COVID-19 and MIS-C treatment in children—results from an international survey
Bibliographic record
Abstract
Children have been mostly excluded from COVID-19 clinical trials, and, as a result, most medicines approved for COVID-19 have no pediatric indication. In addition, access to COVID-19 therapeutics remains limited. Collecting physicians' experiences with off-label use of therapeutics is important to inform global prioritization processes and better target pediatric research and development. A standardized questionnaire was designed to explore the use of therapeutics used to treat COVID-19 and multisystem inflammatory syndrome in children (MIS-C) in pediatric patients globally. Seventy-three physicians from 29 countries participated. For COVID-19, steroids were used by 75.6% of respondents; remdesivir and monoclonal antibodies were prescribed by 48.6% and 27.1% of respondents, respectively. For MIS-C, steroids were prescribed by 79.1% of respondents and intravenous immunoglobulins by 69.6%. The use of these products depended on their pediatric approval and the limited availability of antivirals and most monoclonal antibodies in Africa, South America, Southeast Asia, and Eastern Europe. Off-label prescription resulted widespread due to the paucity of clinical trials in young children at the time of the survey; though, based on our survey results, it was generally safe and led to clinical benefits. Conclusion: This survey provides a snapshot of current practice for treating pediatric COVID-19 worldwide, informing global prioritization efforts to better target pediatric research and development for COVID-19 therapeutics. Off-label use of such medicines is widespread for the paucity of clinical trials under 12 years and 40 kg, though appears to be safe and generally results in clinical benefits, even in young children. However, access to care, including medicine availability, differs widely globally. Clinical development of COVID-19 antivirals and monoclonal antibodies requires acceleration to ensure pediatric indication and allow worldwide availability of therapeutics that will enable more equitable access to COVID-19 treatment. What is Known: • Children have been mostly excluded from COVID-19 clinical trials, and, as a result, most medicines approved for COVID-19 have no pediatric indication. • Access to care differs widely globally, so because of the diversity of national healthcare systems; the unequal availability of medicines for COVID-19 treatment represents an obstacle to the pediatric population's universal right to health care. What is New: • Off-label COVID-19 drug prescription is widespread due to the lack of clinical trials in children younger than 12 years and weighing less than 40 kg, but relatively safe and generally leading to clinical benefit. • The application of the GAP-f framework to COVID-19 medicines is crucial, ensuring widespread access to all safe and effective drugs, enabling the rapid development of age-appropriate formulations, and developing specific access plans (including stability, storage, packaging, and labeling) for distribution in low- and middle-income countries (LMICs). Antivirals and monoclonal antibodies may benefit from the acceleration to reach widespread and equal diffusion.
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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 | 0.001 |
| 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".