Oral Anticoagulation Treatment in the Elderly
Bibliographic record
Abstract
BACKGROUND: Whether elderly patients are at increased risk of complications during oral anticoagulant treatment (OAT) is still a matter of debate. METHOD: Bleeding and thrombotic events occurring during OAT in 461 patients, aged 75 years or older when they started OAT, and in 461 patients younger than 70 years, matched for sex, OAT indication, and treating center, were examined in a prospective, multicenter, inception-cohort study. RESULTS: Bleeding rate was 9.9% and 6.6% patient-years in elderly and young patients, respectively (P = .07), and 2.1% and 1.1% for major bleeding (P = .19); 6 and 1 events, respectively, were fatal (all intracranial, relative risk, 6.4; P = .05). In the elderly, bleeding rate was lower (4.5%) for international normalized ratios (INRs) between 2.0 and 2.9; it was higher during the first 90 treatment days (P = .05) and when arterial vascular disease was the indication for OAT (P = .03). Thrombosis rate was 4.2% and 2.5% patient-years in elderly and young patients, respectively (P = .10); however, 13 and 5 events were fatal (relative risk, 2.8; P = .04). Thrombosis rate was lower (1.5%) for INRs between 2.0 and 2.9; it was higher during the first 90 treatment days (P<.001) and 6 of 7 venous events occurred at lower than 2.0 INRs. CONCLUSIONS: A nonsignificant trend was noted toward a higher rate of both bleeding and thrombotic complications in elderly vs matched younger patients. Intracranial bleeding and fatal thrombotic events were significantly more frequent in the elderly. Our results also indicate that lower than 2.0 INRs do not preclude bleeding in the elderly nor offer adequate protection from thrombotic events. Moderate anticoagulation (2.0-3.0 INRs) in elderly patients seems the safest and most effective.
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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 | 0.000 | 0.002 |
| 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 | 0.000 |
| 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 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".