Low molecular weight heparin versus unfractionated heparin for perioperative thromboprophylaxis in patients with cancer
Bibliographic record
Abstract
BACKGROUND: The choice of the appropriate perioperative thromboprophylaxis in patients with cancer depends on the relative benefits and harms of low molecular weight heparin (LMWH) and unfractionated heparin (UFH). OBJECTIVES: To systematically review the evidence for the relative efficacy and safety of LMWH and UFH for perioperative thromboprophylaxis in patients with cancer. SEARCH METHODS: A comprehensive search for trials of anticoagulation in cancer patients including a February 2010 electronic search of: the Cochrane Central Register of Controlled Trials (CENTRAL), MEDLINE, EMBASE and ISI Web of Science. SELECTION CRITERIA: Randomized controlled trials (RCTs) that enrolled cancer patients undergoing a surgical intervention and compared the effects of LMWH to UFH on mortality, deep venous thrombosis (DVT), pulmonary embolism (PE), bleeding outcomes, and thrombocytopenia. DATA COLLECTION AND ANALYSIS: Two review authors used a standardized form to independently extract in duplicate data on risk of bias, participants, interventions and outcomes of interest. Where possible, we conducted meta-analyses using the random-effects model. MAIN RESULTS: Of 8187 identified citations, we included 16 RCTs with 11,847 patients in the meta-analyses, all using preoperative prophylactic anticoagulation. The overall quality of evidence was moderate. The meta-analysis did not conclusively rule out either a beneficial or harmful effect of LMWH compared to UFH for the following outcomes: mortality (RR = 0.90; 95% CI 0.73 to 1.10), symptomatic DVT (RR = 0.73; 95% CI 0.23 to 2.28), PE (RR = 0.59; 95% CI 0.25 to1.41), minor bleeding (RR = 0.88; 95% CI 0.47 to 1.66) and major bleeding (RR = 0.84; 95% CI 0.52 to 1.36). LMWH was associated with lower incidence of wound hematoma (RR = 0.60; 95% CI 0.43, 0.84) while UFH was associated with higher incidence of intra-operative transfusion (RR = 1.16; 95% CI 0.69,1.62). AUTHORS' CONCLUSIONS: We found no difference between perioperative thromboprophylaxis with LMWH verus UFH in their effects on mortality and embolic outcomes in patients with cancer. Further trials are needed to more carefully evaluate the benefits and harms of different heparin thromboprophylaxis strategies in this population.
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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 | 0.017 | 0.065 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.011 | 0.016 |
| Bibliometrics | 0.007 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".