COVID-19 in Children with Brain-Based Developmental Disabilities: A Rapid Review Update
Bibliographic record
Abstract
Abstract Objective Information regarding the impact of COVID-19 in children with brain-based disabilities, or those at risk of developing such conditions, remains scarce. The objective was to evaluate if children with brain-based disabilities are more likely to (1) develop COVID-19, (2) develop complications from the disease, and (3) to have a poorer prognosis. Study design We conducted a rapid review using search strategies iteratively developed and tested by an experienced medical information specialist in consultation with the review team and a panel of knowledge users. Searches were initially performed on April 18th, 2021, and updated on October 31st, 2020. Four reviewers individually performed study selection using pilot-tested standardized forms. Single reviewers extracted the data using a standardized extraction form that included study characteristics, patients’ characteristics, and outcomes reported. Results We identified 1448 publications, of which 29 were included. Studies reported data on 2288 COVID-19 positive children, including 462 with a brain-based disability, and 72 at risk of developing such disability. Overall, the included studies showed a greater risk to develop severe COVID-19 disease in children with brain-based disabilities. Although mortality is very low, the case-fatality rate appeared to be higher in children with disabilities compared to children without disabilities. Conclusions Our review shows that children with brain-based disabilities are overrepresented in hospitalization numbers compared to children without disabilities. However, most studies included children that were hospitalized from COVID-19 in secondary and tertiary care centers. Results of this review should therefore be interpreted with caution.
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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 | 0.002 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".