Ferritin Levels in a Cohort of Affected Males of Mild Hemophilia A Carriers and Their Unaffected Siblings.
Bibliographic record
Abstract
Abstract Iron deficiency is often used as a surrogate marker of bleeding. According to (multiple) studies, suboptimal iron stores can affect cognitive function, energy level and hence, quality of life. Due to a founder affect certain regions of the Canadian province of Newfoundland and Labrador have a very high prevalence of mild Hemophilia A. To accurately plan for future health related needs of these patients, a base-line cross-sectional study of a large cohort segregating a known founder mutation (Val2016Ala) was undertaken. Serum ferritin concentrations, complete blood counts (CBCs), menstrual blood loss assessed using Pictorial Blood Loss Assessment Chart (PBAC), bleeding histories, BMIs, and quality of life data using the SF-36 questionnaire were collected. Prevalence(%) of Suboptimal Iron Status for Women and Men Sub-Grouped By Menstrual Status and Mutation Status Serum Ferritin Cut-off(ug/L) **P Chi-Square <0.001 *P Chi-Square <0.01 Cohort <11 <24 <40 <50 Females(n=141) 12.1* 37.6** 55.3** 62.4** Males(n=77) 1.3* 4.1** 6.5** 6.5** Menstruating Women(n=81) 15.0 54.3** 71.6** 80.2** Non-Menstruating Women(n=58) 8.6 15.5** 31.0** 36.2** Menstruating Carriers(n=46) 8.7 50.0 65.2 73.9 Menstruating Controls(n=35) 23.5 60.0 80.0 88.6 Affected Males(n=46) 0.0 4.3 6.5 6.5 Control Males(n=31) 3.2 3.2 6.5 6.5 § Six women had hemoglobin concentrations less than 120 g/L and 11 men had concentrations less than 140 g/L, with anemia comparably observed in patients with or without the mutation(data not shown). Women in general reported a lower mean General Health Scale score (63.9, 59.9–67.9 vs. 70.6, 69.5–71.7) and a higher mean Role Emotional Scale score (89.3, 85.8–92.8 vs 79.5, 77.7–81.3) than norms for the general U.S. population. Men with a history of severe bleeding had significantly lower ferritin levels than men without a history of severe bleeding (123.4 g/L, 63.6–186.3 g/L, 105.9–301.5; p <0,05). Mutation status did not influence iron status in either sex or menstrual blood loss in women as measured by the PBAC. Serum ferritin level was not associated with PBAC score. Neither the means of the eight SF-36 domains, health transition scale, nor the two component summary measures were significantly lower for mildly iron-deficient or iron-deficient women. The SF-36 is a general measure of various quality of life domains and may not be sensitive enough to measure the effects iron deficiency could potentially have on women’s cognition and fatigue. A study using measures more sensitive to these affects would better investigate the impact of iron deficiency. Further research is also required to determine whether the low ferritin levels observed in women could possible be a result of inadequate dietary intake of iron or insufficient iron absorption in addition to menstrual blood loss.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| 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) | 0.002 | 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".