A Multinational Study of Thromboprophylaxis Practice in Critically Ill Children*
Bibliographic record
Abstract
OBJECTIVES: Although critically ill children are at increased risk for developing deep venous thrombosis, there are few pediatric studies establishing the prevalence of thrombosis or the efficacy of thromboprophylaxis. We tested the hypothesis that thromboprophylaxis is infrequently used in critically ill children even for those in whom it is indicated. DESIGN: Prospective multinational cross-sectional study over four study dates in 2012. SETTING: Fifty-nine PICUs in Australia, Canada, New Zealand, Portugal, Singapore, Spain, and the United States. PATIENTS: All patients less than 18 years old in the PICU during the study dates and times were included in the study, unless the patients were 1) boarding in the unit waiting for a bed outside the PICU or 2) receiving therapeutic anticoagulation. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: Of 2,484 children in the study, 2,159 (86.9%) had greater than or equal to 1 risk factor for thrombosis. Only 308 children (12.4%) were receiving pharmacologic thromboprophylaxis (e.g., aspirin, low-molecular-weight heparin, or unfractionated heparin). Of 430 children indicated to receive pharmacologic thromboprophylaxis based on consensus recommendations, only 149 (34.7%) were receiving it. Mechanical thromboprophylaxis was used in 156 of 655 children (23.8%) 8 years old or older, the youngest age for that device. Using nonlinear mixed effects model, presence of cyanotic congenital heart disease (odds ratio, 7.35; p < 0.001) and spinal cord injury (odds ratio, 8.85; p = 0.008) strongly predicted the use of pharmacologic and mechanical thromboprophylaxis, respectively. CONCLUSIONS: Thromboprophylaxis is infrequently used in critically ill children. This is true even for children at high risk of thrombosis where consensus guidelines recommend pharmacologic 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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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) | 0.002 | 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".