Perioperative Anticoagulation in Patients with Mechanical Heart Valves Undergoing Elective Surgery: Results of a Survey Conducted among Korean Physicians
Bibliographic record
Abstract
The optimal perioperative anticoagulation management in patients on warfarin therapy is poorly defined due to the lack of randomized trials. Because guidelines are heterogeneous, it was hypothesized that "treatment strategies are not uniform in clinical practice". Between February 2003 and May 2003, a questionnaire with 4 different clinical scenarios was distributed to physicians by e-mail, or direct contact was made by a survey monitor. Two scenarios described the cases of patients with a mechanical heart valve (MHV) in the mitral position, with additional risk factors for a systemic embolism; one undergoing major (scenario 1) and the other minor surgery (scenario 3). Two scenarios described patients with an aortic MHV; one undergoing major (scenario 2) and the other minor (scenario 4) surgery. Different preoperative and postoperative management options were offered. The treatment options for all scenarios were the same. Of the 90 questionnaires distributed, 52 (57.8%) were returned. Hospitalization for full-dose intravenous unfractionated heparin (IV UH) was the most commonly selected strategy in the preoperative phase for scenarios 1 (59%), 2 (42%) and 3 (44%). In scenario 4, 34% chose IV UH. Outpatient, full- dose, subcutaneous UH or low-molecular-weight heparin (LMWH) was the most selected option in the postoperative phase for all scenarios, with the exception of number 4 (52.9% in scenario 1, 34% in scenario 2, 32%, in scenario 3 and 28% in scenario 4). Even among expert clinicians, the management of perioperative anticoagulation is heterogeneous. In particular, the definition of risk categories and the optimal intensity of antithrombotic drugs need to be defined by well-designed prospective studies.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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".