Longitudinal change in Paced Auditory Serial Addition Test (PASAT) performance following immunoablative therapy and haematopoietic stem cell transplant in multiple sclerosis
Bibliographic record
Abstract
Immediately following immunoablation and hematopoietic stem cell transplantation (IA-HSCT) for MS a median decrease in brain volume of 3.2 % over 2.4 months occurs. After 2 years, rates of atrophy are comparable to normal volunteers. Potential impact of atrophy on cognition was evaluated by examining performance on the Paced Auditory Serial Addition Test (PASAT) pre- and post-IA-HSCT. Twenty-three individuals with rapidly progressing/poor prognosis MS underwent high dose IA-HSCT. Individuals completed the 3” PASAT at baseline and 6/12/18/24/30/36 months post-procedure. Mean decline in performance between baseline and 6-months occurred, though it was not statistically significant. Minor declines were offset by an overall trend for improvement over time. The largest (non-significant) cognitive gains were between months 30 and 36. Neither level of impairment at baseline, nor demographic variables, influenced likelihood of improvement. No relationship between changes in cognition and changes in volumes was detected, likely secondary to small sample size. While an initial decline in cognition was noted 6 months post-IA-HSCT, there were no lasting negative effects of treatment given the overall trend for improvement. Initial cognitive decline and marked volume loss are likely secondary to acute toxic effects of chemotherapy. Gains in cognition noted over 36 months suggest long-term follow-up is essential.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".