Mortality in American Veterans with the HLA-B27 Gene
Bibliographic record
Abstract
OBJECTIVE: To compare survival in American veterans with and without the HLA-B27 (B27) gene. METHODS: Mortality was evaluated in a national cohort of veterans with clinically available B27 test results between October 1, 1999, and December 31, 2011. The primary outcome was the mortality difference between B27-positive and B27-negative veterans, adjusted for age, sex, race, and diagnoses codes for diseases that may have influenced both B27 testing and mortality, including psoriasis, inflammatory bowel disease, spondyloarthritis (SpA), and other types of inflammatory arthritis. The secondary outcomes were the adjusted mortality HR for B27+ and B27- veterans, in subgroups with and without SpA. RESULTS: Among veterans with available B27 test results, 27,652 (84.7%) were B27- and 4978 (15.3%) were B27+. The mean followup time was 4.6 years. Mortality was higher in the B27+ group than in the B27- group (HR 1.15, 95% CI 1.03-1.27). Mortality was also higher in the B27+ subgroups with SpA (HR 1.35, 95% CI 1.06-1.72) and without SpA (HR 1.11, 95% CI 0.99-1.24), but the difference was significant only in the subgroup with SpA. CONCLUSION: B27 positivity was associated with an increased mortality rate in a cohort of veterans clinically selected for B27 testing, after adjustment for SpA. In the subgroup with SpA, the mortality rate was associated with B27 positivity, and in the subgroup without SpA, there was a nonsignificant association between B27+ and mortality.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.001 | 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".