Antiphospholipid Antibody Profile Stability Over Time: Prospective Results From the APS ACTION Clinical Database and Repository
Bibliographic record
Abstract
Objective The APS ACTION Registry studies long-term outcomes in persistently antiphospholipid antibody (aPL)-positive patients. Our primary objective was to determine whether clinically meaningful aPL profiles at baseline remain stable over time. Our secondary objectives were to determine (1) whether baseline characteristics differ between patients with stable and unstable aPL profiles, and (2) predictors of unstable aPL profiles over time. Methods A clinically meaningful aPL profile was defined as positive lupus anticoagulant (LAC) test and/or anticardiolipin (aCL)/anti-β2glycoprotein-I (anti–β2-GPI) IgG/M ≥ 40 U. Stable aPL profile was defined as a clinically meaningful aPL profile in at least two-thirds of follow-up measurements. Generalized linear mixed models with logit link were used for primary objective analysis. Results Of 472 patients with clinically meaningful aPL profile at baseline (median follow-up 5.1 yrs), 366/472 (78%) patients had stable aPL profiles over time, 54 (11%) unstable, and 52 (11%) inconclusive. Time did not significantly affect odds of maintaining a clinically meaningful aPL profile at follow-up in univariate (P= 0.906) and multivariable analysis (P= 0.790). Baseline triple aPL positivity decreased (OR 0.25, 95% CI 0.10–0.64,P= 0.004) and isolated LAC test positivity increased (OR 3.3, 95% CI 1.53–7.13,P= 0.002) the odds of an unstable aPL profile over time. Conclusion Approximately 80% of our international cohort patients with clinically meaningful aPL profiles at baseline remain stable at a median follow-up of 5 years; triple aPL-positivity increase the odds of a stable aPL profile. These results will guide future validation studies of stored blood samples through APS ACTION Core Laboratories.
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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 | 0.006 | 0.020 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.007 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".