A Longitudinal Study of Growth and Relation With Anemia and Iron Overload in Pediatric Patients With Transfusion-dependent Thalassemia
Bibliographic record
Abstract
Short stature is one of the most common endocrinopathies in transfusion-dependent thalassemia (TDT). This study aimed to determine the longitudinal pattern of growth in pediatric patients with TDT and study the relationship between growth and hemoglobin level, serum ferritin level/iron overload parameters, and other clinical factors. The interval height-for-age Z-scores (HAZ) of 50 patients with TDT, of a mean age of 13.3±2.8 years, were analyzed using linear mixed model analysis. Nineteen patients (38%) had short stature with HAZ≤-2.0. The prevalence of short stature increased with age. The estimated mean HAZ decreased by 0.19 SD per year from the age of 5 years until approximately 14 years (95% confidence interval [CI], -0.22 to -0.16, P<0.001). Male sex (estimate, -0.28; 95% CI, -0.43 to -0.14; P<0.001), mean 3-year hemoglobin level ≤8 g/dL (estimate, -0.36; 95% CI, -0.53 to -0.19; P<0.001), mean 3-year ferritin level ≥1800 ng/mL (estimate, -0.44; 95% CI, -0.59 to -0.29; P<0.001), and cardiac T2* ≤20 ms (estimate, -1.05; 95% CI, -1.34 to -0.77; P<0.001) were significantly associated with short stature. In conclusion, short stature in patients with TDT is common and relates significantly with increasing age, male sex, hemoglobin level, and iron overload status.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.001 | 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".