Anticoagulation with osocimab in patients with kidney failure undergoing hemodialysis: a randomized phase 2 trial
Bibliographic record
Abstract
Individuals with kidney failure undergoing hemodialysis are at elevated risk for thromboembolic events. Factor (F) XI, which is in the intrinsic pathway of coagulation, is emerging as an attractive target for new anticoagulants that may be safer than existing agents. Osocimab-an inhibitory FXIa antibody-is a potential treatment option for such patients. We conducted a phase 2b, double-blind, placebo-controlled trial, in which 704 participants (448 male, 256 female) with kidney failure undergoing hemodialysis were randomized to receive lower- or higher-dose osocimab or placebo. In total, 686 participants (436 male, 250 female) received treatment for ≤18 months (planned minimal treatment period of 6 months). The co-primary outcomes were clinically relevant bleeding (a composite of major and clinically relevant nonmajor bleeding) and a composite of the incidence of moderate, severe or serious adverse events. Clinically relevant bleeding occurred in 16/232 (6.9%) and 11/224 (4.9%) participants who received lower- and higher-dose osocimab, respectively, and in 18/230 participants (7.8%) who received a placebo. For the composite adverse event endpoint, incidences were 51%, 47% and 43% in the lower-dose osocimab, higher-dose osocimab and placebo groups, respectively. These results suggest that osocimab is associated with a low risk of bleeding and is generally well tolerated in this population; findings that require confirmation in larger trials. ClinicalTrials.gov identifier, NCT04523220 .
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".