Anticoagulant-Related Bleeding in Older Persons With Atrial Fibrillation
Bibliographic record
Abstract
BACKGROUND: Many studies have documented the underuse of anticoagulant (ie, warfarin sodium) therapy as stroke prophylaxis in older persons with atrial fibrillation. Failure to prescribe anticoagulant agents to these patients is often due to physicians' perceiving the risk of major bleeding as unacceptably high because of the presence of such clinical risk factors as hypertension, falls, a history of gastrointestinal tract bleeding, and lack of assurance about compliance. OBJECTIVES: To critically appraise whether the presence of additional clinical factors that increase the risk of bleeding affects the chance of anticoagulant-related hemorrhage, and to develop an approach to the use of anticoagulant agents in older patients with atrial fibrillation who have any of these factors. METHODS: Systematic MEDLINE literature search from January 1966 to March 2002. RESULTS: Many of the factors that are purported to be barriers to anticoagulant therapy in older persons with atrial fibrillation probably should not influence the choice of stroke prophylaxis in these patients. These include previous episodes of upper gastrointestinal tract bleeding, predisposition to falling, and old age in itself. For some other factors, such as alcoholism, participation in activities that predispose to trauma, the presence of a bleeding diathesis or thrombocytopenia, and noncompliance with monitoring, there is little or conflicting evidence about their effect on anticoagulant-related bleeding. However, they should be considered in the clinical decision-making process. CONCLUSIONS: For many older patients with atrial fibrillation, physicians' fears of the risk of bleeding in association with anticoagulant therapy are often exaggerated and unfounded. Therefore, the salient issue in selecting older patients with atrial fibrillation for anticoagulation is accurately estimating their stroke risk, with bleeding risk during anticoagulation being a lesser issue, relevant to only a few patients.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 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) | 0.000 | 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".