Hematopoietic Stem Cell Transplantation Stabilizes Cerebral Vasculopathy in High-Risk Pediatric Sickle Cell Disease Patients: Evidence From a Referral Transplant Center
Bibliographic record
Abstract
Background: Severe sickle cell disease (SCD) can present with different vaso-occlusive manifestations with cerebral vasculopathy (CV) as one of the most serious complications. Hematopoietic stem cell transplant (HSCT) is the ultimate therapy for this complication. The aim of this study was to assess the outcome and impact of HSCT on severe SCD patients with CV complications. Methods: Twenty-five consecutive transplants-naive pediatric SCD patients with CV complications underwent HSCT at our institution between 1993 and 2015, using bone marrow as stem cells source from fully match related donors were included. Neurologic evaluation was done both clinically and radiologically before transplantation and regularly following the HSCT. Results: With a median follow-up of 52.2 ± 5.8 months, the cumulative probability of overall survival (OS) at 3 years was 92.0% and event-free survival (EFS) was 88%. Significant neurologic improvements were observed in most of the patients clinically. Different neurologic complications were assessed. The neurologic manifestations before and after HSCT were hemiparesis (11, 1), seizures (13, 8), focal neurologic deficit (4, 2), loss of conscious (2, 1) headache (6, 1), and psychological symptoms (5, 2). Post-HSCT radiological imaging was done in 15 patients, which showed stabilization of CV among all. Conclusions: Allogeneic HSCT in patients with severe SCD presenting with CV complications including moyamoya vasculopathy showed favorable outcome with significant clinical neurologic improvement and stabilization of the disease. None of the patients with severe vasculopathy underwent neurological vascular by-pass surgery prior to HSCT.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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) | 0.001 | 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".