PROGRESSIYALANUVCHI MUSHAK DISTROFIYALARIDA ELEKTROMIOGRAFIK KO‘RSATKICHLARNING XUSUSIYATLARI
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progressiyalanuvchi mushak distrofiyasi, elektromiografiya, harakat birliklari potensiallari, miopatik o‘zgarishlar, diagnostik biomarkerlar, kasallik progressiyasi##article.abstract##
Tadqiqotning maqsadi — progressiyalanuvchi mushak distrofiyalari (PMD) bilan kasallangan bemorlarda elektromiografik ko‘rsatkichlarning o‘ziga xos xususiyatlarini baholash hamda ularning diagnostik va prognostik ahamiyatini aniqlashdan iborat. Materiallar va usullar: 2022–2024-yillar davomida PMD bilan kasallangan 158 nafar bemor tekshirildi: Dyushenn mushak distrofiyasi (45 nafar bemor), Bekker mushak distrofiyasi (38 nafar), Erb–Rot distrofiyasi (42 nafar) va Landuzi–Dejerin distrofiyasi (33 nafar). Nazorat guruhini 55 nafar sog‘lom shaxs tashkil etdi.
Standartlashtirilgan protokollar asosida ignali elektromiografiya, nerv o‘tkazuvchanligini tekshirish hamda miqdoriy EMG tahlili o‘tkazildi. Harakat birliklari potensiallari parametrlari, spontan faollik, rekrutatsiya patternlari va impuls o‘tkazuvchanligi tezligi tahlil qilindi.
PMDning barcha turlarida miopatik o‘zgarishlarga xos belgilar kuzatildi va ular orasida sezilarli farqlar aniqlandi. Eng og‘ir o‘zgarishlar Dyushen distrofiyasida qayd etildi: harakat birliklari potensiallari amplitudasining pasayishi (284±89 mкV ga nisbatan nazorat guruhida 1245±156 mкV), davomiyligining qisqarishi (6,8±2,1 ms ga nisbatan 12,4±2,8 ms), polifaziyaning ortishi (68,4±12,3% ga nisbatan 15,2±4,1%) va yaqqol spontan faollik. EMG o‘zgarishlari og‘irligi bilan klinik nogironlik darajasi o‘rtasida progressiv korrelyatsiya aniqlangan (r=0,79–0,85).
Elektromiografik ko‘rsatkichlar PMDni diagnostika qilish, subtiplarini differensial ajratish, kasallik progressiyasini monitoring qilish va davolash samaradorligini baholash uchun muhim biomarker hisoblanadi. Miqdoriy EMG tahlili klinik amaliyotda diagnostik aniqlik va prognostik baholashni oshiradi.
Библиографические ссылки
Bushby K., et al. Integration of electromyographic and serum biomarkers in progressive muscular dystrophies: a systems biology approach. Nature Medicine. 2023;29(8):1892-1905.
Chen L., et al. Deep learning algorithms for automated EMG pattern recognition in muscular dystrophies. The Lancet Digital Health. 2024;6(3):e187-e196.
Farina D., et al. High-density surface EMG for early detection of muscle involvement in Duchenne muscular dystrophy. Nature Biomedical Engineering. 2023;7(4):445-458.
Finkel R.S., et al. Age-specific normative values for quantitative EMG parameters in pediatric populations. Muscle & Nerve. 2024;69(2):178-189.
Gooch C.L., et al. Motor unit number estimation in progressive muscular dystrophies: a comprehensive meta-analysis. Neurology. 2023;101(12):e1234-e1247.
Griggs R.C., et al. Ten-year longitudinal study of electromyographic progression in muscular dystrophies. Annals of Neurology. 2024;95(3):412-425.
Hoffman E.P., et al. Molecular mechanisms of dystrophin deficiency and therapeutic implications. Nature Reviews Neurology. 2023;19(7):398-412.
Kimura J., et al. Updated guidelines for electromyographic assessment in muscular dystrophies. Clinical Neurophysiology. 2023;154:78-92.
McDonald C.M., et al. Cost-effectiveness of early EMG-based diagnosis in progressive muscular dystrophies. Health Economics. 2023;32(8):1756-1768.
Mendell J.R., et al. Electromyographic biomarkers in gene therapy trials for Duchenne muscular dystrophy. Molecular Therapy. 2023;31(9):2678-2691.
Mercuri E., et al. Global epidemiology and clinical burden of progressive muscular dystrophies. The Lancet Neurology. 2023;22(5):456-469.
Padberg G.W., et al. Single fiber EMG abnormalities in progressive muscular dystrophies: pathophysiological insights. Muscle & Nerve. 2024;70(4):445-456.
Rodriguez-Cruz P.M., et al. Quantitative EMG analysis in neuromuscular disorders: technical advances and clinical applications. Brain. 2024;147(6):2134-2149.
Stalberg E., et al. Myopathic index: a novel composite biomarker for muscular dystrophy diagnosis. Clinical Neurophysiology. 2024;165:89-98.
Tawil R., et al. Electromyographic signatures across fifteen progressive muscular dystrophy subtypes. Brain. 2024;147(8):2789-2804.
