Safety of allogeneic umbilical cord blood infusions for the treatment of neurological conditions: a systematic review of clinical studies
Bibliographic record
Abstract
BACKGROUND AIMS: Umbilical cord blood (UCB) infusion is being investigated as a treatment for a range of neurological conditions, primarily because of its potent immunomodulatory effects mediated via paracrine signaling. Although initial research mainly utilized autologous UCB, allogeneic samples from a sibling or unrelated donor have now become more common. With the use of allogeneic UCB, questions have arisen surrounding the necessity for human leukocyte antigen (HLA) matching, preparative regimens and immunosuppressant drugs. To investigate the safety of allogeneic UCB for the treatment of neurological conditions and the impact of HLA mismatching and immunosuppresion, the authors conducted a systematic review of the safety of allogeneic UCB infusion for neurological conditions. METHODS: A systematic review of published and gray literature was conducted to investigate the safety of allogeneic UCB infusions for neurological conditions. RESULTS: Authors identified 10 studies using allogeneic UCB to treat autism spectrum disorder, cerebral palsy, stroke, traumatic brain injury and various other conditions. A total of 361 participants (with at least 442 UCB infusions) received a range of HLA-matched/untyped allogeneic units and cell doses, with the majority not administered post-infusion immunosuppression. There were no reported serious adverse events definitely or probably related to the allogeneic UCB infusion, nor later potential complications such as graft-versus-host disease or teratoma formation. CONCLUSIONS: Although variability between studies is high, the available data do not identify safety concerns with allogeneic UCB infusion for the treatment of neurological conditions, even with variable HLA matching or no immunosuppression.
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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 | 0.009 | 0.046 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.007 |
| Bibliometrics | 0.008 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".