Initial Screening Transferrin Saturation Values, Serum Ferritin Concentrations, and <i>HFE</i> Genotypes in Whites and Blacks in the Hemochromatosis and Iron Overload Screening Study
Bibliographic record
Abstract
We compared initial screening data of 44,082 white and 27,124 black Hemochromatosis and Iron Overload Screening (HEIRS) Study participants. Each underwent serum transferrin saturation (TfSat) and ferritin (SF) measurements without regard to fasting, and HFE C282Y and H63D genotyping. Elevated measurements were defined as: TfSat more than 50% (men), more than 45% (women); and SF more than 300 ng/ml (men), more than 200 ng/ml (women). Mean TfSat and percentages of participants with elevated TfSat were significantly greater in whites than in blacks. Mean SF and percentages of participants with elevated SF were significantly greater in blacks than in whites. TfSat and SF varied by gender and age in whites and blacks. Prevalences of genotypes that included either C282Y or H63D were significantly greater in whites than in blacks. The prevalence of elevated TfSat and SF plus genotypes C282Y/C282Y, C282Y/H63D, or H63D/H63D was 0.006 in whites and 0.0003 in blacks. Among whites with HFE C282Y homozygosity, 76.8% of men and 46.9% of women had elevated TfSat and SF values. Three black participants had HFE C282Y homozygosity; one had elevated TfSat and SF values. Possible explanations for differences in TfSat and SF in whites and blacks and pertinence to the detection of hemochromatosis, iron overload, and other disorders with similar phenotypes are discussed.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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) | 0.001 | 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".