Bibliographic record
Abstract
The antiphospholipid antibody syndrome (APS) is defined by the persistent presence of antiphospholipid antibodies in patients with recurrent venous or arterial thromboembolism or pregnancy morbidity. Anti-thrombotic therapy is the mainstay of treatment given the high risk of recurrent thromboembolism that characterizes this condition. Despite the prothrombotic nature of APS, thrombocytopenia is present in a proportion of patients. which can complicate management and limit the use of antithrombotic therapy. The mechanism of APS-associated thrombocytopenia is multifactorial and its relation to thrombotic risk poorly characterized. However, the presence of thrombocytopenia does not appear to reduce thrombotic risk in patients with APS, who can develop thromboembolic complications necessitating antithrombotic treatment. In these cases, treatment of the thrombocytopenia may be necessary to facilitate administration of antithrombotic agents. Clinical trials have demonstrated that patients with antiphospholipid antibodies and venous thromboembolism should be treated with vitamin K antagonists (warfarin); that ischemic stroke may be treated with aspirin or warfarin; and that women with recurrent pregnancy loss should receive prophylactic-dose heparin and aspirin. However, application of these trial results to patients with APS-associated thrombocytopenia can be challenging since there are limited data on the optimal use of antithrombotic agents in this setting. Issues such as determining the platelet threshold at which antithrombotic agents can be safely used and managing patients with both bleeding and thromboembolic complications remain unresolved. Ultimately the risks and benefits of antithrombotic therapy, balanced against the severity of the thrombocytopenia and its potential bleeding risks, need to be assessed using an individualized patient approach.
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.
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) | 0.001 | 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) | 0.018 | 0.005 |
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".