SERUM TRACE ELEMENTS PICTURE IN SICKLE CELL ANAEMIA: A COMPARATIVE STUDY OF HBSS AND HBAA INDIVIDUALS AT A TEACHING HOSPITAL IN SOUTHWEST NIGERIA
Bibliographic record
Abstract
Background: Sickle cell anemia (SCA) is a chronic hemoglobinopathy associated with oxidative stress and altered trace element metabolism. This study evaluates the levels of key trace elements in SCA patients and their potential clinical implications. Methods: A cross-sectional comparative study was conducted at Ekiti State University Teaching Hospital. A total of 111 participants, including 74 SCA patients (37 in steady state and 37 in crises) and 37 age- and sex-matched healthy controls (HbAA), were recruited. Serum copper, zinc, magnesium, selenium, and chromium levels were measured using validated spectrophotometric and colorimetric methods. Data were analyzed using SPSS version 20, with statistical significance set at p ≤ 0.05. Results: SCA patients had significantly higher mean serum copper levels than controls (p < 0.001), while zinc, magnesium, selenium, and chromium levels were significantly lower (p < 0.001). Correlation analysis revealed a significant negative correlation between copper and zinc (r = -0.875, p < 0.001) and positive correlations between zinc and magnesium (r = 0.925, p < 0.001), selenium (r = 0.94, p < 0.001), and chromium (r = 0.918, p < 0.001).Conclusion: This study highlights significant trace element imbalances in SCA patients, suggesting potential micronutrient deficiencies. Further research is needed to assess the clinical impact and potential benefits of targeted nutritional interventions in SCA management
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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 | 0.001 |
| 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".