O objetivo deste estudo foi avaliar se a razão entre as amplitudes dos potenciais de ação sensitivo (SNAP) e motor (CMAP) do nervo ulnar (USMAR) auxiliaria na distinção entre ganglionopatia (GNP) e polineuropatia (PNP).MétodosRevisamos os estudos de neurocondução e eletromiografia de 18 pacientes com GNP, 33 com PNP diabética e 56 controles. GNP foi definida pela presença simultânea de anormalidades na neurocondução e na ressonância magnética cervical. PNP foi definida por critérios clínicos e neurofisiológicos usuais. Usamos o teste ANOVA com Tukey post-hoc e análise da curva ROC para comparar o SNAP e CMAP ulnares, assim como o USMAR entre os grupos.ResultadosAs amplitudes dos CMAPs ulnares foram similares entre GNP × PNP × Controles (p=0,253), mas as amplitudes dos SNAPs ulnares (1,6±3,2 × 11,9±9,1 × 45,7±24,7) e os valores de USMAR (0,3±0,3 × 1,5±0,9 × 4,6±2,2) foram significativamente diferentes. Um corte de 0,71 para a USMAR foi capaz de diferenciar GNP de PNP (sensibilidade de 94,4% e especificidade de 90,9%).ConclusõesA USMAR é um parâmetro útil e confiável para o diagnóstico diferencial entre GNP e PNP.

The objective of this study was to evaluate if the ratio of ulnar sensory nerve action potential (SNAP) over compound muscle action potential (CMAP) amplitudes (USMAR) would help in the distinction between ganglionopathy (GNP) and polyneuropathy (PNP).MethodsWe reviewed the nerve conductions studies and electromyography (EMG) of 18 GNP patients, 33 diabetic PNP patients and 56 controls. GNP was defined by simultaneous nerve conduction studies (NCS) and magnetic resonance imaging (MRI) abnormalities. PNP was defined by usual clinical and NCS criteria. We used ANOVA with post-hoc Tukey test and ROC curve analysis to compare ulnar SNAP and CMAP, as well as USMAR in the groups.ResultsUlnar CMAP amplitudes were similar between GNP x PNP x Controls (p=0.253), but ulnar SNAP amplitudes (1.6±3.2 x 11.9±9.1 × 45.7±24.7) and USMAR values (0.3±0.3 × 1.5±0.9 × 4.6±2.2) were significantly different. A USMAR threshold of 0.71 was able to differentiate GNP and PNP (94.4% sensitivity and 90.9% specificity).ConclusionsUSMAR is a practical and reliable tool for the differentiation between GNP and PNP.