Early Cardiac Involvement and Risk Factors for the Development of Arrhythmia in Patients With β-Thalassemia Major
Bibliographic record
Abstract
BACKGROUND: Cardiac iron overload is the most serious complication in thalassemia; even patients treated with intensive chelation suffer at a certain point from cardiomyopathy and arrhythmia. AIM: The aim of the study was to identify indicators of cardiac dysfunction in thalassemia as well as risk factors associated with the development of arrhythmia. PATIENTS AND METHODS: A total of 45 patients with β-thalassemia major were enrolled in this cross-sectional study. Patients were divided into 2 groups according to the absence (group A) or the presence of arrhythmia (group B). Cardiac parameters in thalassemic groups were evaluated using 24-Holter recording, Stress electrocardiogram, and M-mode echocardiography. Serum ferritin and Cardiac T2* were used to assess the iron status. RESULTS: Group B showed significantly higher values of cardiac T2* and serum ferritin (P<0.05). Group B patients had significantly higher maximum heart rate with significant attacks of bradycardia and ST segment changes. In addition, they achieved a lower percentage of maximum age predicted heart rate and lower values of maximum metabolic equivalents (P<0.05). Significantly higher values of the left atrial diameter, the interventricular septum diameter, and the left-ventricle posterior wall diameter (P<0.05) were identified in group B. CONCLUSIONS: The increase in left atrial diameter, interventricular septum diameter, and left-ventricle posterior wall diameter seems to be related to the development of arrhythmia in patients with thalassemia, especially supraventricular arrhythmias.
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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 | 0.000 | 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 | 0.001 |
| 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".