Antiphospholipid antibiodies: a critical review of the literature
Bibliographic record
Abstract
PURPOSE OF REVIEW: The antiphospholipid antibody syndrome is defined by the presence of antiphospholipid antibodies in patients with recurrent venous or arterial thromboembolism or pregnancy morbidity. Antithrombotic therapies are the mainstay of treatment to reduce the risk of recurrent thromboembolism that characterizes this condition. RECENT FINDINGS: Limitations in the laboratory testing for antiphospholipid antibodies and changes in the diagnostic criteria for antiphospholipid antibody syndrome are important to recognize as they will affect the type of patients enrolled in the clinical trials evaluating antiphospholipid antibody syndrome therapies. In this review, we discuss the laboratory testing and diagnostic criteria for antiphospholipid antibody syndrome, and examine the evidence supporting the optimal antithrombotic management of patients with antiphospholipid antibodies. Studies addressing the management of patients with antiphospholipid antibodies and venous thromboembolism, and antiphospholipid antibodies and ischemic stroke, will be critically reviewed. SUMMARY: Clinical trials and observational studies have evaluated the optimal type, intensity and duration of anticoagulant therapy in patients with antiphospholipid antibodies. Critical evaluation of these studies is required to assess the generalizability of the results and how these results may be applicable to individual 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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".