Characteristics of Upper and Lower Extremity Deep Vein Thrombosis and Predictors of Post-Thrombotic Syndrome in Children
Bibliographic record
Abstract
Our understanding of postthrombotic syndrome (PTS) predictors in children is evolving. The present study aimed to investigate differences in patient- and deep vein thrombosis (DVT)-related characteristics between central venous catheter (CVC)-related and non-CVC-related thrombosis in children, as well as early PTS predictors. Children aged 0 to 18 years were prospectively recruited ≥6 months after imaging-proven upper- or lower-extremity DVT. PTS was measured using CAPTSure. Early predictors included age at DVT diagnosis, DVT symptoms, DVT burden, and days on therapeutic anticoagulation within 30 days post-DVT diagnosis. Analysis of predictors was stratified by CVC-related and non-CVC-related thrombosis. Generalized estimating equations were used for data analyses. In total, 313 DVT-affected extremities of 256 patients were assessed; 275 (88%) DVT cases were CVC related. Patients with non-CVC-related thrombosis were older (median age, 5.8 years; 25th-75th percentile, 4.9-6.4 years vs 3.5 months; 25th-75th percentile, 0.7-18.7 months; P < .001) and more likely to have thrombophilia (64% vs 22%; P < .001) and obesity (30% vs 13%; P = .01) than patients with CVC-related thrombosis. CAPTSure scores were 9.5 points higher (standard error, 3.0; P = .02) in the non-CVC-related thrombosis stratum. Age at the time of DVT predicted PTS in both strata; DVT burden and time from DVT diagnosis to PTS assessment predicted PTS in CVC-related thrombosis. In sum, PTS severity was higher in non-CVC-related vs CVC-related thrombosis. Increasing age at the time of DVT was associated with higher PTS severity. DVT burden and time from DVT diagnosis to PTS assessment were significant PTS predictors in CVC-related thrombosis, indicating that long-term follow-up of these children is important.
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How this classification was reachedexpand
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".