Clinical characteristics, treatment and outcomes of paediatric COVID-19: a systematic review and meta-analysis
Why this work is in the frame
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Bibliographic record
Abstract
OBJECTIVE: Compare paediatric COVID-19 disease characteristics, management and outcomes according to World Bank country income level and disease severity. DESIGN: Systematic review and meta-analysis. SETTING: Between 1 December 2019 and 8 January 2021, 3350 articles were identified. Two reviewers conducted study screening, data abstraction and quality assessment independently and in duplicate. Observational studies describing laboratory-confirmed paediatric (0-19 years old) COVID-19 were considered for inclusion. MAIN OUTCOMES AND MEASURES: The pooled proportions of clinical findings, treatment and outcomes were compared according to World Bank country income level and reported disease severity. RESULTS: 129 studies were included from 31 countries comprising 10 251 children of which 57.4% were hospitalised. Mean age was 7.0 years (SD 3.6), and 27.1% had a comorbidity. Fever (63.3%) and cough (33.7%) were common. Of 3670 cases, 44.1% had radiographic abnormalities. The majority of cases recovered (88.9%); however, 96 hospitalised children died. Compared with high-income countries, in low-income and middle-income countries, a lower proportion of cases were admitted to intensive care units (ICUs) (9.9% vs 26.0%) yet pooled proportion of deaths among hospitalised children was higher (relative risk 2.14, 95% CI 1.43 to 3.20). Children with severe disease received antimicrobials, inotropes and anti-inflammatory agents more frequently than those with non-severe disease. Subgroup analyses showed that a higher proportion of children with multisystem inflammatory syndrome (MIS-C) were admitted to ICU (47.1% vs 22.9%) and a higher proportion of hospitalised children with MIS-C died (4.8% vs 3.6%) compared with the overall sample. CONCLUSION: Paediatric COVID-19 has a favourable prognosis. Further severe disease characterisation in children is needed globally.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.011 | 0.004 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it