Diagnosis and Treatment Methods of Autoimmune Myasthenia Gravis: A Systematic Review

Year 2022, Volume: 4 Issue: 2, 104 - 116, 31.07.2022

Melike Nur Yangın Yaşar Zorlu Feride Severcan

Abstract

Myasthenia Gravis causes abnormalities in the neuromuscular junction, which is an autoimmune disorder and has a prevalence of 15-20 per 100,000 people. Although skeletal and extraocular muscles are commonly affected by the disease, approximately 10% of patients have severe involvement in the muscles necessary for respiration. A myasthenic crisis may cause life-threatening consequences. The prevalence and incidence of autoimmune MG increase with age. Women's disease incidence peaks between the ages of 30 and 40, while men's incidence peaks between the ages of 60 and 80. The existence of autoantibodies against postsynaptic membrane proteins is the most crucial indicator of myasthenia gravis. Anti-AChR (acetylcholine receptor antibody) positive is a distinct feature of MG (% 80). While anti-MuSK (muscle-specific kinase antibody) positivity is detected in 1-10% of all patients, LRP4 (low density lipoprotein receptor related protein 4) antibody positivity is seen in 3-25% of MG patients without AChR and MuSK antibodies (anti-LRP4). Despite many methods used in the diagnosis of Myasthenia Gravis, it is not possible to make the diagnosis in some patients because of conditions that may vary from patient to patient, such as fluctuation in symptoms and clinical findings. Rapid diagnosis is crucial in patients with Myasthenia Gravis, because effective treatment must begin as early as possible to prevent potentially fatal complications. Moreover, rapid diagnosis of patients and determination of the patient's subtype is an important step in the treatment process. Therefore, the aim of this study is to summarize the techniques used in the diagnosis and treatment of myasthenia gravis which is one of the rare diseases.

Keywords

Myasthenia Gravis, Diagnosis Methods, Treatment Methods, Rare Diseases, Neuromuscular Disorders, Autoimmune Disorders

Supporting Institution

Tübitak; Altınbaş Üniversitesi

Project Number

TUBITAK-1003-SBAG-218S986; AYP2021-3

Thanks

Türkiye Bilimsel ve Teknik Araştırma Kurumu, TÜBİTAK-1003 SBAG-Proje no:218S986 ve Altınbaş Üniversitesi, AYP2021-3 projesine teşekkür ederiz.

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