The difference between fingerstick and venous hemoglobin and hematocrit varies by sex and iron stores
Bibliographic record
Abstract
BACKGROUND: Fingerstick blood samples are used to estimate donor venous hemoglobin (Hb). STUDY DESIGN AND METHODS: Fingerstick Hb or hematocrit (Hct) was determined routinely for 2425 selected donors at six blood centers, along with venous Hb. Using sex and measures of iron status including absent iron stores (AIS; ferritin < 12 ng/mL), linear regression models were developed to predict venous Hb from fingerstick. RESULTS: Across all subjects, fingerstick Hb was higher than venous Hb in the higher part of the clinical range, but lower in the lower part of the range. The relationship varied by sex and iron status. Across centers, a female donor had on average a venous Hb result 0.5 to 0.8 g/dL lower than a male donor with the same fingerstick Hb and iron status. Similarly, a donor with AIS had on average a venous Hb result 0.3 to 1.1 g/dL lower than an iron-replete donor with the same fingerstick value and sex. An iron-replete male donor with a fingerstick result at the cutoff (Hb 12.5 g/dL) had an acceptable expected venous Hb (12.8 to 13.8 g/dL). A female donor with AIS with a fingerstick result at the cutoff had an expected venous Hb below 12.5 g/dL (11.7 to 12.4 g/dL). Of females with AIS, 40.2% donated blood when their venous Hb was less than 12.5 g/dL. CONCLUSIONS: Fingerstick is considered a useful estimator of venous Hb. However, in some donor groups, particularly female donors with AIS, fingerstick overestimates venous Hb at the donation cutoff. This significant limitation should be considered in setting donor fingerstick Hb or Hct requirements.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| 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) | 0.002 | 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".