Rapid advice guidelines for management of children with COVID-19
Why this work is in the frame
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Bibliographic record
Abstract
In December 2019, an infectious disease, caused by a novel coronavirus, emerged in Wuhan City, China. The disease was later named coronavirus disease 2019 (COVID-19) and the virus causing it was named the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The rapid spread of COVID-19 worldwide has brought great challenges to local and global public health security and health systems. On March 12, 2020, the World Health Organization (WHO) declared the coronavirus outbreak a global pandemic and raised the risk of a global SARS-CoV-2 outbreak to “very high” (1-6). COVID-19, and its pathogen SARS-CoV-2, represent a novel infectious disease and all populations are therefore susceptible to infection. Its basic reproductive number R0 has been estimated at 3.3 (range 1.4 to 6.5), which is similar to SARS and much higher than Middle East respiratory syndrome (MERS) or influenza (7-10). By April 15, around two million confirmed cases had been reported over 200 countries worldwide. The exact number of patients under the age of 18 remains unknown, but their percentage among all cases is estimated to be less than 2% (11,12). Evidence indicates that the family cluster is the main source of COVID-19 infection for children (13). In contrast to adults, most infected children are asymptomatic or have only mild clinical manifestations. The existing COVID-19 clinical practice guidelines for public health policies have mostly focused on the prevention, diagnosis and treatment in adults, with little attention paid to children. Few of them are based on evidence from systematic reviews (14). Based on the above considerations, an international multidisciplinary working group developed this rapid advice guideline for management of children with COVID-19 using the methods and process proposed by the WHO and GRADE working group (15-17). We present the following article in accordance with the RIGHT reporting checklist (available at http://dx.doi.org/10.21037/atm-20-3754).
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| 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