Bibliographic record
Abstract
Objective: Determining degree of health impairment as perceived by the β-thalassemia major patients is essential information needed to recommend suitable therapy.Due to limited research in this area, this study was done and the aim was survey of quality of life in patients with β-thalassemia major.Materials and Methods: In this cross-sectional study, 70 β-thalassemia major patients aged 15 years and over referred to Mofid children hospital of Tehran in 2010-2011 were studied using a demographic and Global Assessment Scale and Iranian version of SF-36 questionnaires.The samples were chosen on the basis of an available non-randomized sampling.The data was analyzed using SPSS software and statistical analysis methods.Results: The mean age of 70 subjects enrolled in this study was 20.0 (SD=4.0)years.42 patients (60%) were male and 28 patients (40%) were female.The analysis showed that there was no significant association between the gender and age groups and age at the first blood transfusion and the presence of co-morbidity with quality of life and Global Assessment Scale.All of the patients acquired scores above 70 in the Global Assessment Scale.Quality of life of patients was low in the Physical Function and Bodily Pain scales of Physical Health component in comparison with healthy individuals but patients had favorable quality of life in the Mental Health component.Conclusion: Presented data suggested that for improvement of quality of life in β-thalassemia major patients, special attention regarding physical aspects and better accomplishment medical and rehabilitation services is necessary in addition to psychological problems of these patients.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.881 | 0.868 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".