Prospective Evaluation of Fetal Hemoglobin Expression in Maternal Erythrocytes: An Analysis of a Cohort of 345 Parturients
Bibliographic record
Abstract
It is believed that fetal hemoglobin (HbF) expression in adults is largely genetically regulated. The increased expression of HbF in pregnancy has been reported in a small number of articles. Different mechanisms have been proposed, but the description of HbF expression during pregnancy remains unclear. The objectives of this study were to document HbF expression during peri and postpartum periods, confirm its maternal origin, and assess clinical and biochemical parameters potentially associated with HbF modulation. In this observational prospective study, 345 pregnant women were followed. At baseline, 169 had HbF expression (≥1% of total hemoglobin) and 176 did not have HbF expression. Women were followed at the obstetric clinic during their pregnancy. Clinical and biochemical parameters were measured at each visit. Analyses were made to determine which parameters had a significant correlation to HbF expression. Results show that HbF expression of ≥1% during peri and postpartum periods in pregnant women without influencing comorbidities is at its highest peak during the first trimester. In all women, it was proven that HbF was of maternal origin. A significant positive correlation between HbF expression, βeta-human chorionic gonadotropin (β-HCG), and glycosylated hemoglobin (HbA1c) was present. A significant negative association between HbF expression and total hemoglobin was found. HbF expression induction during pregnancy is probably associated with an increase in β-HCG and HbA1C, and a decrease in total hemoglobin, which could temporarily reactivate the fetal erythropoietic system.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| 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) | 0.001 | 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".