Assessment of sudomotor function View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2019-02

AUTHORS

Sylvia J. Buchmann, Ana Isabel Penzlin, Marie Luise Kubasch, Ben Min-Woo Illigens, Timo Siepmann

ABSTRACT

PURPOSE: To review the currently available literature on clinical autonomic tests of sudomotor function. METHODS: We searched PubMED/MEDLINE for articles on technical principles and clinical applications of sudomotor tests with a focus on their drawbacks and perspectives in order to provide a narrative review. RESULTS: The quantitative sudomotor axon reflex sweat test (QSART) is the most widely used test of sudomotor function. The technique captures pathology with low intra- and inter-subject variability but is limited by technical demands. The thermoregulatory sweat test comprises topographic sweat pattern analysis of the ventral skin surface and allows differentiating preganglionic from postganglionic sudomotor damage when combined with a small fiber test such as QSART. The sympathetic skin response also belongs to the more established techniques and is used in lie detection systems due to its high sensitivity for sudomotor responses to emotional stimuli. However, its clinical utility is limited by high variability of measurements, both within and between subjects. Newer and, therefore, less widely established techniques include silicone impressions, quantitative direct and indirect axon reflex testing, sensitive sweat test, and measurement of electrochemical skin conductance. The spoon test does not allow a quantitative assessment of the sweat response but can be used as bedside-screening tool of sudomotor dysfunction. CONCLUSION: While new autonomic sudomotor function testings have been developed and studied over the past decades, the most were well-studied and established techniques QSART and TST remain the gold standard of sudomotor assessment. Combining these techniques allows for sophisticated analysis of neurally mediated sudomotor impairment. However, newer techniques display potential to complement gold standard techniques to further improve their precision and diagnostic value. More... »

PAGES

1-13

Journal

TITLE

Clinical Autonomic Research

ISSUE

N/A

VOLUME

N/A

Author Affiliations

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/s10286-018-0530-2

DOI

http://dx.doi.org/10.1007/s10286-018-0530-2

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1103859285

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/29737432


Indexing Status Check whether this publication has been indexed by Scopus and Web Of Science using the SN Indexing Status Tool
Incoming Citations Browse incoming citations for this publication using opencitations.net

JSON-LD is the canonical representation for SciGraph data.

TIP: You can open this SciGraph record using an external JSON-LD service: JSON-LD Playground Google SDTT

[
  {
    "@context": "https://springernature.github.io/scigraph/jsonld/sgcontext.json", 
    "about": [
      {
        "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/1109", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Neurosciences", 
        "type": "DefinedTerm"
      }, 
      {
        "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/11", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Medical and Health Sciences", 
        "type": "DefinedTerm"
      }
    ], 
    "author": [
      {
        "affiliation": {
          "alternateName": "Charit\u00e9", 
          "id": "https://www.grid.ac/institutes/grid.6363.0", 
          "name": [
            "Department of Neurology, Campus Virchow, Charite University Medicine Berlin, Berlin, Germany"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Buchmann", 
        "givenName": "Sylvia J.", 
        "id": "sg:person.014427231077.89", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.014427231077.89"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "name": [
            "Department of Neurology, Bavaria Hospital Kreischa, Kreischa, Germany"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Penzlin", 
        "givenName": "Ana Isabel", 
        "id": "sg:person.01350561257.80", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01350561257.80"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "name": [
            "Department of Neurology, University Hospital Carl Gustav Carus, Technische Universit\u00e4t Dresden, Fetscherstr. 74, 01307, Dresden, Germany"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Kubasch", 
        "givenName": "Marie Luise", 
        "id": "sg:person.011605633621.21", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.011605633621.21"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "name": [
            "Department of Neurology, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, USA"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Illigens", 
        "givenName": "Ben Min-Woo", 
        "id": "sg:person.01026454617.20", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01026454617.20"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "name": [
            "Department of Neurology, University Hospital Carl Gustav Carus, Technische Universit\u00e4t Dresden, Fetscherstr. 74, 01307, Dresden, Germany"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Siepmann", 
        "givenName": "Timo", 
        "id": "sg:person.0614323317.53", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0614323317.53"
        ], 
        "type": "Person"
      }
    ], 
    "citation": [
      {
        "id": "https://doi.org/10.3988/jcn.2013.9.1.1", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1002033249"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s10286-003-0107-5", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1003324771", 
          "https://doi.org/10.1007/s10286-003-0107-5"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/s0190-9622(89)70063-3", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1004463041"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s10286-008-0506-8", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1005117150", 
          "https://doi.org/10.1007/s10286-008-0506-8"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s10286-008-0506-8", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1005117150", 
          "https://doi.org/10.1007/s10286-008-0506-8"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.physbeh.2012.01.020", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1007090680"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.4103/0972-2327.112479", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1008547791"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1136/jnnp.48.4.378", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1012680132"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1161/01.cir.90.2.779", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1014042323"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s00115-014-4120-9", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1014072704", 
          "https://doi.org/10.1007/s00115-014-4120-9"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1136/jnnp.47.5.536", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1016185618"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1002/ana.410140513", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1022938244"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.npep.2012.05.002", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1022960541"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1111/j.1469-8986.2007.00543.x", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1023851120"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1136/pgmj.23.262.353", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1024431756"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1136/pgmj.23.262.353", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1024431756"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/bf01049065", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1026072951", 
          "https://doi.org/10.1007/bf01049065"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/s0140-6736(05)74815-7", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1026208787"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s102860200003", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1027153354", 
          "https://doi.org/10.1007/s102860200003"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s00421-007-0646-x", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1027668268", 
          "https://doi.org/10.1007/s00421-007-0646-x"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.diabet.2010.05.004", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1029260059"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.clinph.2004.01.023", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1031985291"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1212/01.wnl.0000314646.49565.c0", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1032640976"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1212/01.wnl.0000314646.49565.c0", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1032640976"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.autneu.2010.05.005", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1033060667"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/b978-0-444-52902-2.00007-2", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1034323865"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/sc.1964.4", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1035011453", 
          "https://doi.org/10.1038/sc.1964.4"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/sc.1964.4", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1035011453", 
          "https://doi.org/10.1038/sc.1964.4"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.3389/fendo.2015.00094", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1035360959"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1002/mus.20551", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1040147024"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.2337/diabetes.50.2.436", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1042042773"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.ncl.2004.03.002", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1052189443"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.2741/3677", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1070915878"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s10286-017-0401-2", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1083755782", 
          "https://doi.org/10.1007/s10286-017-0401-2"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s10286-017-0401-2", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1083755782", 
          "https://doi.org/10.1007/s10286-017-0401-2"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1111/jns.12212", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1085202686"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.3389/fneur.2017.00212", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1085596018"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.5603/ait.2017.0042", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1091206087"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.3892/etm.2017.4689", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1091247535"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s10286-017-0467-x", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1091922779", 
          "https://doi.org/10.1007/s10286-017-0467-x"
        ], 
        "type": "CreativeWork"
      }
    ], 
    "datePublished": "2019-02", 
    "datePublishedReg": "2019-02-01", 
    "description": "PURPOSE: To review the currently available literature on clinical autonomic tests of sudomotor function.\nMETHODS: We searched PubMED/MEDLINE for articles on technical principles and clinical applications of sudomotor tests with a focus on their drawbacks and perspectives in order to provide a narrative review.\nRESULTS: The quantitative sudomotor axon reflex sweat test (QSART) is the most widely used test of sudomotor function. The technique captures pathology with low intra- and inter-subject variability but is limited by technical demands. The thermoregulatory sweat test comprises topographic sweat pattern analysis of the ventral skin surface and allows differentiating preganglionic from postganglionic sudomotor damage when combined with a small fiber test such as QSART. The sympathetic skin response also belongs to the more established techniques and is used in lie detection systems due to its high sensitivity for sudomotor responses to emotional stimuli. However, its clinical utility is limited by high variability of measurements, both within and between subjects. Newer and, therefore, less widely established techniques include silicone impressions, quantitative direct and indirect axon reflex testing, sensitive sweat test, and measurement of electrochemical skin conductance. The spoon test does not allow a quantitative assessment of the sweat response but can be used as bedside-screening tool of sudomotor dysfunction.\nCONCLUSION: While new autonomic sudomotor function testings have been developed and studied over the past decades, the most were well-studied and established techniques QSART and TST remain the gold standard of sudomotor assessment. Combining these techniques allows for sophisticated analysis of neurally mediated sudomotor impairment. However, newer techniques display potential to complement gold standard techniques to further improve their precision and diagnostic value.", 
    "genre": "research_article", 
    "id": "sg:pub.10.1007/s10286-018-0530-2", 
    "inLanguage": [
      "en"
    ], 
    "isAccessibleForFree": false, 
    "isPartOf": [
      {
        "id": "sg:journal.1101258", 
        "issn": [
          "0959-9851", 
          "1619-1560"
        ], 
        "name": "Clinical Autonomic Research", 
        "type": "Periodical"
      }
    ], 
    "name": "Assessment of sudomotor function", 
    "pagination": "1-13", 
    "productId": [
      {
        "name": "readcube_id", 
        "type": "PropertyValue", 
        "value": [
          "22643f8bab4fc56acdff0712a64d58873685994992837cdc939bc0ca0b66d40d"
        ]
      }, 
      {
        "name": "pubmed_id", 
        "type": "PropertyValue", 
        "value": [
          "29737432"
        ]
      }, 
      {
        "name": "nlm_unique_id", 
        "type": "PropertyValue", 
        "value": [
          "9106549"
        ]
      }, 
      {
        "name": "doi", 
        "type": "PropertyValue", 
        "value": [
          "10.1007/s10286-018-0530-2"
        ]
      }, 
      {
        "name": "dimensions_id", 
        "type": "PropertyValue", 
        "value": [
          "pub.1103859285"
        ]
      }
    ], 
    "sameAs": [
      "https://doi.org/10.1007/s10286-018-0530-2", 
      "https://app.dimensions.ai/details/publication/pub.1103859285"
    ], 
    "sdDataset": "articles", 
    "sdDatePublished": "2019-04-10T19:02", 
    "sdLicense": "https://scigraph.springernature.com/explorer/license/", 
    "sdPublisher": {
      "name": "Springer Nature - SN SciGraph project", 
      "type": "Organization"
    }, 
    "sdSource": "s3://com-uberresearch-data-dimensions-target-20181106-alternative/cleanup/v134/2549eaecd7973599484d7c17b260dba0a4ecb94b/merge/v9/a6c9fde33151104705d4d7ff012ea9563521a3ce/jats-lookup/v90/0000000001_0000000264/records_8678_00000485.jsonl", 
    "type": "ScholarlyArticle", 
    "url": "http://link.springer.com/10.1007/s10286-018-0530-2"
  }
]
 

Download the RDF metadata as:  json-ld nt turtle xml License info

HOW TO GET THIS DATA PROGRAMMATICALLY:

JSON-LD is a popular format for linked data which is fully compatible with JSON.

curl -H 'Accept: application/ld+json' 'https://scigraph.springernature.com/pub.10.1007/s10286-018-0530-2'

N-Triples is a line-based linked data format ideal for batch operations.

curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1007/s10286-018-0530-2'

Turtle is a human-readable linked data format.

curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1007/s10286-018-0530-2'

RDF/XML is a standard XML format for linked data.

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1007/s10286-018-0530-2'


 

This table displays all metadata directly associated to this object as RDF triples.

213 TRIPLES      21 PREDICATES      62 URIs      19 LITERALS      7 BLANK NODES

Subject Predicate Object
1 sg:pub.10.1007/s10286-018-0530-2 schema:about anzsrc-for:11
2 anzsrc-for:1109
3 schema:author N1dcba485db154abe85356f49785f2221
4 schema:citation sg:pub.10.1007/bf01049065
5 sg:pub.10.1007/s00115-014-4120-9
6 sg:pub.10.1007/s00421-007-0646-x
7 sg:pub.10.1007/s10286-003-0107-5
8 sg:pub.10.1007/s10286-008-0506-8
9 sg:pub.10.1007/s10286-017-0401-2
10 sg:pub.10.1007/s10286-017-0467-x
11 sg:pub.10.1007/s102860200003
12 sg:pub.10.1038/sc.1964.4
13 https://doi.org/10.1002/ana.410140513
14 https://doi.org/10.1002/mus.20551
15 https://doi.org/10.1016/b978-0-444-52902-2.00007-2
16 https://doi.org/10.1016/j.autneu.2010.05.005
17 https://doi.org/10.1016/j.clinph.2004.01.023
18 https://doi.org/10.1016/j.diabet.2010.05.004
19 https://doi.org/10.1016/j.ncl.2004.03.002
20 https://doi.org/10.1016/j.npep.2012.05.002
21 https://doi.org/10.1016/j.physbeh.2012.01.020
22 https://doi.org/10.1016/s0140-6736(05)74815-7
23 https://doi.org/10.1016/s0190-9622(89)70063-3
24 https://doi.org/10.1111/j.1469-8986.2007.00543.x
25 https://doi.org/10.1111/jns.12212
26 https://doi.org/10.1136/jnnp.47.5.536
27 https://doi.org/10.1136/jnnp.48.4.378
28 https://doi.org/10.1136/pgmj.23.262.353
29 https://doi.org/10.1161/01.cir.90.2.779
30 https://doi.org/10.1212/01.wnl.0000314646.49565.c0
31 https://doi.org/10.2337/diabetes.50.2.436
32 https://doi.org/10.2741/3677
33 https://doi.org/10.3389/fendo.2015.00094
34 https://doi.org/10.3389/fneur.2017.00212
35 https://doi.org/10.3892/etm.2017.4689
36 https://doi.org/10.3988/jcn.2013.9.1.1
37 https://doi.org/10.4103/0972-2327.112479
38 https://doi.org/10.5603/ait.2017.0042
39 schema:datePublished 2019-02
40 schema:datePublishedReg 2019-02-01
41 schema:description PURPOSE: To review the currently available literature on clinical autonomic tests of sudomotor function. METHODS: We searched PubMED/MEDLINE for articles on technical principles and clinical applications of sudomotor tests with a focus on their drawbacks and perspectives in order to provide a narrative review. RESULTS: The quantitative sudomotor axon reflex sweat test (QSART) is the most widely used test of sudomotor function. The technique captures pathology with low intra- and inter-subject variability but is limited by technical demands. The thermoregulatory sweat test comprises topographic sweat pattern analysis of the ventral skin surface and allows differentiating preganglionic from postganglionic sudomotor damage when combined with a small fiber test such as QSART. The sympathetic skin response also belongs to the more established techniques and is used in lie detection systems due to its high sensitivity for sudomotor responses to emotional stimuli. However, its clinical utility is limited by high variability of measurements, both within and between subjects. Newer and, therefore, less widely established techniques include silicone impressions, quantitative direct and indirect axon reflex testing, sensitive sweat test, and measurement of electrochemical skin conductance. The spoon test does not allow a quantitative assessment of the sweat response but can be used as bedside-screening tool of sudomotor dysfunction. CONCLUSION: While new autonomic sudomotor function testings have been developed and studied over the past decades, the most were well-studied and established techniques QSART and TST remain the gold standard of sudomotor assessment. Combining these techniques allows for sophisticated analysis of neurally mediated sudomotor impairment. However, newer techniques display potential to complement gold standard techniques to further improve their precision and diagnostic value.
42 schema:genre research_article
43 schema:inLanguage en
44 schema:isAccessibleForFree false
45 schema:isPartOf sg:journal.1101258
46 schema:name Assessment of sudomotor function
47 schema:pagination 1-13
48 schema:productId N5bfc7a8e4bec492385cfbff731e3bbb7
49 Na93c7795cfac44a7a9dae04dae763bea
50 Nac5b5a7f22ff46f5b1a7354affb17732
51 Nf55961fdb6ac4b0f92f43588f199fcec
52 Nfc88d2bb84b14645a377e9d55de38a8f
53 schema:sameAs https://app.dimensions.ai/details/publication/pub.1103859285
54 https://doi.org/10.1007/s10286-018-0530-2
55 schema:sdDatePublished 2019-04-10T19:02
56 schema:sdLicense https://scigraph.springernature.com/explorer/license/
57 schema:sdPublisher N7501a2bc350e4d6eb383fb922897f167
58 schema:url http://link.springer.com/10.1007/s10286-018-0530-2
59 sgo:license sg:explorer/license/
60 sgo:sdDataset articles
61 rdf:type schema:ScholarlyArticle
62 N0fa70d7b4b6d429ba0db18073362cbe2 rdf:first sg:person.0614323317.53
63 rdf:rest rdf:nil
64 N1dcba485db154abe85356f49785f2221 rdf:first sg:person.014427231077.89
65 rdf:rest N2cd6aa609b8041e784ac3c353abcb3ef
66 N21baef958d53438ba147a644d1fbba0e rdf:first sg:person.01026454617.20
67 rdf:rest N0fa70d7b4b6d429ba0db18073362cbe2
68 N2cd6aa609b8041e784ac3c353abcb3ef rdf:first sg:person.01350561257.80
69 rdf:rest Nd16ce2837f954880af27ef80536c93f0
70 N301502e089494552ab009906839675b2 schema:name Department of Neurology, Bavaria Hospital Kreischa, Kreischa, Germany
71 rdf:type schema:Organization
72 N5bfc7a8e4bec492385cfbff731e3bbb7 schema:name nlm_unique_id
73 schema:value 9106549
74 rdf:type schema:PropertyValue
75 N7501a2bc350e4d6eb383fb922897f167 schema:name Springer Nature - SN SciGraph project
76 rdf:type schema:Organization
77 Na93c7795cfac44a7a9dae04dae763bea schema:name doi
78 schema:value 10.1007/s10286-018-0530-2
79 rdf:type schema:PropertyValue
80 Nac5b5a7f22ff46f5b1a7354affb17732 schema:name readcube_id
81 schema:value 22643f8bab4fc56acdff0712a64d58873685994992837cdc939bc0ca0b66d40d
82 rdf:type schema:PropertyValue
83 Nc8224400beef46b69c0d1b331c660f89 schema:name Department of Neurology, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, USA
84 rdf:type schema:Organization
85 Nc98778ee72e5425aba41f187c6c23d95 schema:name Department of Neurology, University Hospital Carl Gustav Carus, Technische Universität Dresden, Fetscherstr. 74, 01307, Dresden, Germany
86 rdf:type schema:Organization
87 Nd16ce2837f954880af27ef80536c93f0 rdf:first sg:person.011605633621.21
88 rdf:rest N21baef958d53438ba147a644d1fbba0e
89 Nd788d09253fe4ec393b3198ead2a3b14 schema:name Department of Neurology, University Hospital Carl Gustav Carus, Technische Universität Dresden, Fetscherstr. 74, 01307, Dresden, Germany
90 rdf:type schema:Organization
91 Nf55961fdb6ac4b0f92f43588f199fcec schema:name dimensions_id
92 schema:value pub.1103859285
93 rdf:type schema:PropertyValue
94 Nfc88d2bb84b14645a377e9d55de38a8f schema:name pubmed_id
95 schema:value 29737432
96 rdf:type schema:PropertyValue
97 anzsrc-for:11 schema:inDefinedTermSet anzsrc-for:
98 schema:name Medical and Health Sciences
99 rdf:type schema:DefinedTerm
100 anzsrc-for:1109 schema:inDefinedTermSet anzsrc-for:
101 schema:name Neurosciences
102 rdf:type schema:DefinedTerm
103 sg:journal.1101258 schema:issn 0959-9851
104 1619-1560
105 schema:name Clinical Autonomic Research
106 rdf:type schema:Periodical
107 sg:person.01026454617.20 schema:affiliation Nc8224400beef46b69c0d1b331c660f89
108 schema:familyName Illigens
109 schema:givenName Ben Min-Woo
110 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01026454617.20
111 rdf:type schema:Person
112 sg:person.011605633621.21 schema:affiliation Nc98778ee72e5425aba41f187c6c23d95
113 schema:familyName Kubasch
114 schema:givenName Marie Luise
115 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.011605633621.21
116 rdf:type schema:Person
117 sg:person.01350561257.80 schema:affiliation N301502e089494552ab009906839675b2
118 schema:familyName Penzlin
119 schema:givenName Ana Isabel
120 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01350561257.80
121 rdf:type schema:Person
122 sg:person.014427231077.89 schema:affiliation https://www.grid.ac/institutes/grid.6363.0
123 schema:familyName Buchmann
124 schema:givenName Sylvia J.
125 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.014427231077.89
126 rdf:type schema:Person
127 sg:person.0614323317.53 schema:affiliation Nd788d09253fe4ec393b3198ead2a3b14
128 schema:familyName Siepmann
129 schema:givenName Timo
130 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0614323317.53
131 rdf:type schema:Person
132 sg:pub.10.1007/bf01049065 schema:sameAs https://app.dimensions.ai/details/publication/pub.1026072951
133 https://doi.org/10.1007/bf01049065
134 rdf:type schema:CreativeWork
135 sg:pub.10.1007/s00115-014-4120-9 schema:sameAs https://app.dimensions.ai/details/publication/pub.1014072704
136 https://doi.org/10.1007/s00115-014-4120-9
137 rdf:type schema:CreativeWork
138 sg:pub.10.1007/s00421-007-0646-x schema:sameAs https://app.dimensions.ai/details/publication/pub.1027668268
139 https://doi.org/10.1007/s00421-007-0646-x
140 rdf:type schema:CreativeWork
141 sg:pub.10.1007/s10286-003-0107-5 schema:sameAs https://app.dimensions.ai/details/publication/pub.1003324771
142 https://doi.org/10.1007/s10286-003-0107-5
143 rdf:type schema:CreativeWork
144 sg:pub.10.1007/s10286-008-0506-8 schema:sameAs https://app.dimensions.ai/details/publication/pub.1005117150
145 https://doi.org/10.1007/s10286-008-0506-8
146 rdf:type schema:CreativeWork
147 sg:pub.10.1007/s10286-017-0401-2 schema:sameAs https://app.dimensions.ai/details/publication/pub.1083755782
148 https://doi.org/10.1007/s10286-017-0401-2
149 rdf:type schema:CreativeWork
150 sg:pub.10.1007/s10286-017-0467-x schema:sameAs https://app.dimensions.ai/details/publication/pub.1091922779
151 https://doi.org/10.1007/s10286-017-0467-x
152 rdf:type schema:CreativeWork
153 sg:pub.10.1007/s102860200003 schema:sameAs https://app.dimensions.ai/details/publication/pub.1027153354
154 https://doi.org/10.1007/s102860200003
155 rdf:type schema:CreativeWork
156 sg:pub.10.1038/sc.1964.4 schema:sameAs https://app.dimensions.ai/details/publication/pub.1035011453
157 https://doi.org/10.1038/sc.1964.4
158 rdf:type schema:CreativeWork
159 https://doi.org/10.1002/ana.410140513 schema:sameAs https://app.dimensions.ai/details/publication/pub.1022938244
160 rdf:type schema:CreativeWork
161 https://doi.org/10.1002/mus.20551 schema:sameAs https://app.dimensions.ai/details/publication/pub.1040147024
162 rdf:type schema:CreativeWork
163 https://doi.org/10.1016/b978-0-444-52902-2.00007-2 schema:sameAs https://app.dimensions.ai/details/publication/pub.1034323865
164 rdf:type schema:CreativeWork
165 https://doi.org/10.1016/j.autneu.2010.05.005 schema:sameAs https://app.dimensions.ai/details/publication/pub.1033060667
166 rdf:type schema:CreativeWork
167 https://doi.org/10.1016/j.clinph.2004.01.023 schema:sameAs https://app.dimensions.ai/details/publication/pub.1031985291
168 rdf:type schema:CreativeWork
169 https://doi.org/10.1016/j.diabet.2010.05.004 schema:sameAs https://app.dimensions.ai/details/publication/pub.1029260059
170 rdf:type schema:CreativeWork
171 https://doi.org/10.1016/j.ncl.2004.03.002 schema:sameAs https://app.dimensions.ai/details/publication/pub.1052189443
172 rdf:type schema:CreativeWork
173 https://doi.org/10.1016/j.npep.2012.05.002 schema:sameAs https://app.dimensions.ai/details/publication/pub.1022960541
174 rdf:type schema:CreativeWork
175 https://doi.org/10.1016/j.physbeh.2012.01.020 schema:sameAs https://app.dimensions.ai/details/publication/pub.1007090680
176 rdf:type schema:CreativeWork
177 https://doi.org/10.1016/s0140-6736(05)74815-7 schema:sameAs https://app.dimensions.ai/details/publication/pub.1026208787
178 rdf:type schema:CreativeWork
179 https://doi.org/10.1016/s0190-9622(89)70063-3 schema:sameAs https://app.dimensions.ai/details/publication/pub.1004463041
180 rdf:type schema:CreativeWork
181 https://doi.org/10.1111/j.1469-8986.2007.00543.x schema:sameAs https://app.dimensions.ai/details/publication/pub.1023851120
182 rdf:type schema:CreativeWork
183 https://doi.org/10.1111/jns.12212 schema:sameAs https://app.dimensions.ai/details/publication/pub.1085202686
184 rdf:type schema:CreativeWork
185 https://doi.org/10.1136/jnnp.47.5.536 schema:sameAs https://app.dimensions.ai/details/publication/pub.1016185618
186 rdf:type schema:CreativeWork
187 https://doi.org/10.1136/jnnp.48.4.378 schema:sameAs https://app.dimensions.ai/details/publication/pub.1012680132
188 rdf:type schema:CreativeWork
189 https://doi.org/10.1136/pgmj.23.262.353 schema:sameAs https://app.dimensions.ai/details/publication/pub.1024431756
190 rdf:type schema:CreativeWork
191 https://doi.org/10.1161/01.cir.90.2.779 schema:sameAs https://app.dimensions.ai/details/publication/pub.1014042323
192 rdf:type schema:CreativeWork
193 https://doi.org/10.1212/01.wnl.0000314646.49565.c0 schema:sameAs https://app.dimensions.ai/details/publication/pub.1032640976
194 rdf:type schema:CreativeWork
195 https://doi.org/10.2337/diabetes.50.2.436 schema:sameAs https://app.dimensions.ai/details/publication/pub.1042042773
196 rdf:type schema:CreativeWork
197 https://doi.org/10.2741/3677 schema:sameAs https://app.dimensions.ai/details/publication/pub.1070915878
198 rdf:type schema:CreativeWork
199 https://doi.org/10.3389/fendo.2015.00094 schema:sameAs https://app.dimensions.ai/details/publication/pub.1035360959
200 rdf:type schema:CreativeWork
201 https://doi.org/10.3389/fneur.2017.00212 schema:sameAs https://app.dimensions.ai/details/publication/pub.1085596018
202 rdf:type schema:CreativeWork
203 https://doi.org/10.3892/etm.2017.4689 schema:sameAs https://app.dimensions.ai/details/publication/pub.1091247535
204 rdf:type schema:CreativeWork
205 https://doi.org/10.3988/jcn.2013.9.1.1 schema:sameAs https://app.dimensions.ai/details/publication/pub.1002033249
206 rdf:type schema:CreativeWork
207 https://doi.org/10.4103/0972-2327.112479 schema:sameAs https://app.dimensions.ai/details/publication/pub.1008547791
208 rdf:type schema:CreativeWork
209 https://doi.org/10.5603/ait.2017.0042 schema:sameAs https://app.dimensions.ai/details/publication/pub.1091206087
210 rdf:type schema:CreativeWork
211 https://www.grid.ac/institutes/grid.6363.0 schema:alternateName Charité
212 schema:name Department of Neurology, Campus Virchow, Charite University Medicine Berlin, Berlin, Germany
213 rdf:type schema:Organization
 




Preview window. Press ESC to close (or click here)


...