Thrombosis and Thromboprophylaxis in Pediatric Patients Admitted with COVID-19 Infection -- A Prospective Multicenter Observational Cohort Study
Bibliographic record
Abstract
Background/Objectives: A striking procoagulant state induced by SARS-CoV-2 (COVID-19) infection has been reported in adults, with many hospitalized patients developing thrombosis despite prophylactic anticoagulation. Reports on the characteristics of COVID-19-associated coagulopathy are scarce in the pediatric population and thromboprophylaxis use is heterogeneous across pediatric centers. To characterize laboratory and clinical outcomes of COVID-19-associated coagulopathy in children and to assess prophylactic anticoagulation use. Design/Methods: Prospective multicenter observational cohort study including all patients from 0 to 18 years of age admitted to one of the pediatric university health centers in the province of Québec, Canada, with confirmed COVID-19 infection from February 1 to July 1, 2021. Patient-level data including laboratory parameters, treatment and outcomes were obtained via chart review. Results: Included were 79 children hospitalized with COVID-19-related symptoms, multisystem inflammatory syndrome in children or an incidental finding of asymptomatic infection. When assessed, hemostatic parameters demonstrated elevation in D-dimers in 94.7%, fibrinogen in 60%, prothrombin time in 51.9%, and activated thromboplastin time in 18.5%. Platelet counts were normal in 91.3% of patients. Ten patients (12.3%) received thromboprophylaxis with low molecular weight heparin, 7 (8.9%) with aspirin and 1 (1.3%) with both. We observed one thrombosis and one major bleed, both attributable to an alternate diagnosis other than COVID-19 infection. Conclusion: The most consistent abnormal hemostatic parameters observed in this study were elevated D-dimers and fibrinogen. No thrombosis ascribable to COVID-19 infection has been observed in this pediatric cohort, despite relatively infrequent anticoagulant prophylaxis. There have been no bleeding events attributable to thromboprophylaxis.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".