Lu sur : https://www.ncbi.nlm.nih.gov/pubmed/32140868
Dépression dans la myasthénie grave: une entité hétérogène et intrigante.
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Titre de l'article Depression in myasthenia gravis: a heterogeneous and intriguing entity.
Date de l'article J Neurol. 2020 Mar 5. doi: 10.1007/s00415-020-09767-7. [Epub ahead of print]
Contenu de l'article
BACKGROUND: Depressive symptoms in myasthenia gravis (MG) are common, may mimic other disease features, and contribute to misdiagnosis and diagnostic delay. Nevertheless, the clinical determinants of depressive symptoms in MG remain poorly studied, in particular their overlap with fatigue. Moreover, studies in MG have rarely looked at distinct depression phenotypes.
METHODS: In 68 consecutive MG patients, we ascertained cognitive-affective and somatic depression with the Beck Depression Inventory (BDI), and also assessed age at disease onset, education, marital state, work ability, sleepiness, fatigue, and treatment modalities. Disease severity was graded according to the Myasthenia Gravis Foundation of America (MGFA) classification.
RESULTS: The prevalence of moderate-severe depression was 20.5%. While depression and fatigue showed large overlap (n = 37, 54.4%), only fatigue increased with disease severity, while BDI scores did not. Thymectomy was independently associated with lower BDI scores, but had no impact on fatigue. Total BDI scores were similar in patients with predominantly cognitive-affective and with predominantly somatic depression. However, ESS correlated only with cognitive-affective BDI, and younger age was independently associated with cognitive-affective BDI. Conversely, female sex and thymectomy were independently associated with somatic BDI.
CONCLUSIONS: Depression and fatigue are highly prevalent and largely overlapping comorbidities in MG, but only fatigue increased with disease severity, and only depression was milder in thymectomized patients. Comparative use of BDI subscales in MG reveals distinct depression phenotypes with distinct correlations to other disease features.
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