Postoperative low molecular weight heparin bridging treatment for patients at high risk of arterial thromboembolism (PERIOP2): double blind randomised controlled trial
Bibliographic record
Abstract
OBJECTIVE: To determine the efficacy and safety of dalteparin postoperative bridging treatment versus placebo for patients with atrial fibrillation or mechanical heart valves when warfarin is temporarily interrupted for a planned procedure. DESIGN: Prospective, double blind, randomised controlled trial. SETTING: 10 thrombosis research sites in Canada and India between February 2007 and March 2016. PARTICIPANTS: 1471 patients aged 18 years or older with atrial fibrillation or mechanical heart valves who required temporary interruption of warfarin for a procedure. INTERVENTION: Random assignment to dalteparin (n=821; one patient withdrew consent immediately after randomisation) or placebo (n=650) after the procedure. MAIN OUTCOME MEASURES: Major thromboembolism (stroke, transient ischaemic attack, proximal deep vein thrombosis, pulmonary embolism, myocardial infarction, peripheral embolism, or vascular death) and major bleeding according to the International Society on Thrombosis and Haemostasis criteria within 90 days of the procedure. RESULTS: The rate of major thromboembolism within 90 days was 1.2% (eight events in 650 patients) for placebo and 1.0% (eight events in 820 patients) for dalteparin (P=0.64, risk difference -0.3%, 95% confidence interval -1.3 to 0.8). The rate of major bleeding was 2.0% (13 events in 650 patients) for placebo and 1.3% (11 events in 820 patients) for dalteparin (P=0.32, risk difference -0.7, 95% confidence interval -2.0 to 0.7). The results were consistent for the atrial fibrillation and mechanical heart valves groups. CONCLUSIONS: In patients with atrial fibrillation or mechanical heart valves who had warfarin interrupted for a procedure, no significant benefit was found for postoperative dalteparin bridging to prevent major thromboembolism. TRIAL REGISTRATION: Clinicaltrials.gov NCT00432796.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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".