Thrombosis and anticoagulation in the setting of renal or liver disease
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Thrombosis and bleeding are among the most common causes of morbidity and mortality in patients with renal disease or liver disease. The pathophysiology underlying the increased risk for venous thromboembolism and bleeding in these 2 populations is distinct, as are considerations for anticoagulation. Anticoagulation in patients with kidney or liver disease increases the risk of bleeding; this risk is correlated with the degree of impairment of anticoagulant elimination by the kidneys and/or liver. Despite being in the same pharmacologic category, anticoagulant agents may have varied degrees of renal and liver metabolism. Therefore, specific anticoagulants may require dose reductions or be contraindicated in renal impairment and liver disease, whereas other drugs in the same class may not be subject to such restrictions. To minimize the risk of bleeding, while ensuring an adequate therapeutic effect, both appropriate anticoagulant drug choices and dose reductions are necessary. Renal and hepatic function may fluctuate, further complicating anticoagulation in these high-risk patient groups.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 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) | 0.000 | 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 it