P.037 Neurofascin-155 IgG in acute-onset inflammatory polyneuropathy: possible predictor of relapse and recovery
Bibliographic record
Abstract
Background: IgG4 autoantibodies to neurofascin-155 (NF-155) have been described in a subset of patients with chronic inflammatory demyelinating polyneuropathy (CIDP). While reports suggest an acute onset is more likely than in antibody negative CIDP, little literature exists around the subsequent course of NF-155 positive cases that originally presented with an acute inflammatory demyelinating polyneuropathy (AIDP) phenotype. Methods: Two male patients, ages 51 and 59, presented with similar, <2 week histories of lower extremity weakness. Patients were diagnosed with AIDP and treated with IVIG. Following initial improvement, both patients relapsed. One patient was treated with IVIG and steroids with subsequent improvement; however, he was unable to be weaned from steroids without experiencing recurrence of symptoms. The other patient was not retreated. Testing for NF-155 IgG was sent. Results: The first patient ultimately required Rituximab for stable improvement, the other improved spontaneously. Both patients later had positive tests for NF-155 IgG4 antibodies. Conclusions: Both of our NF-155 positive cases had initial AIDP-like presentations, followed by a relapsing course and excellent eventual recovery. This result, along with limited other available cases, suggest that in patients with an AIDP-like presentation, NF-155 IgG4 autoantibodies could be a marker of disease recurrence, but do not necessarily predict a poor outcome.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".