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Depression in myasthenia gravis: a heterogeneous and intriguing entity
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,...
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Published in: | Journal of neurology 2020-06, Vol.267 (6), p.1802-1811 |
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container_title | Journal of neurology |
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creator | Gavrilov, Yury V. Alekseeva, Tatjana M. Kreis, Olga A. Valko, Philipp O. Weber, Konrad P. Valko, Yulia |
description | 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. |
doi_str_mv | 10.1007/s00415-020-09767-7 |
format | article |
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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.</description><identifier>ISSN: 0340-5354</identifier><identifier>EISSN: 1432-1459</identifier><identifier>DOI: 10.1007/s00415-020-09767-7</identifier><identifier>PMID: 32140868</identifier><language>eng</language><publisher>Berlin/Heidelberg: Springer Berlin Heidelberg</publisher><subject>Adult ; Cognitive ability ; Comorbidity ; Depression - diagnosis ; Depression - epidemiology ; Depression - physiopathology ; Fatigue ; Fatigue - diagnosis ; Fatigue - epidemiology ; Fatigue - physiopathology ; Female ; Humans ; Male ; Medicine ; Medicine & Public Health ; Mental depression ; Middle Aged ; Myasthenia ; Myasthenia gravis ; Myasthenia Gravis - diagnosis ; Myasthenia Gravis - epidemiology ; Myasthenia Gravis - physiopathology ; Neurology ; Neuromuscular junctions ; Neuroradiology ; Neurosciences ; Original Communication ; Patients ; Phenotypes ; Prevalence ; Russia - epidemiology ; Severity of Illness Index ; Sleep and wakefulness ; Thymectomy ; Thymectomy - statistics & numerical data</subject><ispartof>Journal of neurology, 2020-06, Vol.267 (6), p.1802-1811</ispartof><rights>Springer-Verlag GmbH Germany, part of Springer Nature 2020</rights><rights>Springer-Verlag GmbH Germany, part of Springer Nature 2020.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c419t-9b59346759e71cd410c1bb949bf73ac40a760d1aeee80001f35883c9bfb6f80c3</citedby><cites>FETCH-LOGICAL-c419t-9b59346759e71cd410c1bb949bf73ac40a760d1aeee80001f35883c9bfb6f80c3</cites><orcidid>0000-0003-2526-4582 ; 0000-0002-6147-1960</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,780,784,27924,27925</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/32140868$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Gavrilov, Yury V.</creatorcontrib><creatorcontrib>Alekseeva, Tatjana M.</creatorcontrib><creatorcontrib>Kreis, Olga A.</creatorcontrib><creatorcontrib>Valko, Philipp O.</creatorcontrib><creatorcontrib>Weber, Konrad P.</creatorcontrib><creatorcontrib>Valko, Yulia</creatorcontrib><title>Depression in myasthenia gravis: a heterogeneous and intriguing entity</title><title>Journal of neurology</title><addtitle>J Neurol</addtitle><addtitle>J Neurol</addtitle><description>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.</description><subject>Adult</subject><subject>Cognitive ability</subject><subject>Comorbidity</subject><subject>Depression - diagnosis</subject><subject>Depression - epidemiology</subject><subject>Depression - physiopathology</subject><subject>Fatigue</subject><subject>Fatigue - diagnosis</subject><subject>Fatigue - epidemiology</subject><subject>Fatigue - physiopathology</subject><subject>Female</subject><subject>Humans</subject><subject>Male</subject><subject>Medicine</subject><subject>Medicine & Public Health</subject><subject>Mental depression</subject><subject>Middle Aged</subject><subject>Myasthenia</subject><subject>Myasthenia gravis</subject><subject>Myasthenia Gravis - diagnosis</subject><subject>Myasthenia Gravis - epidemiology</subject><subject>Myasthenia Gravis - physiopathology</subject><subject>Neurology</subject><subject>Neuromuscular junctions</subject><subject>Neuroradiology</subject><subject>Neurosciences</subject><subject>Original Communication</subject><subject>Patients</subject><subject>Phenotypes</subject><subject>Prevalence</subject><subject>Russia - epidemiology</subject><subject>Severity of Illness Index</subject><subject>Sleep and wakefulness</subject><subject>Thymectomy</subject><subject>Thymectomy - statistics & numerical data</subject><issn>0340-5354</issn><issn>1432-1459</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2020</creationdate><recordtype>article</recordtype><recordid>eNp9kLFOwzAURS0EoqXwAwwoEgtL4Dm245gNFQpIlVhgtpz0JXXVOsVOkPr3mLaAxMDk4Z53fXUIOadwTQHkTQDgVKSQQQpK5jKVB2RIOctSyoU6JENgHFLBBB-QkxAWAFDE4JgMWEY5FHkxJJN7XHsMwbYusS5ZbUzo5uisSRpvPmy4TUwyxw5926DDtg-JcbNIdt42vXVNgq6z3eaUHNVmGfBs_47I2-ThdfyUTl8en8d307TiVHWpKoViPJdCoaTVjFOoaFkqrspaMlNxMDKHGTWIWMS1tGaiKFgV4zKvC6jYiFztete-fe8xdHplQ4XLpdmO0xmTnDEpBYvo5R900fbexXU64zTLBQOuIpXtqMq3IXis9drblfEbTUF_WdY7yzpa1lvLWsaji311X65w9nPyrTUCbAeEGLkG_e_f_9R-AlEthwA</recordid><startdate>20200601</startdate><enddate>20200601</enddate><creator>Gavrilov, Yury V.</creator><creator>Alekseeva, Tatjana M.</creator><creator>Kreis, Olga A.</creator><creator>Valko, Philipp O.</creator><creator>Weber, Konrad P.</creator><creator>Valko, Yulia</creator><general>Springer Berlin Heidelberg</general><general>Springer Nature B.V</general><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>3V.</scope><scope>7TK</scope><scope>7X7</scope><scope>7XB</scope><scope>88E</scope><scope>8AO</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>BENPR</scope><scope>CCPQU</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>K9.</scope><scope>M0S</scope><scope>M1P</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>7X8</scope><orcidid>https://orcid.org/0000-0003-2526-4582</orcidid><orcidid>https://orcid.org/0000-0002-6147-1960</orcidid></search><sort><creationdate>20200601</creationdate><title>Depression in myasthenia gravis: a heterogeneous and intriguing entity</title><author>Gavrilov, Yury V. ; Alekseeva, Tatjana M. ; Kreis, Olga A. ; Valko, Philipp O. ; Weber, Konrad P. ; Valko, Yulia</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c419t-9b59346759e71cd410c1bb949bf73ac40a760d1aeee80001f35883c9bfb6f80c3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2020</creationdate><topic>Adult</topic><topic>Cognitive ability</topic><topic>Comorbidity</topic><topic>Depression - diagnosis</topic><topic>Depression - epidemiology</topic><topic>Depression - physiopathology</topic><topic>Fatigue</topic><topic>Fatigue - diagnosis</topic><topic>Fatigue - epidemiology</topic><topic>Fatigue - physiopathology</topic><topic>Female</topic><topic>Humans</topic><topic>Male</topic><topic>Medicine</topic><topic>Medicine & Public Health</topic><topic>Mental depression</topic><topic>Middle Aged</topic><topic>Myasthenia</topic><topic>Myasthenia gravis</topic><topic>Myasthenia Gravis - diagnosis</topic><topic>Myasthenia Gravis - epidemiology</topic><topic>Myasthenia Gravis - physiopathology</topic><topic>Neurology</topic><topic>Neuromuscular junctions</topic><topic>Neuroradiology</topic><topic>Neurosciences</topic><topic>Original Communication</topic><topic>Patients</topic><topic>Phenotypes</topic><topic>Prevalence</topic><topic>Russia - epidemiology</topic><topic>Severity of Illness Index</topic><topic>Sleep and wakefulness</topic><topic>Thymectomy</topic><topic>Thymectomy - statistics & numerical data</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Gavrilov, Yury V.</creatorcontrib><creatorcontrib>Alekseeva, Tatjana M.</creatorcontrib><creatorcontrib>Kreis, Olga A.</creatorcontrib><creatorcontrib>Valko, Philipp O.</creatorcontrib><creatorcontrib>Weber, Konrad P.</creatorcontrib><creatorcontrib>Valko, Yulia</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>Neurosciences Abstracts</collection><collection>ProQuest - Health & Medical Complete保健、医学与药学数据库</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Medical Database (Alumni Edition)</collection><collection>ProQuest Pharma Collection</collection><collection>Hospital Premium Collection</collection><collection>Hospital Premium Collection (Alumni Edition)</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>ProQuest Central (Alumni)</collection><collection>ProQuest Central</collection><collection>ProQuest Central</collection><collection>ProQuest One Community College</collection><collection>Health Research Premium Collection</collection><collection>Health Research Premium Collection (Alumni)</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>Health & Medical Collection (Alumni Edition)</collection><collection>Medical Database</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><collection>MEDLINE - Academic</collection><jtitle>Journal of neurology</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Gavrilov, Yury V.</au><au>Alekseeva, Tatjana M.</au><au>Kreis, Olga A.</au><au>Valko, Philipp O.</au><au>Weber, Konrad P.</au><au>Valko, Yulia</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Depression in myasthenia gravis: a heterogeneous and intriguing entity</atitle><jtitle>Journal of neurology</jtitle><stitle>J Neurol</stitle><addtitle>J Neurol</addtitle><date>2020-06-01</date><risdate>2020</risdate><volume>267</volume><issue>6</issue><spage>1802</spage><epage>1811</epage><pages>1802-1811</pages><issn>0340-5354</issn><eissn>1432-1459</eissn><abstract>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.</abstract><cop>Berlin/Heidelberg</cop><pub>Springer Berlin Heidelberg</pub><pmid>32140868</pmid><doi>10.1007/s00415-020-09767-7</doi><tpages>10</tpages><orcidid>https://orcid.org/0000-0003-2526-4582</orcidid><orcidid>https://orcid.org/0000-0002-6147-1960</orcidid><oa>free_for_read</oa></addata></record> |
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subjects | Adult Cognitive ability Comorbidity Depression - diagnosis Depression - epidemiology Depression - physiopathology Fatigue Fatigue - diagnosis Fatigue - epidemiology Fatigue - physiopathology Female Humans Male Medicine Medicine & Public Health Mental depression Middle Aged Myasthenia Myasthenia gravis Myasthenia Gravis - diagnosis Myasthenia Gravis - epidemiology Myasthenia Gravis - physiopathology Neurology Neuromuscular junctions Neuroradiology Neurosciences Original Communication Patients Phenotypes Prevalence Russia - epidemiology Severity of Illness Index Sleep and wakefulness Thymectomy Thymectomy - statistics & numerical data |
title | Depression in myasthenia gravis: a heterogeneous and intriguing entity |
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