Neuralgic amyotrophy: a paradigm shift in diagnosis and treatment. Issue 8 (2nd June 2020)

• Record Type: Journal Article
• Authors: Gstoettner, Clemens; Mayer, Johannes A; Rassam, Stephanie; Hruby, Laura A; Salminger, Stefan; Sturma, Agnes; Aman, Martin; Harhaus, Leila; Platzgummer, Hannes; Aszmann, Oskar C
• Is Part Of: Journal of neurology, neurosurgery and psychiatry. Volume 91:Issue 8(2020)
• Page Start: 879
• Page End: 888
• Publication Date: 2020-06-02
• Subjects: peripheral nerve surgery -- clinical neurology -- neurosurgery -- neuromuscular; Neurology -- Periodicals; Nervous system -- Surgery -- Periodicals; Psychiatry -- Periodicals; 616.8
• DOI: 10.1136/jnnp-2020-323164
• Languages: English
• ISSNs: 0022-3050

Abstract

Abstract : Neuralgic amyotrophy (NA), also known as Parsonage-Turner syndrome, is characterised by sudden pain attacks, followed by patchy muscle paresis in the upper extremity. Recent reports have shown that incidence is much higher than previously assumed and that the majority of patients never achieve full recovery. Traditionally, the diagnosis was mainly based on clinical observations and treatment options were confined to application of corticosteroids and symptomatic management, without proven positive effects on long-term outcomes. These views, however, have been challenged in the last years. Improved imaging methods in MRI and high-resolution ultrasound have led to the identification of structural peripheral nerve pathologies in NA, most notably hourglass-like constrictions. These pathognomonic findings have paved the way for more accurate diagnosis through high-resolution imaging. Furthermore, surgery has shown to improve clinical outcomes in such cases, indicating the viability of peripheral nerve surgery as a valuable treatment option in NA. In this review, we present an update on the current knowledge on this disease, including pathophysiology and clinical presentation, moving on to diagnostic and treatment paradigms with a focus on recent radiological findings and surgical reports. Finally, we present a surgical treatment algorithm to support clinical decision making, with the aim to encourage translation into day-to-day practice.