Improving the Effectiveness of Anticoagulant Therapy: The Promise of Factor XI Inhibition
Bibliographic record
Abstract
This continuing medical education-accredited symposium, held at the 2023 International Society for Thrombosis and Haemostasis (ISTH) congress in Montréal, Canada, focused on current unmet needs in anticoagulation, especially in the atrial fibrillation (AF) population, and reflected on the promise of the emerging class of Factor XI inhibitors for stroke prevention (SPAF) in susceptible patients. The faculty agreed that, although direct oral anticoagulants (DOAC) have represented a major advance compared with vitamin K antagonists, their utilisation remains suboptimal, often due to the prevailing fear of bleeding in many types of patients. Older age alone can be a reason for withholding anticoagulation, due to the risk and implications of bleeding. Frailty and comorbidities, such as chronic kidney disease (CKD), which can adversely affect the bioavailability of DOACs, are also deterrents to optimal anticoagulant use. Clinicians may try to avoid or mitigate bleeding by inappropriately prescribing low doses of DOACs, an off-label practice that has been found to fail to protect patients from thrombotic risk, without attenuating the risk of bleeding. In addition, the potential for drug-drug interactions and poor adherence also limit the optimal use of DOACs in real-world clinical practice. A recent patient survey focusing on the topic of ‘minor bleeding’, often referred to by clinicians as ‘nuisance bleeding’, and typically not well captured in clinical trials, revealed the far-reaching impact of ongoing problems with bleeding on quality of life, and the possibility that these experiences may deter patients from adherence to their prescribed anticoagulant regimen. Factor XI represents a promising new target for anticoagulation, which may minimise the risk of bleeding by pharmacologically ‘uncoupling’ the clotting pathway, leading to pathological thrombosis from the cascade largely responsible for physiological haemostasis. Phase II research with investigational Factor XI inhibitors has established their antithrombotic and safety potential, and some of these agents may also avoid other practical drawbacks of DOACs. Phase III evaluation of Factor XI inhibition is ongoing in a number of clinical settings.
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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 | 0.014 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.005 | 0.006 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.004 | 0.013 |
| Insufficient payload (model declined to judge) | 0.006 | 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".