Clinical factors influencing normalization of prothrombin time after stopping warfarin: a retrospective cohort study
Bibliographic record
Abstract
BACKGROUND: Anticoagulation with warfarin should be stopped 4-6 days before invasive procedures to avoid bleeding complications. Despite this routine, some patients still have high International Normalized Ratio (INR) values on the day of surgery and the procedure may be cancelled. We sought to identify easily available clinical characteristics that may influence the rate of normalization of prothrombin time when warfarin is stopped before surgery or invasive procedures. METHODS: Clinical data were collected retrospectively from consecutive cases from two cohorts, who stopped warfarin 6 days before surgery. An INR value of 1.6 or higher on the day of surgery or requirement for reversal with vitamin K the day before surgery were criteria for slow return (S) to normal INR. RESULTS: Of 202 patients, 14 (7%) were classified as S. Eight of the S-patients required reversal with vitamin K one day before surgery and in another case surgery was cancelled due to high INR. Baseline INR was the only variable significantly associated with classification as S in stepwise logistic regression analysis (p = 0.003). The odds ratio for being in the normal group was 0.27 (95% confidence interval 0.12-0.62) for each unit baseline INR increased. The positive predictive value of baseline INR with a cut off at > 3.0 was only 15% and for INR > 3.5 it was 33%. CONCLUSION: Baseline INR, but not the size of the maintenance dose, is associated with the rate of normalization of prothrombin time after stopping warfarin, but it has limited utility as predictor in clinical practice. Whenever normal hemostasis is considered crucial for the safety, the INR should be checked again before the invasive procedure.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| 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 | 0.000 |
| 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 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".