OA2‐AM23‐MN‐06 | Change in Hemoglobin as an Indicator of Iron Deficiency in Repeat Blood Donors
Bibliographic record
Abstract
Repeat blood donation can cause iron deficiency. Blood collectors use a fingerstick hemoglobin (Hb) test to qualify donors because no point-of-care test is available for ferritin or other measures of iron stores. In some countries, ferritin is measured post-donation to monitor iron stores. In the Netherlands, donors with ferritin level below 30 ng/mL are deferred for their next donation. Although there is a clear physiological association between ferritin and changes in Hb, no quantitative estimate for this association for blood donors has been published. We analyzed data on 29,469 male and 35,292 female repeat blood donors (with 50,390 and 49,862 donations, respectively) with at least two donations between January 2012 and September 2022 for whom Hb level at first donation (baseline) was available and both ferritin and Hb were measured at subsequent donations. We analyzed the association between the log ferritin (lFer) level and the fingerstick Hb change-from-baseline (dHb). As there is a clear changepoint in the association between the dHb and log ferritin levels, we determined the changepoint by maximum likelihood estimation of a two-segmented line, where the right-hand segment has a constant value. We generated confidence intervals calculating various statistics on 1000 bootstrap samples for both the male and female data subsets. To provide an intuitive confirmation of the association, we plotted a rolling mean with a window of n = 1000 observations. On average, male donors contributed 1.7 donations and females 1.4 donations to the data subsets. Of all male and female donations, 37% and 52%, respectively, had ferritin levels below 30 ng/mL. We found a linear association between dHb and lFer for ferritin levels below 30 ng/mL (1.08 mmol/mg [95% confidence interval (CI) 1.02–1.15] for males, 0.59 mmol/mg [95% CI 0.56–0.63] for females). For ferritin levels above 30 ng/mL, we found no change in Hb as a function of lFer. The changepoint for is 30.2 for males (95% CI 28.7–31.8 ng/mL) and 31.4 for females (95% CI 28.5–33.0 ng/mL). The higher changepoint in female donors could be due to selection bias (females with a lower Hb values may be more likely to drop out as a blood donor). Scatterplot of ferritin (plotted on log scale) versus hemoglobin change from baseline.
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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 | 0.003 | 0.005 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.009 | 0.002 |
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".