Quantitative assessment of motor impairment and surgical outcome in Hirayama disease with proximal involvement using motor unit number index.

Journal: Neurophysiologie Clinique = Clinical Neurophysiology
Published:
Abstract

Objective: To assess the feasibility of motor unit number index (MUNIX) in quantitatively evaluating Hirayama disease (HD) with proximal involvement and to identify the effectiveness of anterior cervical fusion (ACF) in treating atypical HD with proximal involvement.

Methods: This study included 28 atypical HD patients with proximal involvement (proximal-distal vs. distal-proximal groups: 5 vs. 23) and 41 healthy controls. All patients underwent pre- and postoperative 1-year MUNIX tests on abductor pollicis brevis (APB), abductor digiti minimi (ADM), biceps brachii (BB) and deltoid (Del). The disabilities of arm, shoulder and hand (DASH) and Medical Research Council (MRC) scales were also performed in these patients before and one year after operation.

Results: Preoperatively, the patients in the distal-proximal group showed reduced compound muscle action potential (CMAP), decreased MUNIX and increased motor unit size index (MUSIX) in bilateral distal muscles and symptomatic-side proximal muscles (P < 0.05), and similar abnormalities were also observed in ADM, BB and Del on the symptomatic side in the proximal-distal groups (P < 0.05). Postoperative follow-up analysis identified increased MUNIX in the symptomatic-side proximal muscles with improved motor function in the proximal-distal groups (P < 0.05), and distal-proximal group patients showed an increase in both CMAP and MUSIX in the symptomatic-side proximal muscles (P < 0.05).

Conclusions: MUNIX may serve as an available supplementary test to quantitatively evaluate the motor dysfunction and treatment outcome in HD with proximal involvement. ACF procedures can effectively treat these atypical HD patients, especially for those whose symptoms started in proximal muscles.

Authors
Chaojun Zheng, Yu Zhu, Qifeng Yu, Dongqing Zhu, Jun Li, Feizhou Lyu, Robert Weber, Kai Qiao, Jianyuan Jiang

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