Antiphospholipid Antibody Testing in a General Population Sample from the USA: An Administrative Database Study
Bibliographic record
Abstract
We sought to characterized patterns of aPL testing in a large general population sample from the United States. Using Truven Health MarketScan laboratory data from 2010-2015 we identified individuals tested for lupus anticoagulant(LA), anti-cardiolipin (aCL), and anti-beta2-glycoprotein1(aGP1). Our research was approved by the McGill institutional review board (A04-M47-12B). We identified 33,456 individuals with at least one aPL test. Among these, only 6,391 (19%) had all three tests (LA, aCL, aGP1) performed. Confirmatory aPL testing was performed at least 12 weeks later in 77%, 45%, and 41% of initially positive LA, aCL, and aGP1, respectively. Of those re-tested after ≥12 weeks, only 255 (10.6%) were found to have a confirmatory positive aPL test. These findings highlight that aPL testing may often be incompletely performed. Further investigations will be required to better understand the low rate of a confirmatory positive aPL test ≥12 weeks after the initial test.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".