Vasospasm following aneurysmal subarachnoid hemorrhage: prediction, detection, and intervention View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2019-12

AUTHORS

Hassan Gamal Eldeen Nassar, Azza Abbas Ghali, Wafik Said Bahnasy, Mostafa Mohamed Elawady

ABSTRACT

Background: Vasospasm of the cerebral blood vessels is a common complication of aneurysmal subarachnoid hemorrhage (aSAH) which results in delayed cerebral ischemia (DCI) and worsening of the outcome. Methods: This study was performed on 41 aSAH patients diagnosed by non-contrast brain CT, CT angiography, and digital subtraction angiography followed by interventional aneurysmal embolization. Patients were followed up for 20 days by clinical assessment, EEG monitoring, and transcranial duplex studies (TCD) for early detection of vasospasm and DCI. Results: The most common ruptured aneurysmal sites were middle cerebral, anterior communicating, posterior communicating, terminal internal carotid, and anterior cerebral arteries respectively. The incidence of vasospasm was 36.8% of the included cases; 57% progressed to DCI while 43% passed a spontaneous regressive course. The most common arteries undergoing vasospasm were the MCA followed by the ACA, ICA, and lastly the basilar arteries. The mean time of vasospasm development as detected by EEG monitoring and/or TCD was 8.4 ± 2.8 days which was earlier than clinical signs by 12.5 ± 5.3 h in those progressed to DCI. Conclusion: Continuous EEG monitoring and TCD are valuable methods for early detection of vasospasm and they allow for early therapeutic intervention before irreversible ischemic neurological deficits take place. More... »

PAGES

3

Identifiers

URI

http://scigraph.springernature.com/pub.10.1186/s41983-018-0050-y

DOI

http://dx.doi.org/10.1186/s41983-018-0050-y

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1111268122

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/30686913


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/2008/1103", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Clinical Sciences", 
        "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": "Tanta University", 
          "id": "https://www.grid.ac/institutes/grid.412258.8", 
          "name": [
            "Department of Neuropsychiatry, Faculty of Medicine, Tanta University, 31527, Tanta, Egypt"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Nassar", 
        "givenName": "Hassan Gamal Eldeen", 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Tanta University", 
          "id": "https://www.grid.ac/institutes/grid.412258.8", 
          "name": [
            "Department of Neuropsychiatry, Faculty of Medicine, Tanta University, 31527, Tanta, Egypt"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Ghali", 
        "givenName": "Azza Abbas", 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Tanta University", 
          "id": "https://www.grid.ac/institutes/grid.412258.8", 
          "name": [
            "Department of Neuropsychiatry, Faculty of Medicine, Tanta University, 31527, Tanta, Egypt"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Bahnasy", 
        "givenName": "Wafik Said", 
        "id": "sg:person.011334507233.46", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.011334507233.46"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Tanta University", 
          "id": "https://www.grid.ac/institutes/grid.412258.8", 
          "name": [
            "Department of Neuropsychiatry, Faculty of Medicine, Tanta University, 31527, Tanta, Egypt"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Elawady", 
        "givenName": "Mostafa Mohamed", 
        "type": "Person"
      }
    ], 
    "citation": [
      {
        "id": "https://doi.org/10.1016/j.jstrokecerebrovasdis.2011.05.024", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1000001246"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.wneu.2016.10.064", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1002787484"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.wneu.2016.09.096", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1018203727"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1212/wnl.62.9.1468", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1020052921"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1212/wnl.62.9.1468", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1020052921"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.jcrc.2016.09.011", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1033743284"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1136/neurintsurg-2014-011403", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1036821716"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1136/neurintsurg-2014-011403", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1036821716"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.jstrokecerebrovasdis.2013.01.006", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1037557398"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1161/strokeaha.116.012957", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1038144139"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1161/strokeaha.116.012957", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1038144139"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/nrneurol.2013.246", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1039617511", 
          "https://doi.org/10.1038/nrneurol.2013.246"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.clinph.2014.10.215", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1040297252"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.nec.2009.10.002", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1042138867"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s10143-016-0701-3", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1045204770", 
          "https://doi.org/10.1007/s10143-016-0701-3"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.jstrokecerebrovasdis.2012.08.004", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1045371294"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.jstrokecerebrovasdis.2016.05.032", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1047022375"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1136/jnnp.2008.163063", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1048335752"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1212/01.con.0000415429.99394.e8", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1064344016"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1212/01.con.0000415429.99394.e8", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1064344016"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1212/01.con.0000415429.99394.e8", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1064344016"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.jocn.2017.02.001", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1084090373"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.wneu.2017.03.057", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1084112942"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.wneu.2017.07.114", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1090916432"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.wneu.2017.09.179", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1092130681"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.wneu.2017.10.089", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1092349097"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.wneu.2017.10.089", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1092349097"
        ], 
        "type": "CreativeWork"
      }
    ], 
    "datePublished": "2019-12", 
    "datePublishedReg": "2019-12-01", 
    "description": "Background: Vasospasm of the cerebral blood vessels is a common complication of aneurysmal subarachnoid hemorrhage (aSAH) which results in delayed cerebral ischemia (DCI) and worsening of the outcome.\nMethods: This study was performed on 41 aSAH patients diagnosed by non-contrast brain CT, CT angiography, and digital subtraction angiography followed by interventional aneurysmal embolization. Patients were followed up for 20\u00a0days by clinical assessment, EEG monitoring, and transcranial duplex studies (TCD) for early detection of vasospasm and DCI.\nResults: The most common ruptured aneurysmal sites were middle cerebral, anterior communicating, posterior communicating, terminal internal carotid, and anterior cerebral arteries respectively. The incidence of vasospasm was 36.8% of the included cases; 57% progressed to DCI while 43% passed a spontaneous regressive course. The most common arteries undergoing vasospasm were the MCA followed by the ACA, ICA, and lastly the basilar arteries. The mean time of vasospasm development as detected by EEG monitoring and/or TCD was 8.4\u2009\u00b1\u20092.8\u00a0days which was earlier than clinical signs by 12.5\u2009\u00b1\u20095.3\u00a0h in those progressed to DCI.\nConclusion: Continuous EEG monitoring and TCD are valuable methods for early detection of vasospasm and they allow for early therapeutic intervention before irreversible ischemic neurological deficits take place.", 
    "genre": "research_article", 
    "id": "sg:pub.10.1186/s41983-018-0050-y", 
    "inLanguage": [
      "en"
    ], 
    "isAccessibleForFree": false, 
    "isPartOf": [
      {
        "id": "sg:journal.1005612", 
        "issn": [
          "1110-1083", 
          "1687-8329"
        ], 
        "name": "The Egyptian Journal of Neurology, Psychiatry and Neurosurgery", 
        "type": "Periodical"
      }, 
      {
        "issueNumber": "1", 
        "type": "PublicationIssue"
      }, 
      {
        "type": "PublicationVolume", 
        "volumeNumber": "55"
      }
    ], 
    "name": "Vasospasm following aneurysmal subarachnoid hemorrhage: prediction, detection, and intervention", 
    "pagination": "3", 
    "productId": [
      {
        "name": "readcube_id", 
        "type": "PropertyValue", 
        "value": [
          "d83b4edb876c9c2cfc4d3df7d9324510368645c1c14fbe3c8306e5421dbcb832"
        ]
      }, 
      {
        "name": "pubmed_id", 
        "type": "PropertyValue", 
        "value": [
          "30686913"
        ]
      }, 
      {
        "name": "nlm_unique_id", 
        "type": "PropertyValue", 
        "value": [
          "0043617"
        ]
      }, 
      {
        "name": "doi", 
        "type": "PropertyValue", 
        "value": [
          "10.1186/s41983-018-0050-y"
        ]
      }, 
      {
        "name": "dimensions_id", 
        "type": "PropertyValue", 
        "value": [
          "pub.1111268122"
        ]
      }
    ], 
    "sameAs": [
      "https://doi.org/10.1186/s41983-018-0050-y", 
      "https://app.dimensions.ai/details/publication/pub.1111268122"
    ], 
    "sdDataset": "articles", 
    "sdDatePublished": "2019-04-11T08:57", 
    "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/v90/0000000325_0000000325/records_100819_00000000.jsonl", 
    "type": "ScholarlyArticle", 
    "url": "https://link.springer.com/10.1186%2Fs41983-018-0050-y"
  }
]
 

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.10.1186/s41983-018-0050-y'

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

curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1186/s41983-018-0050-y'

Turtle is a human-readable linked data format.

curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1186/s41983-018-0050-y'

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

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1186/s41983-018-0050-y'


 

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

152 TRIPLES      21 PREDICATES      50 URIs      21 LITERALS      9 BLANK NODES

Subject Predicate Object
1 sg:pub.10.1186/s41983-018-0050-y schema:about anzsrc-for:11
2 anzsrc-for:1103
3 schema:author N24202fc9f625499eb1e9c7da97b6c9bf
4 schema:citation sg:pub.10.1007/s10143-016-0701-3
5 sg:pub.10.1038/nrneurol.2013.246
6 https://doi.org/10.1016/j.clinph.2014.10.215
7 https://doi.org/10.1016/j.jcrc.2016.09.011
8 https://doi.org/10.1016/j.jocn.2017.02.001
9 https://doi.org/10.1016/j.jstrokecerebrovasdis.2011.05.024
10 https://doi.org/10.1016/j.jstrokecerebrovasdis.2012.08.004
11 https://doi.org/10.1016/j.jstrokecerebrovasdis.2013.01.006
12 https://doi.org/10.1016/j.jstrokecerebrovasdis.2016.05.032
13 https://doi.org/10.1016/j.nec.2009.10.002
14 https://doi.org/10.1016/j.wneu.2016.09.096
15 https://doi.org/10.1016/j.wneu.2016.10.064
16 https://doi.org/10.1016/j.wneu.2017.03.057
17 https://doi.org/10.1016/j.wneu.2017.07.114
18 https://doi.org/10.1016/j.wneu.2017.09.179
19 https://doi.org/10.1016/j.wneu.2017.10.089
20 https://doi.org/10.1136/jnnp.2008.163063
21 https://doi.org/10.1136/neurintsurg-2014-011403
22 https://doi.org/10.1161/strokeaha.116.012957
23 https://doi.org/10.1212/01.con.0000415429.99394.e8
24 https://doi.org/10.1212/wnl.62.9.1468
25 schema:datePublished 2019-12
26 schema:datePublishedReg 2019-12-01
27 schema:description Background: Vasospasm of the cerebral blood vessels is a common complication of aneurysmal subarachnoid hemorrhage (aSAH) which results in delayed cerebral ischemia (DCI) and worsening of the outcome. Methods: This study was performed on 41 aSAH patients diagnosed by non-contrast brain CT, CT angiography, and digital subtraction angiography followed by interventional aneurysmal embolization. Patients were followed up for 20 days by clinical assessment, EEG monitoring, and transcranial duplex studies (TCD) for early detection of vasospasm and DCI. Results: The most common ruptured aneurysmal sites were middle cerebral, anterior communicating, posterior communicating, terminal internal carotid, and anterior cerebral arteries respectively. The incidence of vasospasm was 36.8% of the included cases; 57% progressed to DCI while 43% passed a spontaneous regressive course. The most common arteries undergoing vasospasm were the MCA followed by the ACA, ICA, and lastly the basilar arteries. The mean time of vasospasm development as detected by EEG monitoring and/or TCD was 8.4 ± 2.8 days which was earlier than clinical signs by 12.5 ± 5.3 h in those progressed to DCI. Conclusion: Continuous EEG monitoring and TCD are valuable methods for early detection of vasospasm and they allow for early therapeutic intervention before irreversible ischemic neurological deficits take place.
28 schema:genre research_article
29 schema:inLanguage en
30 schema:isAccessibleForFree false
31 schema:isPartOf N91bd00d70a654bdca79eae76508f8527
32 N920ba2c6b383479bb389901c6b017bc7
33 sg:journal.1005612
34 schema:name Vasospasm following aneurysmal subarachnoid hemorrhage: prediction, detection, and intervention
35 schema:pagination 3
36 schema:productId N32df79b230eb4703b6dff9c83c86b88a
37 N6618cbfa0d444e00bf39eb45a3a709c5
38 N78f88f4efd2d49d0b81b873b47cdddac
39 Nd4e6fc99e9a34218bca006645d43870b
40 Ndb46d6f1fc69404ca8e3735036e8fe86
41 schema:sameAs https://app.dimensions.ai/details/publication/pub.1111268122
42 https://doi.org/10.1186/s41983-018-0050-y
43 schema:sdDatePublished 2019-04-11T08:57
44 schema:sdLicense https://scigraph.springernature.com/explorer/license/
45 schema:sdPublisher N70d7f1a38f2c4995bb6122d0ae6e531f
46 schema:url https://link.springer.com/10.1186%2Fs41983-018-0050-y
47 sgo:license sg:explorer/license/
48 sgo:sdDataset articles
49 rdf:type schema:ScholarlyArticle
50 N094a7a4e2b1a434a8deca9fecbc0cf56 rdf:first sg:person.011334507233.46
51 rdf:rest N7799dd99bd404725bb69352720224942
52 N0b887de47abb45d9b2266d74ff9115c7 rdf:first N3b03fa0589474237844db87622bb4ce7
53 rdf:rest N094a7a4e2b1a434a8deca9fecbc0cf56
54 N24202fc9f625499eb1e9c7da97b6c9bf rdf:first N4ef8ce4ddf4846d49e47385754951e90
55 rdf:rest N0b887de47abb45d9b2266d74ff9115c7
56 N32df79b230eb4703b6dff9c83c86b88a schema:name nlm_unique_id
57 schema:value 0043617
58 rdf:type schema:PropertyValue
59 N35dba69b8ab1401186a36976c2ec6ab5 schema:affiliation https://www.grid.ac/institutes/grid.412258.8
60 schema:familyName Elawady
61 schema:givenName Mostafa Mohamed
62 rdf:type schema:Person
63 N3b03fa0589474237844db87622bb4ce7 schema:affiliation https://www.grid.ac/institutes/grid.412258.8
64 schema:familyName Ghali
65 schema:givenName Azza Abbas
66 rdf:type schema:Person
67 N4ef8ce4ddf4846d49e47385754951e90 schema:affiliation https://www.grid.ac/institutes/grid.412258.8
68 schema:familyName Nassar
69 schema:givenName Hassan Gamal Eldeen
70 rdf:type schema:Person
71 N6618cbfa0d444e00bf39eb45a3a709c5 schema:name doi
72 schema:value 10.1186/s41983-018-0050-y
73 rdf:type schema:PropertyValue
74 N70d7f1a38f2c4995bb6122d0ae6e531f schema:name Springer Nature - SN SciGraph project
75 rdf:type schema:Organization
76 N7799dd99bd404725bb69352720224942 rdf:first N35dba69b8ab1401186a36976c2ec6ab5
77 rdf:rest rdf:nil
78 N78f88f4efd2d49d0b81b873b47cdddac schema:name dimensions_id
79 schema:value pub.1111268122
80 rdf:type schema:PropertyValue
81 N91bd00d70a654bdca79eae76508f8527 schema:volumeNumber 55
82 rdf:type schema:PublicationVolume
83 N920ba2c6b383479bb389901c6b017bc7 schema:issueNumber 1
84 rdf:type schema:PublicationIssue
85 Nd4e6fc99e9a34218bca006645d43870b schema:name readcube_id
86 schema:value d83b4edb876c9c2cfc4d3df7d9324510368645c1c14fbe3c8306e5421dbcb832
87 rdf:type schema:PropertyValue
88 Ndb46d6f1fc69404ca8e3735036e8fe86 schema:name pubmed_id
89 schema:value 30686913
90 rdf:type schema:PropertyValue
91 anzsrc-for:11 schema:inDefinedTermSet anzsrc-for:
92 schema:name Medical and Health Sciences
93 rdf:type schema:DefinedTerm
94 anzsrc-for:1103 schema:inDefinedTermSet anzsrc-for:
95 schema:name Clinical Sciences
96 rdf:type schema:DefinedTerm
97 sg:journal.1005612 schema:issn 1110-1083
98 1687-8329
99 schema:name The Egyptian Journal of Neurology, Psychiatry and Neurosurgery
100 rdf:type schema:Periodical
101 sg:person.011334507233.46 schema:affiliation https://www.grid.ac/institutes/grid.412258.8
102 schema:familyName Bahnasy
103 schema:givenName Wafik Said
104 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.011334507233.46
105 rdf:type schema:Person
106 sg:pub.10.1007/s10143-016-0701-3 schema:sameAs https://app.dimensions.ai/details/publication/pub.1045204770
107 https://doi.org/10.1007/s10143-016-0701-3
108 rdf:type schema:CreativeWork
109 sg:pub.10.1038/nrneurol.2013.246 schema:sameAs https://app.dimensions.ai/details/publication/pub.1039617511
110 https://doi.org/10.1038/nrneurol.2013.246
111 rdf:type schema:CreativeWork
112 https://doi.org/10.1016/j.clinph.2014.10.215 schema:sameAs https://app.dimensions.ai/details/publication/pub.1040297252
113 rdf:type schema:CreativeWork
114 https://doi.org/10.1016/j.jcrc.2016.09.011 schema:sameAs https://app.dimensions.ai/details/publication/pub.1033743284
115 rdf:type schema:CreativeWork
116 https://doi.org/10.1016/j.jocn.2017.02.001 schema:sameAs https://app.dimensions.ai/details/publication/pub.1084090373
117 rdf:type schema:CreativeWork
118 https://doi.org/10.1016/j.jstrokecerebrovasdis.2011.05.024 schema:sameAs https://app.dimensions.ai/details/publication/pub.1000001246
119 rdf:type schema:CreativeWork
120 https://doi.org/10.1016/j.jstrokecerebrovasdis.2012.08.004 schema:sameAs https://app.dimensions.ai/details/publication/pub.1045371294
121 rdf:type schema:CreativeWork
122 https://doi.org/10.1016/j.jstrokecerebrovasdis.2013.01.006 schema:sameAs https://app.dimensions.ai/details/publication/pub.1037557398
123 rdf:type schema:CreativeWork
124 https://doi.org/10.1016/j.jstrokecerebrovasdis.2016.05.032 schema:sameAs https://app.dimensions.ai/details/publication/pub.1047022375
125 rdf:type schema:CreativeWork
126 https://doi.org/10.1016/j.nec.2009.10.002 schema:sameAs https://app.dimensions.ai/details/publication/pub.1042138867
127 rdf:type schema:CreativeWork
128 https://doi.org/10.1016/j.wneu.2016.09.096 schema:sameAs https://app.dimensions.ai/details/publication/pub.1018203727
129 rdf:type schema:CreativeWork
130 https://doi.org/10.1016/j.wneu.2016.10.064 schema:sameAs https://app.dimensions.ai/details/publication/pub.1002787484
131 rdf:type schema:CreativeWork
132 https://doi.org/10.1016/j.wneu.2017.03.057 schema:sameAs https://app.dimensions.ai/details/publication/pub.1084112942
133 rdf:type schema:CreativeWork
134 https://doi.org/10.1016/j.wneu.2017.07.114 schema:sameAs https://app.dimensions.ai/details/publication/pub.1090916432
135 rdf:type schema:CreativeWork
136 https://doi.org/10.1016/j.wneu.2017.09.179 schema:sameAs https://app.dimensions.ai/details/publication/pub.1092130681
137 rdf:type schema:CreativeWork
138 https://doi.org/10.1016/j.wneu.2017.10.089 schema:sameAs https://app.dimensions.ai/details/publication/pub.1092349097
139 rdf:type schema:CreativeWork
140 https://doi.org/10.1136/jnnp.2008.163063 schema:sameAs https://app.dimensions.ai/details/publication/pub.1048335752
141 rdf:type schema:CreativeWork
142 https://doi.org/10.1136/neurintsurg-2014-011403 schema:sameAs https://app.dimensions.ai/details/publication/pub.1036821716
143 rdf:type schema:CreativeWork
144 https://doi.org/10.1161/strokeaha.116.012957 schema:sameAs https://app.dimensions.ai/details/publication/pub.1038144139
145 rdf:type schema:CreativeWork
146 https://doi.org/10.1212/01.con.0000415429.99394.e8 schema:sameAs https://app.dimensions.ai/details/publication/pub.1064344016
147 rdf:type schema:CreativeWork
148 https://doi.org/10.1212/wnl.62.9.1468 schema:sameAs https://app.dimensions.ai/details/publication/pub.1020052921
149 rdf:type schema:CreativeWork
150 https://www.grid.ac/institutes/grid.412258.8 schema:alternateName Tanta University
151 schema:name Department of Neuropsychiatry, Faculty of Medicine, Tanta University, 31527, Tanta, Egypt
152 rdf:type schema:Organization
 




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


...