CONCLUSIONS: This is the first report of critically ill children with iGAS in Canada during the increased incidence reported worldwide. We describe the clinical course of iGAS infection in children admitted to PICU with access to advanced extracorporeal interventions. Though there is a high mortality rate in this cohort, those who survive have favorable outcomes.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".