Citations

ABSTRACT Background and Aims Chronic inflammatory demyelinating polyradiculoneuropathy ( CIDP ) is a common, treatable, autoimmune, neuropathy frequently misdiagnosed. The complex electrodiagnostic ( EDX ) criteria required for diagnosis are challenging to apply in routine practice. This study evaluates the effectiveness of a machine‐assisted EDX tool in real‐time identification of demyelinating nerve conduction studies ( NCS ) stipulated by 2021‐ EAN / PNS CIDP criteria in conjunction with an online CIDP clinical probability calculator. Methods We prospectively evaluated 100 consecutive patients with referral or EDX diagnosis of polyradiculoneuropathy beginning January 1, 2024. Fifty patients were included, each from Jacksonville and Rochester Mayo Clinics. Routine electromyography ( EMG ) reports were compared to a machine‐assisted support tool applying 2021‐ EAN / PNS CIDP EDX criteria to NCS assessing demyelination. The EDX ‐assistant performance was compared to the final clinical diagnosis and our previously reported online CIDP clinical prediction tool ( https://news.mayocliniclabs.com/cidp‐calculator/ ). Results Among 100 patients (60% male; median age 64), 30 had a final clinical CIDP diagnosis with 29 having intravenous immunoglobulin follow‐up; 27 (93%) improved and 2 (7%) stabilized. Routine EMGs reported demyelination in 14 of 30 (47%), with 46% sensitivity and 79% specificity. The EDX ‐assistant identified CIDP demyelination in 28 of 30 (93%), with 93% sensitivity and 57% specificity. The clinical calculator detected CIDP in 30 of 30 (100%) with 86% specificity, increasing to 94% after excluding false positives lacking demyelinating features on the EDX tool. Interpretation A real‐time machine‐assisted EDX support tool, used with a clinical web‐based calculator, streamlines CIDP assessment by improving standardized identification of 2021‐EAN/PNS CIDP demyelinating NCS criteria and aiding clinical decisions.

ABSTRACTBackground and AimsNerve conduction studies (NCS) are integral to diagnosing chronic inflammatory demyelinating polyradiculoneuropathy (CIDP), but their role in predicting treatment outcomes remains underexplored. This study evaluates NCS changes at first follow‐up (first NCS changes) as predictors of treatment success in CIDP, focusing on their correlation with clinical outcomes over time.MethodsNewly diagnosed CIDP patients meeting the 2021 EAN/PNS criteria were retrospectively evaluated. Baseline and first follow‐up NCS parameters were compared with clinical outcomes, assessed by the Neuropathy Impairment Score (NIS) and Inflammatory Neuropathy Cause and Treatment (INCAT) disability score. All patients received first‐line immunotherapy (intravenous immunoglobulin, corticosteroids, or plasma exchange).ResultsOf 39 treated patients, 26 (66.7%) were responders based on improving NIS trends, while 13 (33.3%) were nonresponders. Responders showed significant improvements at the first follow‐up in fibular compound muscle action potential (CMAP) amplitude, ulnar CMAP amplitude, summated CMAP amplitudes, and fibular motor conduction velocity. Changes in fibular CMAP amplitude consistently correlated with NIS (R = −0.8 to −0.6, p ≤ 0.004) and INCAT disability score improvements (R = −0.6 to −0.3, p ≤ 0.032) across all follow‐up intervals up to 60 months. Ulnar and summated CMAP amplitude changes also correlated with clinical outcomes, though their associations were less sustained than those of fibular CMAP amplitude.InterpretationThe first change in fibular CMAP amplitude is a reliable biomarker for predicting CIDP treatment response, with ulnar and summated CMAP amplitudes as alternatives when the fibular response is absent. Our findings highlight the utility of first NCS changes in monitoring and predicting treatment outcomes in CIDP.

ABSTRACTBackground and AimsChronic inflammatory demyelinating polyradiculoneuropathy (CIDP) is difficult to distinguish from mimicking disorders, with misdiagnosis resulting in IVIG overutilization. We evaluate a clinical‐electrophysiological model to facilitate CIDP versus mimic neuropathy prediction.MethodsUsing the European Academy of Neurology/Peripheral Nerve Society (EAN/PNS) 2021 CIDP guidelines we derived 26 clinical and 144 nerve conduction variables. The model was generated and validated utilizing total CIDP (n = 129) and mimics (n = 309); including (1) IgG4‐nodopathies; (2) POEMS (polyneuropathy–organomegaly–endocrinopathy–monoclonal protein‐skin changes); (3) anti‐myelin‐associated‐glycoprotein; (4) paraneoplastic; (5) Waldenström B‐cell lymphoma; (6) diabetic neuropathies; (7) amyloidosis; (8) Charcot–Marie–Tooth; (9) motor neuropathies/neuronopathies; and (10) idiopathic‐inflammatory‐myopathies.ResultsWe analyzed 9282 clinical and 51 408 electrophysiological data points. Univariate analysis identified 11 of 26 clinical variables with significant odds ratios. A multivariate regression model using four clinical and two electrophysiologic variables achieved 93% area‐under‐curve (95% CI 91–95): progression over 8 weeks (OR 40.66, 95% CI 5.31–311.36), absent autonomic involvement (OR 17.82, 95% CI 2.93–108.24), absent muscle atrophy (OR 16.65, 95% CI 3.27–84.73), proximal weakness (OR 3.63, 95% CI 1.58–8.33), ulnar motor conduction velocity slowing < 35.7 m/s (OR 5.21, 95% CI 2.13–12.76), and ulnar motor conduction block (OR 13.37, 95% CI 2.47–72.40). A web‐based probability calculator (https://news.mayocliniclabs.com/cidp‐calculator/) was developed, with 100% sensitivity and 68% specificity at a 92% probability threshold. Specificity improved to 93% when considering “red flags,” electrophysiologic criteria, and laboratory testing.InterpretationA probability calculator using clinical electrophysiological variables assists CIDP differentiation from mimics, with scores below 92% unlikely to have CIDP. The highest specificity is achieved by considering clinical “red flags,” electrophysiologic demyelination, and laboratory testing.