Association of killer cell immunoglobulin–like receptor genotypes with vascular arterial events and anticardiolipin antibodies in patients with lupus
Bibliographic record
Abstract
To determine whether killer cell immunologlobulin-like receptor (KIR) genotypes are associated with vasculitis, vascular arterial events or anticardiolipin (aCL) antibodies in patients with lupus. A total of 304 patients followed prospectively at the University of Toronto Lupus Clinic were assessed for the occurrence of vasculitis and vascular arterial events. Molecular HLA-C and KIR (presence or absence of KIR2DL1, 2DL2, 2DL3, 2DS1 and 2DS2) genotyping were performed. Chi-square and logistic regression were used to analyse association between KIR genes and vascular arterial events and aCL antibodies. In patients with vascular arterial events, there was a significant increase in KIR2DS2 (60% vs 45%, P = 0.02) and in KIR2DL2 (62% vs 47%, P = 0.01) compared with patients without events. There was no increase in activating KIR genotypes in patients with vasculitis. In patients with aCL antibodies, significant increases were seen in KIR2DS2 (54% vs 41%, P = 0.03) and KIR2DL2 (58% vs 41%, P = 0.003), but KIR2DL3 was decreased (87% vs 95%, P = 0.03). Logistic regression confirmed independent association of KIR2DS2 with vascular arterial events. We found an increase in KIR2DS2 in lupus patients with vascular arterial events, but not in patients with vasculitis.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".