Inpatient signs and symptoms and factors associated with death in children aged 5 years and younger admitted to two Ebola management centres in Sierra Leone, 2014: a retrospective cohort study
Bibliographic record
Abstract
BACKGROUND: Médecins Sans Frontières (MSF) opened Ebola management centres (EMCs) in Sierra Leone in Kailahun in June, 2014, and Bo in September, 2014. Case fatality in the west African Ebola virus disease epidemic has been highest in children younger than 5 years. Clinical data on outcomes can provide important evidence to guide future management. However, such data on children are scarce and disaggregated clinical data across all ages in this epidemic have focussed on symptoms reported on arrival at treatment facilities, rather than symptoms and signs observed during admission. We aimed to describe the clinical characteristics of children aged 5 years and younger admitted to the MSF EMCs in Bo and Kailahun, and any associations between these characteristics and mortality. METHODS: In a retrospective cohort study, we included data from children aged 5 years and younger with laboratory-confirmed Ebola virus disease admitted to EMCs between June and December, 2014. We described epidemiological, demographic, and clinical characteristics and viral load (measured using Ebola virus cycle thresholds [Ct]), and assessed their association with death using Cox regression modelling. FINDINGS: We included 91 children in analysis; 52 died (57·1%). Case fatality was higher in children aged less than 2 years (76·5% [26/34]) than those aged 2-5 years (45·6% [26/57]; adjusted HR 3·5 [95% CI 1·5-8·5]) and in those with high (Ct<25) versus low (Ct≥25) viral load (81·8% [18/22] vs 45·9% [28/61], respectively; adjusted HR 9·2 [95% CI 3·8-22·5]). Symptoms observed during admission included: weakness 74·7% (68); fever 70·8% (63/89); distress 63·7% (58); loss of appetite 60·4% (55); diarrhoea 59·3% (54); and cough 52·7% (48). At admission, 25% (19/76) of children were afebrile. Signs significantly associated with death were fever, vomiting, and diarrhoea. Hiccups, bleeding, and confusion were observed only in children who died. INTERPRETATION: This description of the clinical features of Ebola virus disease over the duration of illness in children aged 5 years and younger shows symptoms associated with death and a high prevalence of distress, with implications for clinical management. Collection and analysis of age-specific data on Ebola is very important to ensure that the specific vulnerabilities of children are addressed. FUNDING: No specific funding was received for this study. EB is supported by the National Health and Medical Research Council of Australia.
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How this classification was reachedexpand
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".