Antithrombotic prophylaxis in children and adolescents' patients with SARS-CoV-2 (COVID-19) infection: A practical guidance for clinicians.
Bibliographic record
Abstract
Severe coronavirus disease 2019 (COVID-19) is often associated with features of hypercoagulable state which can manifest as venous thromboembolism (VTE) and/or microthrombosis. Given the high risk of VTE in critically ill COVID-19 patients, appropriate VTE prophylaxis seems to be an important part of managing these patients. Although many protocols regarding venous thromboembolism (VTE) prophylaxis or therapeutic (full-dose) anticoagulation have been conducted worldwide, primarily in hospitalised adult patients, details on paediatric patients, if included, are limited or incomplete. The current evidences suggest that anticoagulation therapy with low molecular weight heparins (LMWH) appears to be associated with better prognosis in patients with moderate to severe COVID-19 induced coagulopathies or elevated D-dimer levels. Our recommendations are intended to offer guidance for anticoagulation prophylaxis and treatment in COVID-19 children and adolescent patients and not intend to supersede the clinician judgement. We are also conscious that several clinical questions deserve further studies and clarifications because this area is rapidly evolving.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.008 | 0.004 |
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 source (direct Gemma or distilled Codex), 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".