Perioperative anticoagulation in patients with chronic atrial fibrillation who are undergoing elective surgery: results of a physician survey.
Bibliographic record
Abstract
OBJECTIVE: To survey physicians' anticoagulation preferences in patients with chronic atrial fibrillation who are undergoing elective surgery. MATERIALS AND METHODS: A survey was performed that asked physicians to provide pre- and postoperative anticoagulation preferences for two clinical scenarios of patients with chronic atrial fibrillation (high stroke risk, low stroke risk) undergoing elective surgery. In addition to the interruption of warfarin therapy, perioperative anticoagulation options were as follows: a) in-hospital full dose intravenous heparin; b) outpatient full dose subcutaneous unfractionated heparin or low molecular weight heparin (LMWH); c) low dose unfractionated heparin or LMWH (postoperative only); d) nothing other than stopping warfarin preoperatively and restarting it postoperatively; or e) another anticoagulant strategy. RESULTS: In the high stroke risk scenario, the proportions of respondents preferring anticoagulation options a, b, d and e in the preoperative period were 24%, 20%, 54% and 2%, respectively; the proportions preferring options a, b, c, d and e in the postoperative period were 35%, 13%, 15%, 35% and 1%, respectively. In the low stroke risk scenario, the proportions of respondents preferring options a, b, d and e in the preoperative period were 7%, 10%, 80% and 3%, respectively; the proportions preferring options a, b, c, d and e in the postoperative period were 11%, 9%, 10%, 68% and 2%, respectively. CONCLUSIONS: In patients with chronic atrial fibrillation who underwent elective surgery, perioperative anticoagulant management preferences varied widely in patients at high risk for stroke, but were more uniform and less aggressive in patients at low risk for stroke.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.002 | 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".