Treatment responsiveness in CIDP patients with diabetes is associated with unique electrophysiological characteristics, and not with common criteria for CIDP
Bibliographic record
Abstract
OBJECTIVES: Characterize treatment responsiveness in chronic inflammatory demyelinating polyradiculoneuropathy (CIDP) patients with diabetes mellitus (DM). METHODS: We performed a retrospective chart review of CIDP subjects assessed between 1997 and 2013 and compared treatment response rates in those with and without DM, using different sets of criteria. RESULTS: 99 CIDP patients were included, 34 CIDP+DM and 65 CIDP-DM patients, both having similar treatment response rates. CIDP patients fulfilling European Federation of Neurological Societies/Peripheral Nerve Society (EFNS/PNS) criteria had higher treatment response rates. Responders fulfilled a higher number of American Academy of Neurology (AAN) and EFNS/PNS criteria and had a higher number of demyelinating features in the total cohort and in CIDP-DM but not in CIDP+DM patients. CIDP+DM responders, however, had unique electrophysiologic characteristics. CONCLUSION: Fulfilling EFNS/PNS and AAN criteria, and higher number of demyelinating features, are associated with higher treatment response rates in CIDP-DM but not in CIDP+DM patients, implying the need for adjusting current criteria to predict treatment response rates in CIDP-DM patients.
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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 | 0.000 | 0.000 |
| 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".