Risk factors associated with venous thromboembolism after hepatectomy in oncology patients
Bibliographic record
Abstract
BACKGROUND: Liver resection increases venous thromboembolism (VTE) risk due to malignancy-related hyper-coagulopathy and surgical inflammation. Current guidelines recommend early post-operative and extended pharmacologic prophylaxis for all patients but lack stratification by patient or surgical factors. Despite these guidelines, surgeon preferences influence prophylaxis practices. This study aimed to identify clinical factors associated with VTE following liver resection. METHODS: Using data from the Hemorrhage During Liver Resection (HeLiX) trial, a randomized clinical trial of patients undergoing liver resection for cancer, univariate comparisons and logistic regression were performed. RESULTS: Study cohort VTE incidence was 4.1 %. Multivariable analysis identified major liver resection (odds ratio (OR) 2.59, 95 % confidence interval (CI) 1.38-5.03) and higher estimated blood loss (EBL) (OR 1.14 per 500 mL increase, 95 % CI 1.03-1.26) as associated with increased risk. Surgical duration (OR 1.14 per hour increase, 95 % CI 0.95-1.34) and use of tranexamic acid (OR 1.77, 95 % CI 0.98-3.27) did not reach statistical significance. VTE rate was highly dependent on extent of resection (1-2 segments, 1.7 %; 3-4 segments, 5.4 %; >4 segments, 6.7 %). CONCLUSION: Major resection and increased EBL are associated with higher risk of VTE. These patients may warrant more intensive prophylax compared to those having minor resections with minimal blood loss.
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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) | 0.000 | 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".