Clinical factors influencing the sensitivity to warfarin when restarted after surgery
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVE: Resumption of oral anticoagulation after surgery may result in a different maintenance dose of warfarin than before the procedure. Knowledge of the clinical determinants of postoperative response could help avoid excessive anticoagulation in sensitive patients or avoid extended delays in achieving a therapeutic level in resistant patients. DESIGN: Retrospective review. SUBJECTS: Two hundred warfarin-treated patients who were managed by our clinic for surgery. OUTCOME: Two independent adjudicators classified the postoperative response to warfarin as Resistant, Normal or Sensitive, based on previous maintenance dose, international normalized ratio (INR) on the day of resumption, number of days until INR of >1.9 and doses of warfarin given. A third adjudicator resolved disagreements. Clinical data were extracted from the patient records and correlated with the response. RESULTS: Interobserver agreement for classification of postoperative response was moderate (weighted kappa 0.46) with 37 (18.5%) considered resistant, 135 (67.5%) normal, 27 (13.5%) sensitive and one patient was not classifiable. The main type of surgery was cardiac. In univariable analysis only addition of amiodarone after surgery was associated with a sensitive response (P = 0.04). After adjustment for all other factors with an ordered categorical response, amiodarone remained as the sole independent risk factor (P = 0.02) for a sensitive response, odds ratio 0.41 (95% confidence interval 0.19-0.89) for Normal instead of Sensitive or for Resistant instead of Normal. CONCLUSION: Altered sensitivity to warfarin occurs in about one-third of patients after surgery and can be predicted by the introduction of concomitant amiodarone therapy but not by patient factors or the nature of the procedure. Changes in concomitant medications after surgery should alert doctors of the potential for increased sensitivity to warfarin.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".