Comparison of monoclonal gammopathy of undetermined significance-associated neuropathy and chronic inflammatory demyelinating polyneuropathy patients
Bibliographic record
Abstract
OBJECTIVES: There are varying reports on whether monoclonal gammopathy of undetermined significance-associated neuropathy (MGUSN) patients are distinguishable from those with chronic inflammatory demyelinating polyneuropathy (CIDP) and whether specific MGUSN subclasses are associated with specific clinical phenotypes. METHODS: We performed a retrospective chart review of MGUSN (n = 56) and CIDP (n = 67) patients. Data extracted included: demographics, neurological examination, and nerve conduction studies (NCS) at baseline and last visit. Clinical status was rated as 0 = worse, 1 = unchanged, 2 = stabilized after a declining course, or 3 = improved. The electrophysiology data were rated as 0 = worse, 1 = stable, or 2 = improved. Statistical analyses were performed using JMP (version 9.0.2 for Macintosh, from SAS). RESULTS: Seventy percent were males, aged 68.1 ± 12.6 years with neuropathy for 9.8 ± 6.8 years and follow-up of 4.0 ± 3.2 years. CIDP patients had more severe neuropathy, and were more likely to receive treatment and to respond. The clinical neuropathy status remained unchanged in 52.8 % of the MGUSN and 24.2 % of the CIDP patients, and stabilized in 7.6 % of MGUSN and 30.3 % of CIDP patients. IgM-MGUSN patients did not differ from other immunoglobulin subclasses in response to treatment. The clinical severity and the number of abnormal NCS parameters were greater in the demyelinating MGUSN in comparison to the axonal group. CONCLUSION: MGUSN patients have less severe neuropathy than CIDP patients, but among the MGUSN patients the severity is greater in the demyelinating and the IgM groups. MGUSN patients may do well without treatment and exposure to potential adverse effects.
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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 | 0.001 |
| 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".