MANAGEMENT OF DENTAL EXTRACTIONS IN PATIENTS TAKING WARFARIN AS ANTICOAGULANT TREATMENT: A SYSTEMATIC REVIEW.
Bibliographic record
Abstract
OBJECTIVES: The management of patients on anticoagulation therapy is challenging. The objective of this study was to conduct a systematic review to establish the effectiveness of hemostatic interventions to prevent postoperative bleeding following dental extractions among patients taking warfarin. METHODS: A systematic review of the literature was conducted using PubMed, EMBASE and the Cochrane Central Register of Controlled Trials databases and applying relevant MeSH terms. Identified studies were screened independently by 2 reviewers using the following selection criteria: tooth extraction, patients taking warfarin as the only anticoagulant, randomized controlled trials and a hemostatic intervention. RESULTS: Six articles were included in the final review, all evaluating different interventions. Oral or local hemostatic agents were compared in 4 studies where patients continued taking warfarin before and after the procedure; in 3 studies, there were no differences between the agents in preventing postoperative bleeding and, in 1, Histoacryl glue was superior to a gelatin sponge. Two studies compared warfarin continuation with temporary discontinuation and found that continuation did not increase the risk of bleeding in patients who had an international normalized ratio (INR) within the therapeutic range. CONCLUSIONS: Patients with an INR within the therapeutic range can safely continue taking the regular dose of warfarin before dental extractions. There is no evidence to support or reject the superiority of local hemostatic agents over warfarin discontinuation.
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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 | 0.004 | 0.022 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.005 |
| Bibliometrics | 0.007 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".