Impacts of Hematopoietic Stem Cell Transplantation on Quality of Life and Behavioral Outcomes in Pediatric Patients with Leukemia and Thalassemia
Bibliographic record
Abstract
Background: This study aimed to investigate the effects of allogeneic hematopoietic stem cell transplantation (HSCT) on quality of life and behavioral problems in children diagnosed with leukemia and β-thalassemia major, with a focus on post-transplant diagnosis-specific differences in psychosocial adjustment. Method: This study included 112 children (63 children with acute leukemia, 49 children with β-thalassemia major) aged 6–18 years, along with a control group of 30 healthy children within the same age range. The Pediatric Quality of Life Inventory (PedsQL) and the Child Behavior Checklist for Ages 6–18 (CBCL) were administered. Participants were categorized into five groups, and the outcomes were compared accordingly. Results: The emotional functioning subscale scores of the PedsQL were significantly lower in children with leukemia and those who had undergone HSCT for leukemia, when compared to children with thalassemia (p < 0.05). The social functioning subscale scores were also significantly lower in children with leukemia who underwent HSCT compared to those with thalassemia (p < 0.05). The CBCL internalizing scores were higher in children with leukemia and post-HSCT leukemia patients than in their healthy peers (p < 0.05). Over time, both diagnostic groups showed improvements, with total PedsQL scores increasing and total CBCL scores decreasing after HSCT. Conclusions: This study demonstrates that quality of life improved and behavioral problems diminished over time following HSCT. However, the psychosocial impact of HSCT varied depending on the underlying disease, with children diagnosed with leukemia being slightly more adversely affected. These findings suggest that interventions aimed at improving quality of life and addressing behavioral issues should be tailored to the specific diagnosis.
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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 | 0.000 |
| 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".