The effectiveness of hematopoietic stem cell transplantation in treating pediatric sickle cell disease: Systematic review and meta-analysis
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Background: Patients with sickle cell disease (SCD) have just one recognized curative therapy option: hematopoietic stem cell transplantation (HSCT), which results in a long-lasting improvement in the clinical phenotype. Here, we assessed the effectiveness of HSCT in treating children with SCD by a systematic review and meta-analysis. Methods: Up until January 2024, a comprehensive search was done using Web of Science, CINAHL, Embase, Google Scholar, Cochrane Library, PubMed/Medline, and Embase. Two reviewers worked separately to extract the data, and Newcastle-Ottawa Quality Assessment tool was used to assess the research's quality. The outcomes analyzed were Overall survival (OS), event-free survival (EFS), graft failure (GF) and mortality. Results: Nineteen papers satisfied our inclusion requirements and were assessed to be of fair quality. The pooled rate of OS was high (92%; 95% CI: 90.3%-93.5%). Similar finding was detected for EFS (85.8%; 95% CI: 83.7%-87.7%). In the other hand, pooled rates of GF and mortality were 6.9% (95% CI: 5.3%-8.9%) and 7.4% (95% CI: 5%-10.7%), respectively. A significant publication bias was detected for OS, EFS and GF outcomes. Subgroups analysis showed that study design was the major source of heterogeneity. Conclusion: Our results show that HSCT is effective and safe, with pooled survival rates above 90%. It is important to assess innovative tactics in light of the alarming GF and mortality rates.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it