Timing of Pharmacologic Venous Thromboembolism Prophylaxis in Severe Traumatic Brain Injury: A Propensity-Matched Cohort Study
Bibliographic record
Abstract
BACKGROUND: Patients with severe traumatic brain injury (sTBI) are at high risk for developing venous thromboembolism (VTE). Nonetheless, pharmacologic VTE prophylaxis is often delayed out of concern for precipitating extension of intracranial hemorrhage (ICH). The purpose of this study was to compare the effectiveness of early vs late VTE prophylaxis in patients with sTBI, and to characterize the risk of subsequent ICH-related complication. STUDY DESIGN: Adults with isolated sTBI (head Abbreviated Injury Scale score ≥3 and total Glasgow Coma Scale score ≤8) who received VTE prophylaxis with low-molecular-weight or unfractionated heparin were derived from the American College of Surgeons Trauma Quality Improvement Program (2012 to 2014). Patients were divided into EP (<72 hours) or LP (≥72 hours) groups. Propensity score matching was used to minimize selection bias. The primary end point was VTE (pulmonary embolism or deep vein thrombosis). Secondary outcomes were defined as late neurosurgical intervention (≥72 hours) or death. RESULTS: We identified 3,634 patients with sTBI. Early prophylaxis was given in 43% of patients. Higher head injury severity, presence of ICH, and early neurosurgery were associated with late prophylaxis. Propensity score matching yielded a well-balanced cohort of 2,468 patients. Early prophylaxis was associated with lower rates of both pulmonary embolism (odds ratio = 0.48; 95% CI, 0.25-0.91) and deep vein thrombosis (odds ratio = 0.51; 95% CI, 0.36-0.72), but no increase in risk of late neurosurgical intervention or death. CONCLUSIONS: In this observational study of patients with sTBI, early initiation of VTE prophylaxis was associated with decreased risk of pulmonary embolism and deep vein thrombosis, but no increase in risk of late neurosurgical intervention or death. Early prophylaxis may be safe and should be the goal for each patient in the context of appropriate risk stratification.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| 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".