Risk Factors for Insulin Resistance, Metabolic Syndrome, and Diabetes in 248 <i>HFE</i> C282Y Homozygotes Identified by Population Screening in the HEIRS Study
Bibliographic record
Abstract
BACKGROUND: We sought to identify risk factors for insulin resistance, metabolic syndrome (MetS), and diabetes mellitus in 248 non-Hispanic white HFE C282Y homozygotes identified by population screening. METHODS: We analyzed observations obtained prospectively in a postscreening examination: age; sex; body mass index (BMI); systolic/diastolic blood pressure; metacarpophalangeal (MP) joint hypertrophy; hepatomegaly; complete blood counts; alanine/aspartate aminotransferase levels; elevated C-reactive protein (>0.5 mg/dL); transferrin saturation; serum ferritin; homeostasis model assessment-insulin resistance (HOMA-IR); and MetS. RESULTS: Twenty-six participants (10.5%) had diabetes diagnoses. A significant trend across HOMA-IR quartiles was observed only for blood neutrophils. Logistic regression on HOMA-IR fourth quartile revealed positive associations: age (P = 0.0002); male sex (P = 0.0022); and BMI (P < 0.0001). HOMA-IR fourth quartile predicted MetS (P < 0.0001). Logistic regression on diabetes revealed positive associations: age (P = 0.0012); male sex (P = 0.0068); MP joint hypertrophy (P = 0.0167); neutrophils (P = 0.0342); and MetS (P = 0.0298). Serum ferritin did not predict HOMA-IR fourth quartile, MetS, or diabetes. CONCLUSIONS: In screening C282Y homozygotes, age, male sex, and BMI predicted HOMA-IR fourth quartile. HOMA-IR fourth quartile alone predicted MetS. Diabetes was associated with greater age, male sex, MP joint hypertrophy, greater blood neutrophil counts, and MetS.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.000 | 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".