Characteristics of participants with self‐reported hemochromatosis or iron overload at HEIRS study initial screening
Bibliographic record
Abstract
There are few descriptions of young adults with self-reported hemochromatosis or iron overload (H/IO). We analyzed initial screening data in 7,343 HEmochromatosis and IRon Overload Screening (HEIRS) Study participants ages 25-29 years, including race/ethnicity and health information; transferrin saturation (TS) and ferritin (SF) measurements; and HFE C282Y and H63D genotypes. We used denaturing high-pressure liquid chromatography and sequencing to detect mutations in HJV, TFR2, HAMP, SLC40A1, and FTL. Fifty-one participants reported previous H/IO; 23 (45%) reported medical conditions associated with H/IO. Prevalences of reports of arthritis, diabetes, liver disease or liver cancer, heart failure, fertility problems or impotence, and blood relatives with H/IO were significantly greater in participants with previous H/IO reports than in those without. Only 7.8% of the 51 participants with previous H/IO reports had elevated TS; 13.7% had elevated SF. Only one participant had C282Y homozygosity. Three participants aged 25-29 years were heterozygous for potentially deleterious mutations in HFE2, TFR2, and HAMP promoter, respectively. Prevalences of self-reported conditions, screening iron phenotypes, and C282Y homozygosity were similar in 1,165 participants aged 30 years or greater who reported previous H/IO. We conclude that persons who report previous H/IO diagnoses in screening programs are unlikely to have H/IO phenotypes or genotypes. Previous H/IO reports in some participants could be explained by treatment that induced iron depletion before initial screening, misdiagnosis, or participant misunderstanding of their physician or the initial screening questionnaire.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.003 | 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".