Serum ferritin concentrations and body iron stores in a multicenter, multiethnic primary‐care population
Bibliographic record
Abstract
How often elevated serum ferritin in primary-care patients reflects increased iron stores (normally 0.8 g in men, 0.4 g in women) is not known. The Hereditary Hemochromatosis and Iron Overload Screening (HEIRS) study screened 101,168 primary-care participants (44% Caucasians, 27% African-Americans, 14% Asians/Pacific Islanders, 13% Hispanics, 2% others). Follow-up clinical evaluation was performed in 302 of 333 HFE C282Y homozygotes regardless of iron measures and 1,375 of 1,920 nonhomozygotes with serum ferritin >300 microg/L (men), >200 microg/L (women) and transferrin saturation >50% (men), >45% (women). Quantitative phlebotomy was conducted in 122 of 175 C282Y homozygotes and 122 of 1,102 nonhomozygotes with non-transfusional serum ferritin elevation at evaluation. The estimated prevalence in the Caucasian population of C282Y homozygotes with serum ferritin >900 microg/L at evaluation was 20 per 10,000 men and 4 per 10,000 women; this constellation was predictive of iron stores >4 g in men and >2 g in women. The estimated prevalence per 10,000 of non-C282Y homozygotes with serum ferritin >900 microg/L at evaluation was 7 among Caucasians, 13 among Hispanics, 20 among African Americans, and 38 among Asians and Pacific Islanders, and this constellation was predictive of iron stores >2 g but <4 g. In conclusion, serum ferritin >900 microg/L after initial elevations of both serum ferritin and transferrin saturation is predictive of mildly increased iron stores in multiple ethnic populations regardless of HFE genotype. Serum ferritin >900 microg/L in male C282Y homozygotes is predictive of moderately increased iron stores.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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".