Low Molecular Weight Heparin for Venous Thromboembolism Prophylaxis in Urologic Oncologic Surgery
Bibliographic record
Abstract
OBJECTIVES: This is a prospective study in the use of low molecular weight heparin (LMWH) for venous thromboembolism prophylaxis in the previously unstudied subset of patients undergoing elective urologic cancer surgery. METHODS: Thirty-eight patients undergoing elective urologic surgery were studied. Thirty-six had urologic malignancies. Pre-operative risk factors for venous thromboembolic disease were recorded. All patients received LMWH (dalteparin, Fragmin; Pharmacia, Stockholm, Sweden) subcutaneously on a daily basis beginning 1-2 hr before surgery and lasting for 3-7 days. Postoperative physical examination was used to check for clinical evidence of deep venous thrombosis (DVT). Clinical parameters such as physical examination and radiological testing were used to assess for evidence of DVT. Other data included intraoperative blood loss, transfusion requirements, postoperative bleeding complications, postoperative hematocrit and coagulation profiles, and local complications related to the subcutaneous injection of the LMWH. RESULTS: All patients completed the prophylaxis protocol. None developed DVT. Mean intraoperative blood loss was 735 mL and 12 patients received an average of 1 unit of blood transfusion. No unusual hemorrhagic events were noted intra- or post-operatively. No reactions to the LMWH were noted. Average hematocrit of postoperative day 3 was 30.7 and platelet count and coagulation profiles remained normal postoperatively. CONCLUSIONS: Low molecular weight heparins appear promising for DVT prophylaxis in high-risk urology patients.
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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 | 0.001 | 0.003 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".