Undiagnosed diabetes and impaired fasting glucose in <i>HFE</i> C282Y homozygotes and <i>HFE</i> wild-type controls in the HEIRS Study
Bibliographic record
Abstract
OBJECTIVE: mutations identified in population screening. RESEARCH DESIGN AND METHODS: We analyzed these observations in a postscreening examination: age; sex; body mass index; systolic/diastolic blood pressure; metacarpophalangeal joint hypertrophy; hepatomegaly; blood neutrophils; alanine and aspartate aminotransferase; elevated C reactive protein; transferrin saturation; serum ferritin; and Field Center. RESULTS: There were 223 p.C282Y homozygotes and 449 controls without diagnosed diabetes (43.9% men). Mean age of p.C282Y homozygotes was 52±13 years (controls 57±14 years; p<0.0001). Mean transferrin saturation in p.C282Y homozygotes was 67±26% (controls 34±14%; p<0.0001). Mean serum ferritin in p.C282Y homozygotes was 607 pmol/L (95% CI 497 to 517; controls 274 pmol/L (247 to 301); p<0.0001). Overall prevalences of UDM (4.0% vs 4.2%) and IFG (23.8% vs 25.6%) did not differ significantly between p.C282Y homozygotes and wt/wt controls, respectively. In logistic regressions, male sex, body mass index, and alanine aminotransferase were significantly associated with UDM. ORs were 2.7 (1.2 to 2.8); 1.0 (1.0 to 1.1); and 1.0 (1.0 to 1.0), respectively. Age, male sex, and body mass index were significantly associated with IFG. ORs were 1.0 (1.0 to 1.1); 2.8 (1.9 to 4.2); and 1.0 (1.0 to 1.1), respectively. CONCLUSIONS: Prevalences of UDM and IFG were similar in p.C282Y homozygotes and controls in a postpopulation screening examination. Male sex was the strongest predictor of UDM and IFG.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".