Bibliographic record
Abstract
PURPOSE OF REVIEW: The antiphospholipid antibody syndrome (APS) is characterized by arterial or venous thrombosis or pregnancy morbidity in patients with persistent antiphospholipid antibodies (aPL). Experimental data supporting activation of the complement cascade has provided critical insight into the underlying pathophysiology of aPL-induced pregnancy loss and thrombosis. RECENT FINDINGS: Although the mechanism by which pregnancy loss and thrombosis is incompletely elucidated, studies using mice deficient in complement components and specific inhibitors to complement have demonstrated that activation of complement contributes to fetal loss, growth restriction and thrombosis. Inhibition of complement activation can prevent these complications. Use of a specific complement inhibitor to C5 has been used successfully in a patient with catastrophic APS undergoing renal transplantation. SUMMARY: Activation of complement plays an important role in the pathogenesis of aPL-induced pregnancy morbidity and thrombosis. This understanding has been advanced primarily using mouse models of APS and clinical studies in patients with APS are needed. Although there is currently no specific complement-targeted therapy approved for APS, developing and evaluating complement-targeted therapies in patients with APS are warranted. Complement inhibition may provide a novel upstream treatment option for patients with APS compared with the current standard treatment of anticoagulation.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.003 |
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".