Autologous Hematopoietic Stem Cell Transplantation for Chronic Inflammatory Demyelinating Polyradiculoneuropathy
Bibliographic record
Abstract
BACKGROUND: Chronic inflammatory demyelinating polyradiculoneuropathy (CIDP) refractory to conventional therapy can lead to marked disability and represents a therapeutic challenge. OBJECTIVE: To report five cases of treatment-refractory disabling CIDP treated with autologous hematopoietic stem cell transplantation (AHSCT). METHODS: This was a retrospective cohort study from a tertiary care referral center for both neuromuscular disease and AHSCT. Patients with CIDP treated with AHSCT between 2008 and 2020 were included. All patients had major persistent and disabling neuropathic deficits despite combinations of intensive immunosuppressive therapy. The primary outcome measures were: Medical Research Council sum score, Overall Neuropathy Limitations Scale and requirement for ongoing CIDP immunotherapy after transplantation. We also analyzed safety outcomes by documenting all severe AHSCT-related complications. RESULTS: Five patients with refractory CIDP underwent AHSCT. Three were classified as manifesting a typical syndrome, two were classified as the multifocal Lewis Sumner variant. The mean age at time of CIDP diagnosis was 33.4 years (range 24-46 years), with a median delay of 46 months (range 21-135 months) between diagnosis and AHSCT. The median follow-up period was 41 months. All five patients were able to wean off CIDP-related immunotherapy. Marked improvements in Medical Research Council scale and overall Neuropathy Limitations Scale were noted in 4/5 patients. One patient with longstanding neurogenic atrophy showed no improvement in disability scales. There were no treatment-related deaths or critical illnesses. CONCLUSIONS: AHSCT can achieve marked sustained clinical improvement of refractory CIDP and may allow for weaning off long-term complex immunotherapies.
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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) | 0.002 | 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".