Clinical biomarkers differentiate myelitis from vascular and other causes of myelopathy
OBJECTIVETo assess the predictive value of the initial clinical and paraclinical features in the differentiation of inflammatory myelopathies from other causes of myelopathy in patients with initial diagnosis of transverse myelitis (TM). METHODSWe analyzed the clinical presentation, spinal cord MRI,...
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| Veröffentlicht in: | Neurology 2018-01, Vol.90 (1), p.e12-e21 |
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| creator | Barreras, Paula Fitzgerald, Kathryn C Mealy, Maureen A Jimenez, Jorge A Becker, Daniel Newsome, Scott D Levy, Michael Gailloud, Philippe Pardo, Carlos A |
| description | OBJECTIVETo assess the predictive value of the initial clinical and paraclinical features in the differentiation of inflammatory myelopathies from other causes of myelopathy in patients with initial diagnosis of transverse myelitis (TM).
METHODSWe analyzed the clinical presentation, spinal cord MRI, and CSF features in a cohort of 457 patients referred to a specialized myelopathy center with the presumptive diagnosis of TM. After evaluation, the myelopathies were classified as inflammatory, ischemic/stroke, arteriovenous malformations/fistulas, spondylotic, or other. A multivariable logistic regression model was used to determine characteristics associated with the final diagnosis and predictors that would improve classification accuracy.
RESULTSOut of 457 patients referred as TM, only 247 (54%) were confirmed as inflammatory; the remaining 46% were diagnosed as vascular (20%), spondylotic (8%), or other myelopathy (18%). Our predictive model identified the temporal profile of symptom presentation (hyperacute 21 days), initial motor examination, and MRI lesion distribution as characteristics that improve the correct classification rate of myelopathies from 67% to 87% (multinomial area under the curve increased from 0.32 to 0.67), compared to only considering CSF pleocytosis and MRI gadolinium enhancement. Of all predictors, the temporal profile of symptoms contributed the most to the increased discriminatory power.
CONCLUSIONSThe temporal profile of symptoms serves as a clinical biomarker in the differential diagnosis of TM. The establishment of a definite diagnosis in TM requires a critical analysis of the MRI and CSF characteristics to rule out non-inflammatory causes of myelopathy.
CLASSIFICATION OF EVIDENCEThis study provides Class IV evidence that for patients presenting with myelopathy, temporal profile of symptoms, initial motor examination, and MRI lesion distribution distinguish those with inflammatory myelopathies from those with other causes of myelopathy. |
| doi_str_mv | 10.1212/WNL.0000000000004765 |
| format | Article |
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METHODSWe analyzed the clinical presentation, spinal cord MRI, and CSF features in a cohort of 457 patients referred to a specialized myelopathy center with the presumptive diagnosis of TM. After evaluation, the myelopathies were classified as inflammatory, ischemic/stroke, arteriovenous malformations/fistulas, spondylotic, or other. A multivariable logistic regression model was used to determine characteristics associated with the final diagnosis and predictors that would improve classification accuracy.
RESULTSOut of 457 patients referred as TM, only 247 (54%) were confirmed as inflammatory; the remaining 46% were diagnosed as vascular (20%), spondylotic (8%), or other myelopathy (18%). Our predictive model identified the temporal profile of symptom presentation (hyperacute <6 hours, acute 6–48 hours, subacute 48 hours–21 days, chronic >21 days), initial motor examination, and MRI lesion distribution as characteristics that improve the correct classification rate of myelopathies from 67% to 87% (multinomial area under the curve increased from 0.32 to 0.67), compared to only considering CSF pleocytosis and MRI gadolinium enhancement. Of all predictors, the temporal profile of symptoms contributed the most to the increased discriminatory power.
CONCLUSIONSThe temporal profile of symptoms serves as a clinical biomarker in the differential diagnosis of TM. The establishment of a definite diagnosis in TM requires a critical analysis of the MRI and CSF characteristics to rule out non-inflammatory causes of myelopathy.
CLASSIFICATION OF EVIDENCEThis study provides Class IV evidence that for patients presenting with myelopathy, temporal profile of symptoms, initial motor examination, and MRI lesion distribution distinguish those with inflammatory myelopathies from those with other causes of myelopathy.</description><identifier>ISSN: 0028-3878</identifier><identifier>EISSN: 1526-632X</identifier><identifier>DOI: 10.1212/WNL.0000000000004765</identifier><identifier>PMID: 29196574</identifier><language>eng</language><publisher>United States: American Academy of Neurology</publisher><subject>Adult ; Aged ; Biomarkers - cerebrospinal fluid ; Cohort Studies ; Diagnosis, Differential ; Disease Progression ; Female ; Humans ; Magnetic Resonance Imaging ; Male ; Middle Aged ; Myelitis, Transverse - diagnosis ; Neurologic Examination ; Retrospective Studies ; Spinal Cord - diagnostic imaging ; Spinal Cord Diseases - classification ; Spinal Cord Diseases - diagnosis ; Time Factors</subject><ispartof>Neurology, 2018-01, Vol.90 (1), p.e12-e21</ispartof><rights>2018 American Academy of Neurology</rights><rights>Copyright © 2017 The Author(s). Published by Wolters Kluwer Health, Inc. on behalf of the American Academy of Neurology.</rights><rights>Copyright © 2017 The Author(s). Published by Wolters Kluwer Health, Inc. on behalf of the American Academy of Neurology. 2017 American Academy of Neurology</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c5235-d6c9c011145c9c95a2c272f2852114c1a0607e238cc85dad526b37ee9ab36a883</citedby><cites>FETCH-LOGICAL-c5235-d6c9c011145c9c95a2c272f2852114c1a0607e238cc85dad526b37ee9ab36a883</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>230,314,776,780,881,27901,27902</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/29196574$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Barreras, Paula</creatorcontrib><creatorcontrib>Fitzgerald, Kathryn C</creatorcontrib><creatorcontrib>Mealy, Maureen A</creatorcontrib><creatorcontrib>Jimenez, Jorge A</creatorcontrib><creatorcontrib>Becker, Daniel</creatorcontrib><creatorcontrib>Newsome, Scott D</creatorcontrib><creatorcontrib>Levy, Michael</creatorcontrib><creatorcontrib>Gailloud, Philippe</creatorcontrib><creatorcontrib>Pardo, Carlos A</creatorcontrib><title>Clinical biomarkers differentiate myelitis from vascular and other causes of myelopathy</title><title>Neurology</title><addtitle>Neurology</addtitle><description>OBJECTIVETo assess the predictive value of the initial clinical and paraclinical features in the differentiation of inflammatory myelopathies from other causes of myelopathy in patients with initial diagnosis of transverse myelitis (TM).
METHODSWe analyzed the clinical presentation, spinal cord MRI, and CSF features in a cohort of 457 patients referred to a specialized myelopathy center with the presumptive diagnosis of TM. After evaluation, the myelopathies were classified as inflammatory, ischemic/stroke, arteriovenous malformations/fistulas, spondylotic, or other. A multivariable logistic regression model was used to determine characteristics associated with the final diagnosis and predictors that would improve classification accuracy.
RESULTSOut of 457 patients referred as TM, only 247 (54%) were confirmed as inflammatory; the remaining 46% were diagnosed as vascular (20%), spondylotic (8%), or other myelopathy (18%). Our predictive model identified the temporal profile of symptom presentation (hyperacute <6 hours, acute 6–48 hours, subacute 48 hours–21 days, chronic >21 days), initial motor examination, and MRI lesion distribution as characteristics that improve the correct classification rate of myelopathies from 67% to 87% (multinomial area under the curve increased from 0.32 to 0.67), compared to only considering CSF pleocytosis and MRI gadolinium enhancement. Of all predictors, the temporal profile of symptoms contributed the most to the increased discriminatory power.
CONCLUSIONSThe temporal profile of symptoms serves as a clinical biomarker in the differential diagnosis of TM. The establishment of a definite diagnosis in TM requires a critical analysis of the MRI and CSF characteristics to rule out non-inflammatory causes of myelopathy.
CLASSIFICATION OF EVIDENCEThis study provides Class IV evidence that for patients presenting with myelopathy, temporal profile of symptoms, initial motor examination, and MRI lesion distribution distinguish those with inflammatory myelopathies from those with other causes of myelopathy.</description><subject>Adult</subject><subject>Aged</subject><subject>Biomarkers - cerebrospinal fluid</subject><subject>Cohort Studies</subject><subject>Diagnosis, Differential</subject><subject>Disease Progression</subject><subject>Female</subject><subject>Humans</subject><subject>Magnetic Resonance Imaging</subject><subject>Male</subject><subject>Middle Aged</subject><subject>Myelitis, Transverse - diagnosis</subject><subject>Neurologic Examination</subject><subject>Retrospective Studies</subject><subject>Spinal Cord - diagnostic imaging</subject><subject>Spinal Cord Diseases - classification</subject><subject>Spinal Cord Diseases - diagnosis</subject><subject>Time Factors</subject><issn>0028-3878</issn><issn>1526-632X</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2018</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNp9kU1v1DAQhi0EotvCP0AoRy4pthN_XZDQqkClFVxatTdr1pkQUyde7KTV_ntMt1SFA76M5Xnm9cy8hLxh9JRxxt9ffd2c0ienVVI8IysmuKxlw6-fkxWlXNeNVvqIHOf8g9KSVOYlOeKGGSlUuyJX6-An7yBUWx9HSDeYctX5vseE0-xhxmrcY_Czz1Wf4ljdQnZLgFTB1FVxHjBVDpaMuYr9PRp3MA_7V-RFDyHj64d4Qi4_nV2sv9Sbb5_P1x83tRO8EXUnnXGUMdaKcjECuOOK91wLXt4cAyqpQt5o57TooCvDbRuFaGDbSNC6OSEfDrq7ZTti50rTCYLdJV-G2dsI3v6dmfxgv8dbK5RoZSuLwLsHgRR_LphnO_rsMASYMC7ZMqOYNNzQtqDtAXUp5pywf_yGUfvbE1s8sf96UsrePm3xseiPCQXQB-Auhrns_yYsd5jsgBDm4f_avwCO8pqj</recordid><startdate>20180102</startdate><enddate>20180102</enddate><creator>Barreras, Paula</creator><creator>Fitzgerald, Kathryn C</creator><creator>Mealy, Maureen A</creator><creator>Jimenez, Jorge A</creator><creator>Becker, Daniel</creator><creator>Newsome, Scott D</creator><creator>Levy, Michael</creator><creator>Gailloud, Philippe</creator><creator>Pardo, Carlos A</creator><general>American Academy of Neurology</general><general>Lippincott Williams & Wilkins</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>7X8</scope><scope>5PM</scope></search><sort><creationdate>20180102</creationdate><title>Clinical biomarkers differentiate myelitis from vascular and other causes of myelopathy</title><author>Barreras, Paula ; Fitzgerald, Kathryn C ; Mealy, Maureen A ; Jimenez, Jorge A ; Becker, Daniel ; Newsome, Scott D ; Levy, Michael ; Gailloud, Philippe ; Pardo, Carlos A</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c5235-d6c9c011145c9c95a2c272f2852114c1a0607e238cc85dad526b37ee9ab36a883</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2018</creationdate><topic>Adult</topic><topic>Aged</topic><topic>Biomarkers - cerebrospinal fluid</topic><topic>Cohort Studies</topic><topic>Diagnosis, Differential</topic><topic>Disease Progression</topic><topic>Female</topic><topic>Humans</topic><topic>Magnetic Resonance Imaging</topic><topic>Male</topic><topic>Middle Aged</topic><topic>Myelitis, Transverse - diagnosis</topic><topic>Neurologic Examination</topic><topic>Retrospective Studies</topic><topic>Spinal Cord - diagnostic imaging</topic><topic>Spinal Cord Diseases - classification</topic><topic>Spinal Cord Diseases - diagnosis</topic><topic>Time Factors</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Barreras, Paula</creatorcontrib><creatorcontrib>Fitzgerald, Kathryn C</creatorcontrib><creatorcontrib>Mealy, Maureen A</creatorcontrib><creatorcontrib>Jimenez, Jorge A</creatorcontrib><creatorcontrib>Becker, Daniel</creatorcontrib><creatorcontrib>Newsome, Scott D</creatorcontrib><creatorcontrib>Levy, Michael</creatorcontrib><creatorcontrib>Gailloud, Philippe</creatorcontrib><creatorcontrib>Pardo, Carlos A</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>MEDLINE - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><jtitle>Neurology</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Barreras, Paula</au><au>Fitzgerald, Kathryn C</au><au>Mealy, Maureen A</au><au>Jimenez, Jorge A</au><au>Becker, Daniel</au><au>Newsome, Scott D</au><au>Levy, Michael</au><au>Gailloud, Philippe</au><au>Pardo, Carlos A</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Clinical biomarkers differentiate myelitis from vascular and other causes of myelopathy</atitle><jtitle>Neurology</jtitle><addtitle>Neurology</addtitle><date>2018-01-02</date><risdate>2018</risdate><volume>90</volume><issue>1</issue><spage>e12</spage><epage>e21</epage><pages>e12-e21</pages><issn>0028-3878</issn><eissn>1526-632X</eissn><abstract>OBJECTIVETo assess the predictive value of the initial clinical and paraclinical features in the differentiation of inflammatory myelopathies from other causes of myelopathy in patients with initial diagnosis of transverse myelitis (TM).
METHODSWe analyzed the clinical presentation, spinal cord MRI, and CSF features in a cohort of 457 patients referred to a specialized myelopathy center with the presumptive diagnosis of TM. After evaluation, the myelopathies were classified as inflammatory, ischemic/stroke, arteriovenous malformations/fistulas, spondylotic, or other. A multivariable logistic regression model was used to determine characteristics associated with the final diagnosis and predictors that would improve classification accuracy.
RESULTSOut of 457 patients referred as TM, only 247 (54%) were confirmed as inflammatory; the remaining 46% were diagnosed as vascular (20%), spondylotic (8%), or other myelopathy (18%). Our predictive model identified the temporal profile of symptom presentation (hyperacute <6 hours, acute 6–48 hours, subacute 48 hours–21 days, chronic >21 days), initial motor examination, and MRI lesion distribution as characteristics that improve the correct classification rate of myelopathies from 67% to 87% (multinomial area under the curve increased from 0.32 to 0.67), compared to only considering CSF pleocytosis and MRI gadolinium enhancement. Of all predictors, the temporal profile of symptoms contributed the most to the increased discriminatory power.
CONCLUSIONSThe temporal profile of symptoms serves as a clinical biomarker in the differential diagnosis of TM. The establishment of a definite diagnosis in TM requires a critical analysis of the MRI and CSF characteristics to rule out non-inflammatory causes of myelopathy.
CLASSIFICATION OF EVIDENCEThis study provides Class IV evidence that for patients presenting with myelopathy, temporal profile of symptoms, initial motor examination, and MRI lesion distribution distinguish those with inflammatory myelopathies from those with other causes of myelopathy.</abstract><cop>United States</cop><pub>American Academy of Neurology</pub><pmid>29196574</pmid><doi>10.1212/WNL.0000000000004765</doi><oa>free_for_read</oa></addata></record> |
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| subjects | Adult Aged Biomarkers - cerebrospinal fluid Cohort Studies Diagnosis, Differential Disease Progression Female Humans Magnetic Resonance Imaging Male Middle Aged Myelitis, Transverse - diagnosis Neurologic Examination Retrospective Studies Spinal Cord - diagnostic imaging Spinal Cord Diseases - classification Spinal Cord Diseases - diagnosis Time Factors |
| title | Clinical biomarkers differentiate myelitis from vascular and other causes of myelopathy |
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