The Characteristics of Chronic Inflammatory Demyelinating Polyneuropathy in Patients with and without Diabetes – An Observational Study
Bibliographic record
Abstract
INTRODUCTION: We aimed to determine whether the clinical characteristics and electrodiagnostic classification of nerve injury, and response to treatment differed in patients diagnosed with chronic inflammatory demyelinating polyneuropathy (CIDP) with and without diabetes. METHODS: CIDP patients with diabetes (CIDP+DM) (n = 67) and without diabetes (CIDP-DM) (n = 67) underwent clinical examination and nerve conduction studies (NCS). CIDP-DM patients were selected using age and gender matching with the existing CIDP+DM cohort. Patients treated with immunotherapies were classified as responders (R) (n = 46) or non-responders (NR) (n = 54) based on clinical response to treatment. The groups were compared using analysis of variance, contingency tables and Kruskal-Wallis analyses. RESULTS: CIDP+DM subjects had more severe neuropathy based on higher lower limb vibration potential thresholds (VPT)(p = 0.004), higher Toronto Clinical Neuropathy Score (TCNS) (p = 0.0009), more proximal weakness (p = 0.03), more gait abnormality (p = 0.03) and more abnormal NCS. CIDP+DM subjects had more abnormal sural NCS with lower sural sensory nerve action potential amplitudes (2.4±3.0 µV, 6.6±6.0 µV, p<0.0001) and slower sural nerve conduction velocities (38.6±5.4 m/s, 41.0±5.3 m/s, p = 0.04). CIDP-DM subjects were more likely to receive immune therapies (93% vs 57%, p = <0.0001), despite no significant differences in treatment responder rates (p = 0.71). Patients who responded to therapy had shorter duration of CIDP than non-responders (8.0±6.0 y vs 11.9±7.6 y, p = 0.004). DISCUSSION: The clinical phenotype and electrophysiological profile of CIDP patients differs according to the presence or absence of diabetes. Despite CIDP+DM patients having more severe clinical and electrophysiological neuropathy, they are less likely to receive disease-modifying/specific therapy, yet have similar response rates to treatment as those without diabetes. Specifically, the duration of neuropathy - not diabetes status - was associated with treatment response.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".