Evaluation of the Correlation between Echocardiographic Findings and Serum Ferritin in Thalassemia Major Patients
Bibliographic record
Abstract
INTRODUCTION: Thalassemia is a disorder that affects beta globin gene production and the resultant need for erythrocyte transfusions puts the patient at risk for iron loading, especially cardiac iron loading. Cardiac complications are the most serious ones accompanied by morbidity and mortality. The most harm to the heart is caused by iron overload. Ferritin is generally associated with the amount of stored iron in the body. The aim of this study was to investigate the relationship between echocardiographic findings and serum ferritin level. MATERIALS & METHODS: 107 patients with thalassemia major were enrolled in this prospective analytical study. Serum ferritin levels and echocardiographic findings (diastolic, systolic, pulmonary artery pressure, valvular dysfunctions) were assessed. The data were analyzed by spearman statistical test. RESULTS: Serum ferritin levels of the thalassemia major patients in the study were 2419.13±1772.65 ng/ml. there wasn’t any significant relationship between echocardiographic findings and serum ferritin level. CONCLUSION: Although our findings didn’t support the association between ferritin level and echocardiographic data but we suggest serial cardiac assessment to prevent the effect of increasing iron on the heart.
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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 | 0.002 |
| 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 | 0.000 | 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".