Can thrombophilia predict recurrent catheter-related deep vein thrombosis in children?
Bibliographic record
Abstract
The role of thrombophilia testing in predicting catheter-related deep vein thrombosis (DVT) after an incident (ie, first) catheter-related DVT in children remains unclear. The present study investigated the association between thrombophilia and recurrent catheter-related DVT. Children with thrombophilia testing, performed according to the clinician's judgment and the family's preference, and a history of objectively confirmed catheter-related DVT were included in the study. Recurrent catheter-related DVT after placement of a new catheter was the main outcome. Thrombophilia was classified as minor, major, or none. Analysis was conducted using mixed effect logistic regression. A total of 245 patients had 1,365 catheters inserted; 941 of these catheters were placed after the incident catheter-related DVT. Anticoagulants as treatment or prophylaxis were administered in 78.1% of inserted catheters for at least 50% of the time they were in place. Minor thrombophilia was found in 12.7% of patients, whereas major thrombophilia was seen in 8.2% of children. The incidence rate of recurrent events was 0.23/100 catheter-days (95% confidence interval, 0.19-0.28 catheter-days); 34.3% (95% confidence interval, 28.6%-40.0%) of patients requiring a new catheter after their incident thrombotic event had at least 1 recurrent event. The incidence proportion of bleeding complications was 4.6/100 patients receiving anticoagulation. Young age of the patient at the time of catheter insertion and lack of administration of treatment or prophylactic doses of anticoagulant were predictive of recurrent events. In contrast, thrombophilia was not predictive of recurrent catheter-related DVT during subsequent catheter insertions among tested patients. Our findings suggest that thrombophilia testing to predict recurrence in these patients may be unnecessary.
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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 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| 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".