Is high hemoglobin a hindrance factor for blood donation? A pilot observational study from the coastal region of India.
Bibliographic record
Abstract
BACKGROUND: Blood donors with high Hb are often deferred for the presumed risk of polycythemia vera (PV). However, adequate data to substantiate or refute this hypothesis is lacking. METHODOLOGY: We conducted an observational study on blood donors found to have high hemoglobin (Hb≥18g/dL) during the pre-donation screening process using a portable hemoglobinometer at our blood center for four months. We adopted a cost effective methodology wherein a questionnaire was used to elicit the secondary causative factors of high hemoglobin and a complete blood count test to observe the blood cell parameters and JAK2V617F mutation test was performed in a subset of donors lacking secondary erythrocytosis (SE) history. RESULTS: Of the total 7076 donors enrolled, 112 male donors (1.58%) had high hemoglobin. The majority (70.4%) were repeat donors with mean age of 31.4 years. About 61% of the donors had attributable factors for SE like smoking, occupational exposure to carbon monoxide. The mean hemoglobin value of capillary and venous hemoglobin demonstrated a statistically significant difference (P<0.05) where 2.7% of donors had venous Hb<18g/dL. The hematological profile of all the donors showed increased RBC but normal platelet and WBC count. Of 24 donors included for the JAK2V617F test, none had a positive report. CONCLUSION: This study suggests high hemoglobin in blood donors is less likely due to PV. Hence, re-considering their deferral may help alleviate donor anxiety and allow donor return. However, multi-centric studies are required to develop consensus statements on PV risk status and blood donation eligibility.
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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 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".