Prevalence of antibodies to prothrombin in solid phase (aPT) and to phosphatidylserine-prothrombin complex (aPS/PT) in patients with and without lupus anticoagulant
Bibliographic record
Abstract
Antibodies to prothrombin in solid phase (aPT) and those to phosphatidiyserine-prothrombin complex (aPS/PT) have been suggested to strongly correlate with the presence of lupus anticoagulant (LA). As their clinical diagnostic value and true relationship with the LA remains elusive, we designed this study to evaluate the prevalence and significance of aPT and aPS/PT in a large cohort of patients with and without LA. Samples from 257 patients were included. aPT and aPS/PT were tested by ELISA. LA was tested as per the current criteria from the ISTH Subcommittee on LA-Phospholipid-dependent antibodies. aPS/PT and aPT were found in 51% and 32% of LA-positive (LA+ve) patients and in 22% and 28% of LA-negative (LA-ve) patients, respectively. Thrombosis, particularly venous thrombosis was associated with IgG aPT in the LA+ve group (p=0.0006) and in the LA-ve group (p=0.017). Antibodies to phosphatidylserine-prothrombin, either IgG and IgM were associated with thrombosis in general (p=0.0003) in particularly with venous thrombosis in the LA+ve group (p<0.0001 for IgG and p=0.025 for IgM; respectively) and the LA-ve group (p=0.028, 0.02 and 0.001, respectively). Further multivariate logistic regression analysis showed that LA and of IgG and/or IgM aPS/PT were independent risk factors for thrombosis and pregnancy loss. In conclusion, aPS/PT, but not aPT, are more frequently found in patients with LA. Their association with thrombosis seems to be independent of the presence of LA.
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".