Could we Predict Respiratory Failure in Amyotrophic Lateral Sclerosis?

NEUROLOGICAL SCIENCES AND NEUROPHYSIOLOGY(2022)

引用 0|浏览0
暂无评分
摘要
Introduction: Respiratory complications are important in the prognosis of amyotrophic lateral sclerosis (ALS). The aim of this study was to determine the electrophysiological findings that may predict respiratory failure. Methods: According to the Awaji electrodiagnostic criteria, 30 patients with ALS who were diagnosed with definite or probable ALS without respiratory failure were included in the study. Nerve conduction studies, needle electromyography (EMG), and single-breath count tests were performed in all patients. In addition, the pulmonary function tests, swallowing EMG, and arterial blood gas analysis of the patients were recorded and evaluated. The patients were followed until respiratory failure developed. Results: As a result of 18 months of follow-up, 26 of 30 patients developed respiratory failure. When the contribution of the accessory respiratory muscles to the respiratory effort before the development of respiratory failure was evaluated clinically and electrophysiologically, it was observed that the most common muscles involved in the respiratory effort were sternocleidomastoid (SCM), trapezius, and rectus abdominis. Before the development of respiratory failure, the latest neurogenic EMG findings were seen in the SCM (50% cases), trapezius (20% cases), and thoracic paraspinal muscles (17% of cases), respectively. It was thought that this finding could be an important early electrophysiologic marker in predicting the development of respiratory failure in ALS cases. Conclusions: To sum up, the presence of neurogenic changes in certain muscles in needle EMG and demonstration of the contribution of certain accessory respiratory muscles in respiration can be used as an electrophysiological marker to predict the development of respiratory failure.
更多
查看译文
关键词
Amyotrophic lateral sclerosis, early electrophysiologic marker, electromyography, electrophysiological evaluation, respiratory failure
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要