Bleeding Risk in Elderly Patients with Venous Thromboembolism Who Would Have Been Excluded from Anticoagulation Trials
Bibliographic record
Abstract
Older patients with venous thromboembolism (VTE) are underrepresented in clinical anticoagulation trials. We examined to which extent elderly patients with VTE would be excluded from such trials and compared the bleeding risk between hypothetically excluded and enrolled patients. We studied 991 patients aged ≥65 years with acute VTE in a prospective multicenter cohort. We identified 12 landmark VTE oral anticoagulation trials from the eighth and updated ninth American College of Chest Physician Guidelines. For each trial, we abstracted the exclusion criteria and calculated the proportion of our study patients who would have been excluded from trial participation. We examined the association between five common exclusion criteria (hemodynamic instability, high bleeding risk, comorbidity, co-medication, and invasive treatments) and major bleeding (MB) within 36 months using competing risk regression, adjusting for age, sex, and periods of anticoagulation. A median of 31% (range: 20-52%) of our patients would have been excluded from participation in the landmark trials. Hemodynamic instability (sub-hazard ratio [SHR]: 2.2, 95% CI: 1.1-4.7), comorbidity (SHR: 1.5, 95% CI: 1.1-2.2), and co-medication (SHR: 1.5, 95% CI: 1.0-2.3) were associated with MB. Compared to eligible patients, those with ≥2 exclusion criteria had a twofold (SHR: 2.16, 95% CI: 1.38-3.39) increased risk of MB. Overall, about one-third of older patients would not be eligible for participation in guideline-defining VTE anticoagulation trials. The bleeding risk increases significantly with the number of exclusion criteria present. Thus, results from such trials may not be generalizable to older, multimorbid, and co-medicated patients.
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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 | 0.010 | 0.040 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".