Noninvasive estimation of impaired left ventricular untwisting velocity by peak early diastolic intra-ventricular pressure gradients using vector flow mapping View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2021-03-07

AUTHORS

Yuki Nakajima, Takeshi Hozumi, Kazushi Takemoto, Suwako Fujita, Teruaki Wada, Manabu Kashiwagi, Kunihiro Shimamura, Yasutsugu Shiono, Akio Kuroi, Takashi Tanimoto, Takashi Kubo, Atsushi Tanaka, Takashi Akasaka

ABSTRACT

BackgroundIntroduction of vector flow mapping (VFM) based on the combination of color Doppler and speckle-tracking echocardiography provides noninvasive assessment of early diastolic intra-ventricular pressure gradient (ED-IVPG). The purpose of this study was to evaluate the value of peak ED-IVPG measurement just after aortic valve closure using VFM for noninvasive estimation of impaired LV untwisting velocity as the index of LV relaxation in the clinical setting.Methods and resultsThe study included 65 consecutive patients in whom echocardiography was performed for the assessment of LV function. We assessed peak ED-IVPG between LV apex and base by VFM analysis software. We also measured peak LV untwisting velocity and LV twisting by speckle-tracking strain analysis. Peak ED-IVPG was successfully and quickly assessed in all the study patients. Peak ED-IVPG was significantly reduced in patients with impaired peak LV untwisting velocity (< 70 degrees/s) compared with patients without impaired peak LV untwisting velocity. The receiver operating characteristic analysis showed the best cut-off value of peak ED-IVPG for determining impaired peak LV untwisting velocity was 0.40 mmHg (sensitivity 81%, specificity 74%, and area under the curve 0.81). There was a well correlation between peak ED-IVPG and peak LV untwisting velocity (r = 0.64, p < 0.0001).ConclusionsThe present results suggest that peak ED-IVPG just after aortic valve closure measured by VFM may be used as noninvasive index for estimation of impaired LV untwisting velocity in the clinical setting. More... »

PAGES

166-172

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/s12574-021-00520-1

DOI

http://dx.doi.org/10.1007/s12574-021-00520-1

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1136208185

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/33682077


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/2008/11", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Medical and Health Sciences", 
        "type": "DefinedTerm"
      }, 
      {
        "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/1102", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Cardiorespiratory Medicine and Haematology", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Aortic Valve", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Echocardiography", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Heart Ventricles", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Humans", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Ventricular Dysfunction, Left", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Ventricular Function, Left", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Ventricular Pressure", 
        "type": "DefinedTerm"
      }
    ], 
    "author": [
      {
        "affiliation": {
          "alternateName": "Department of Cardiovascular Medicine, Wakayama Medical University, 811-1 Kimiidera, 641-8509, Wakayama, Japan", 
          "id": "http://www.grid.ac/institutes/grid.412857.d", 
          "name": [
            "Department of Cardiovascular Medicine, Wakayama Medical University, 811-1 Kimiidera, 641-8509, Wakayama, Japan"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Nakajima", 
        "givenName": "Yuki", 
        "id": "sg:person.010772153323.77", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.010772153323.77"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Department of Cardiovascular Medicine, Wakayama Medical University, 811-1 Kimiidera, 641-8509, Wakayama, Japan", 
          "id": "http://www.grid.ac/institutes/grid.412857.d", 
          "name": [
            "Department of Cardiovascular Medicine, Wakayama Medical University, 811-1 Kimiidera, 641-8509, Wakayama, Japan"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Hozumi", 
        "givenName": "Takeshi", 
        "id": "sg:person.01364434455.38", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01364434455.38"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Department of Cardiovascular Medicine, Wakayama Medical University, 811-1 Kimiidera, 641-8509, Wakayama, Japan", 
          "id": "http://www.grid.ac/institutes/grid.412857.d", 
          "name": [
            "Department of Cardiovascular Medicine, Wakayama Medical University, 811-1 Kimiidera, 641-8509, Wakayama, Japan"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Takemoto", 
        "givenName": "Kazushi", 
        "id": "sg:person.01266125010.66", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01266125010.66"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Department of Cardiovascular Medicine, Wakayama Medical University, 811-1 Kimiidera, 641-8509, Wakayama, Japan", 
          "id": "http://www.grid.ac/institutes/grid.412857.d", 
          "name": [
            "Department of Cardiovascular Medicine, Wakayama Medical University, 811-1 Kimiidera, 641-8509, Wakayama, Japan"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Fujita", 
        "givenName": "Suwako", 
        "id": "sg:person.0715625754.71", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0715625754.71"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Department of Cardiovascular Medicine, Wakayama Medical University, 811-1 Kimiidera, 641-8509, Wakayama, Japan", 
          "id": "http://www.grid.ac/institutes/grid.412857.d", 
          "name": [
            "Department of Cardiovascular Medicine, Wakayama Medical University, 811-1 Kimiidera, 641-8509, Wakayama, Japan"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Wada", 
        "givenName": "Teruaki", 
        "id": "sg:person.0723621375.10", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0723621375.10"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Department of Cardiovascular Medicine, Wakayama Medical University, 811-1 Kimiidera, 641-8509, Wakayama, Japan", 
          "id": "http://www.grid.ac/institutes/grid.412857.d", 
          "name": [
            "Department of Cardiovascular Medicine, Wakayama Medical University, 811-1 Kimiidera, 641-8509, Wakayama, Japan"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Kashiwagi", 
        "givenName": "Manabu", 
        "id": "sg:person.01051432331.47", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01051432331.47"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Department of Cardiovascular Medicine, Wakayama Medical University, 811-1 Kimiidera, 641-8509, Wakayama, Japan", 
          "id": "http://www.grid.ac/institutes/grid.412857.d", 
          "name": [
            "Department of Cardiovascular Medicine, Wakayama Medical University, 811-1 Kimiidera, 641-8509, Wakayama, Japan"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Shimamura", 
        "givenName": "Kunihiro", 
        "id": "sg:person.01042334674.03", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01042334674.03"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Department of Cardiovascular Medicine, Wakayama Medical University, 811-1 Kimiidera, 641-8509, Wakayama, Japan", 
          "id": "http://www.grid.ac/institutes/grid.412857.d", 
          "name": [
            "Department of Cardiovascular Medicine, Wakayama Medical University, 811-1 Kimiidera, 641-8509, Wakayama, Japan"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Shiono", 
        "givenName": "Yasutsugu", 
        "id": "sg:person.0774221474.24", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0774221474.24"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Department of Cardiovascular Medicine, Wakayama Medical University, 811-1 Kimiidera, 641-8509, Wakayama, Japan", 
          "id": "http://www.grid.ac/institutes/grid.412857.d", 
          "name": [
            "Department of Cardiovascular Medicine, Wakayama Medical University, 811-1 Kimiidera, 641-8509, Wakayama, Japan"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Kuroi", 
        "givenName": "Akio", 
        "id": "sg:person.0710230113.99", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0710230113.99"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Department of Cardiovascular Medicine, Wakayama Medical University, 811-1 Kimiidera, 641-8509, Wakayama, Japan", 
          "id": "http://www.grid.ac/institutes/grid.412857.d", 
          "name": [
            "Department of Cardiovascular Medicine, Wakayama Medical University, 811-1 Kimiidera, 641-8509, Wakayama, Japan"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Tanimoto", 
        "givenName": "Takashi", 
        "id": "sg:person.0611657674.62", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0611657674.62"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Department of Cardiovascular Medicine, Wakayama Medical University, 811-1 Kimiidera, 641-8509, Wakayama, Japan", 
          "id": "http://www.grid.ac/institutes/grid.412857.d", 
          "name": [
            "Department of Cardiovascular Medicine, Wakayama Medical University, 811-1 Kimiidera, 641-8509, Wakayama, Japan"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Kubo", 
        "givenName": "Takashi", 
        "id": "sg:person.01347751771.77", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01347751771.77"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Department of Cardiovascular Medicine, Wakayama Medical University, 811-1 Kimiidera, 641-8509, Wakayama, Japan", 
          "id": "http://www.grid.ac/institutes/grid.412857.d", 
          "name": [
            "Department of Cardiovascular Medicine, Wakayama Medical University, 811-1 Kimiidera, 641-8509, Wakayama, Japan"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Tanaka", 
        "givenName": "Atsushi", 
        "id": "sg:person.0736227535.42", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0736227535.42"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Department of Cardiovascular Medicine, Wakayama Medical University, 811-1 Kimiidera, 641-8509, Wakayama, Japan", 
          "id": "http://www.grid.ac/institutes/grid.412857.d", 
          "name": [
            "Department of Cardiovascular Medicine, Wakayama Medical University, 811-1 Kimiidera, 641-8509, Wakayama, Japan"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Akasaka", 
        "givenName": "Takashi", 
        "id": "sg:person.0647415353.43", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0647415353.43"
        ], 
        "type": "Person"
      }
    ], 
    "citation": [
      {
        "id": "sg:pub.10.1007/bf03181570", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1000615577", 
          "https://doi.org/10.1007/bf03181570"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s12574-016-0321-5", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1035769505", 
          "https://doi.org/10.1007/s12574-016-0321-5"
        ], 
        "type": "CreativeWork"
      }
    ], 
    "datePublished": "2021-03-07", 
    "datePublishedReg": "2021-03-07", 
    "description": "BackgroundIntroduction of vector flow mapping (VFM) based on the combination of color Doppler and speckle-tracking echocardiography provides noninvasive assessment of early diastolic intra-ventricular pressure gradient (ED-IVPG). The purpose of this study was to evaluate the value of peak ED-IVPG measurement just after aortic valve closure using VFM for noninvasive estimation of impaired LV untwisting velocity as the index of LV relaxation in the clinical setting.Methods and resultsThe study included 65 consecutive patients in whom echocardiography was performed for the assessment of LV function. We assessed peak ED-IVPG between LV apex and base by VFM analysis software. We also measured peak LV untwisting velocity and LV twisting by speckle-tracking strain analysis. Peak ED-IVPG was successfully and quickly assessed in all the study patients. Peak ED-IVPG was significantly reduced in patients with impaired peak LV untwisting velocity (<\u200970 degrees/s) compared with patients without impaired peak LV untwisting velocity. The receiver operating characteristic analysis showed the best cut-off value of peak ED-IVPG for determining impaired peak LV untwisting velocity was 0.40\u00a0mmHg (sensitivity 81%, specificity 74%, and area under the curve 0.81). There was a well correlation between peak ED-IVPG and peak LV untwisting velocity (r\u2009=\u20090.64, p\u2009<\u20090.0001).ConclusionsThe present results suggest that peak ED-IVPG just after aortic valve closure measured by VFM may be used as noninvasive index for estimation of impaired LV untwisting velocity in the clinical setting.", 
    "genre": "article", 
    "id": "sg:pub.10.1007/s12574-021-00520-1", 
    "isAccessibleForFree": false, 
    "isPartOf": [
      {
        "id": "sg:journal.1036334", 
        "issn": [
          "1349-0222", 
          "1880-344X"
        ], 
        "name": "Journal of Echocardiography", 
        "publisher": "Springer Nature", 
        "type": "Periodical"
      }, 
      {
        "issueNumber": "3", 
        "type": "PublicationIssue"
      }, 
      {
        "type": "PublicationVolume", 
        "volumeNumber": "19"
      }
    ], 
    "keywords": [
      "vector flow mapping", 
      "peak LV", 
      "aortic valve closure", 
      "intra-ventricular pressure gradients", 
      "speckle-tracking strain analysis", 
      "clinical setting", 
      "speckle-tracking echocardiography", 
      "noninvasive estimation", 
      "flow mapping", 
      "ConclusionsThe present results", 
      "study patients", 
      "consecutive patients", 
      "LV relaxation", 
      "LV function", 
      "untwisting velocity", 
      "ResultsThe study", 
      "noninvasive index", 
      "LV apex", 
      "LV twisting", 
      "color Doppler", 
      "noninvasive assessment", 
      "valve closure", 
      "patients", 
      "LV", 
      "echocardiography", 
      "characteristic analysis", 
      "BackgroundIntroduction", 
      "mmHg", 
      "present results", 
      "setting", 
      "pressure gradient", 
      "closure", 
      "assessment", 
      "index", 
      "study", 
      "Doppler", 
      "strain analysis", 
      "apex", 
      "analysis software", 
      "correlation", 
      "analysis", 
      "combination", 
      "purpose", 
      "function", 
      "values", 
      "receiver", 
      "results", 
      "relaxation", 
      "method", 
      "velocity", 
      "measurements", 
      "base", 
      "mapping", 
      "gradient", 
      "well correlation", 
      "twisting", 
      "software", 
      "estimation"
    ], 
    "name": "Noninvasive estimation of impaired left ventricular untwisting velocity by peak early diastolic intra-ventricular pressure gradients using vector flow mapping", 
    "pagination": "166-172", 
    "productId": [
      {
        "name": "dimensions_id", 
        "type": "PropertyValue", 
        "value": [
          "pub.1136208185"
        ]
      }, 
      {
        "name": "doi", 
        "type": "PropertyValue", 
        "value": [
          "10.1007/s12574-021-00520-1"
        ]
      }, 
      {
        "name": "pubmed_id", 
        "type": "PropertyValue", 
        "value": [
          "33682077"
        ]
      }
    ], 
    "sameAs": [
      "https://doi.org/10.1007/s12574-021-00520-1", 
      "https://app.dimensions.ai/details/publication/pub.1136208185"
    ], 
    "sdDataset": "articles", 
    "sdDatePublished": "2022-09-02T16:07", 
    "sdLicense": "https://scigraph.springernature.com/explorer/license/", 
    "sdPublisher": {
      "name": "Springer Nature - SN SciGraph project", 
      "type": "Organization"
    }, 
    "sdSource": "s3://com-springernature-scigraph/baseset/20220902/entities/gbq_results/article/article_885.jsonl", 
    "type": "ScholarlyArticle", 
    "url": "https://doi.org/10.1007/s12574-021-00520-1"
  }
]
 

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/s12574-021-00520-1'

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/s12574-021-00520-1'

Turtle is a human-readable linked data format.

curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1007/s12574-021-00520-1'

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

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1007/s12574-021-00520-1'


 

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

239 TRIPLES      21 PREDICATES      92 URIs      82 LITERALS      14 BLANK NODES

Subject Predicate Object
1 sg:pub.10.1007/s12574-021-00520-1 schema:about N20c50eac94674dc89f5a6cedb2fb8db9
2 N2d9cfca92c654fceb5f5ecc6e20be10a
3 N4b96670592d1464e928df418cda3c957
4 Nda6b77e038d444da9eceed3d5b5eadb6
5 Ndc9af06e9f1948f29249ffbfb73f05e9
6 Ne736578fe7474f9fa95c2f88e94357cd
7 Nf1ea424e7a564c0abdfe63ef2498b76c
8 anzsrc-for:11
9 anzsrc-for:1102
10 schema:author Nfd8b4d1fa24b49cc8130ff7d985824cf
11 schema:citation sg:pub.10.1007/bf03181570
12 sg:pub.10.1007/s12574-016-0321-5
13 schema:datePublished 2021-03-07
14 schema:datePublishedReg 2021-03-07
15 schema:description BackgroundIntroduction of vector flow mapping (VFM) based on the combination of color Doppler and speckle-tracking echocardiography provides noninvasive assessment of early diastolic intra-ventricular pressure gradient (ED-IVPG). The purpose of this study was to evaluate the value of peak ED-IVPG measurement just after aortic valve closure using VFM for noninvasive estimation of impaired LV untwisting velocity as the index of LV relaxation in the clinical setting.Methods and resultsThe study included 65 consecutive patients in whom echocardiography was performed for the assessment of LV function. We assessed peak ED-IVPG between LV apex and base by VFM analysis software. We also measured peak LV untwisting velocity and LV twisting by speckle-tracking strain analysis. Peak ED-IVPG was successfully and quickly assessed in all the study patients. Peak ED-IVPG was significantly reduced in patients with impaired peak LV untwisting velocity (< 70 degrees/s) compared with patients without impaired peak LV untwisting velocity. The receiver operating characteristic analysis showed the best cut-off value of peak ED-IVPG for determining impaired peak LV untwisting velocity was 0.40 mmHg (sensitivity 81%, specificity 74%, and area under the curve 0.81). There was a well correlation between peak ED-IVPG and peak LV untwisting velocity (r = 0.64, p < 0.0001).ConclusionsThe present results suggest that peak ED-IVPG just after aortic valve closure measured by VFM may be used as noninvasive index for estimation of impaired LV untwisting velocity in the clinical setting.
16 schema:genre article
17 schema:isAccessibleForFree false
18 schema:isPartOf N0c85f8ec7f834cd0a448a034d9d6187a
19 Na5e5ce45739c468dbff94a231773d9ed
20 sg:journal.1036334
21 schema:keywords BackgroundIntroduction
22 ConclusionsThe present results
23 Doppler
24 LV
25 LV apex
26 LV function
27 LV relaxation
28 LV twisting
29 ResultsThe study
30 analysis
31 analysis software
32 aortic valve closure
33 apex
34 assessment
35 base
36 characteristic analysis
37 clinical setting
38 closure
39 color Doppler
40 combination
41 consecutive patients
42 correlation
43 echocardiography
44 estimation
45 flow mapping
46 function
47 gradient
48 index
49 intra-ventricular pressure gradients
50 mapping
51 measurements
52 method
53 mmHg
54 noninvasive assessment
55 noninvasive estimation
56 noninvasive index
57 patients
58 peak LV
59 present results
60 pressure gradient
61 purpose
62 receiver
63 relaxation
64 results
65 setting
66 software
67 speckle-tracking echocardiography
68 speckle-tracking strain analysis
69 strain analysis
70 study
71 study patients
72 twisting
73 untwisting velocity
74 values
75 valve closure
76 vector flow mapping
77 velocity
78 well correlation
79 schema:name Noninvasive estimation of impaired left ventricular untwisting velocity by peak early diastolic intra-ventricular pressure gradients using vector flow mapping
80 schema:pagination 166-172
81 schema:productId N351a0645d8054d2194194b81334c12a4
82 N8939725c60024506abd76e12c92da4cb
83 N8a2c38cce28a434aaa8483035a7a3dcf
84 schema:sameAs https://app.dimensions.ai/details/publication/pub.1136208185
85 https://doi.org/10.1007/s12574-021-00520-1
86 schema:sdDatePublished 2022-09-02T16:07
87 schema:sdLicense https://scigraph.springernature.com/explorer/license/
88 schema:sdPublisher Nb0d7ffb274b3434aaee0f5fd34e18738
89 schema:url https://doi.org/10.1007/s12574-021-00520-1
90 sgo:license sg:explorer/license/
91 sgo:sdDataset articles
92 rdf:type schema:ScholarlyArticle
93 N00bf6a5e89f34b44bbf80463b25d47e5 rdf:first sg:person.01051432331.47
94 rdf:rest Nc617476c7c45449e91daa6cc340cbba8
95 N0c85f8ec7f834cd0a448a034d9d6187a schema:volumeNumber 19
96 rdf:type schema:PublicationVolume
97 N11b2a9c5c40647e1a5fad320550f5aec rdf:first sg:person.0736227535.42
98 rdf:rest N3caa7eb9caf348439406fefe3787cd01
99 N20c50eac94674dc89f5a6cedb2fb8db9 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
100 schema:name Humans
101 rdf:type schema:DefinedTerm
102 N2d9cfca92c654fceb5f5ecc6e20be10a schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
103 schema:name Aortic Valve
104 rdf:type schema:DefinedTerm
105 N351a0645d8054d2194194b81334c12a4 schema:name pubmed_id
106 schema:value 33682077
107 rdf:type schema:PropertyValue
108 N3caa7eb9caf348439406fefe3787cd01 rdf:first sg:person.0647415353.43
109 rdf:rest rdf:nil
110 N3f041437b7cd4a0983f912c3d30dc005 rdf:first sg:person.0774221474.24
111 rdf:rest Ne3767010a2764667bb4067228643c3fb
112 N4b96670592d1464e928df418cda3c957 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
113 schema:name Echocardiography
114 rdf:type schema:DefinedTerm
115 N4f618095334246e5ada409924b6bdbff rdf:first sg:person.0715625754.71
116 rdf:rest N9508b98bf6b54d138439fe16239f694a
117 N556f0a1618844b50921dcc71e5f1bcb0 rdf:first sg:person.01266125010.66
118 rdf:rest N4f618095334246e5ada409924b6bdbff
119 N8939725c60024506abd76e12c92da4cb schema:name dimensions_id
120 schema:value pub.1136208185
121 rdf:type schema:PropertyValue
122 N8a2c38cce28a434aaa8483035a7a3dcf schema:name doi
123 schema:value 10.1007/s12574-021-00520-1
124 rdf:type schema:PropertyValue
125 N9508b98bf6b54d138439fe16239f694a rdf:first sg:person.0723621375.10
126 rdf:rest N00bf6a5e89f34b44bbf80463b25d47e5
127 Na5e5ce45739c468dbff94a231773d9ed schema:issueNumber 3
128 rdf:type schema:PublicationIssue
129 Nb0d7ffb274b3434aaee0f5fd34e18738 schema:name Springer Nature - SN SciGraph project
130 rdf:type schema:Organization
131 Nb317acd0d07743f884aa58303864293c rdf:first sg:person.01364434455.38
132 rdf:rest N556f0a1618844b50921dcc71e5f1bcb0
133 Nc617476c7c45449e91daa6cc340cbba8 rdf:first sg:person.01042334674.03
134 rdf:rest N3f041437b7cd4a0983f912c3d30dc005
135 Ncace768ff5aa41e29e649be7bfac02eb rdf:first sg:person.0611657674.62
136 rdf:rest Ndaaab95cc48c49298fd522ca56c5a941
137 Nda6b77e038d444da9eceed3d5b5eadb6 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
138 schema:name Ventricular Function, Left
139 rdf:type schema:DefinedTerm
140 Ndaaab95cc48c49298fd522ca56c5a941 rdf:first sg:person.01347751771.77
141 rdf:rest N11b2a9c5c40647e1a5fad320550f5aec
142 Ndc9af06e9f1948f29249ffbfb73f05e9 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
143 schema:name Ventricular Dysfunction, Left
144 rdf:type schema:DefinedTerm
145 Ne3767010a2764667bb4067228643c3fb rdf:first sg:person.0710230113.99
146 rdf:rest Ncace768ff5aa41e29e649be7bfac02eb
147 Ne736578fe7474f9fa95c2f88e94357cd schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
148 schema:name Heart Ventricles
149 rdf:type schema:DefinedTerm
150 Nf1ea424e7a564c0abdfe63ef2498b76c schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
151 schema:name Ventricular Pressure
152 rdf:type schema:DefinedTerm
153 Nfd8b4d1fa24b49cc8130ff7d985824cf rdf:first sg:person.010772153323.77
154 rdf:rest Nb317acd0d07743f884aa58303864293c
155 anzsrc-for:11 schema:inDefinedTermSet anzsrc-for:
156 schema:name Medical and Health Sciences
157 rdf:type schema:DefinedTerm
158 anzsrc-for:1102 schema:inDefinedTermSet anzsrc-for:
159 schema:name Cardiorespiratory Medicine and Haematology
160 rdf:type schema:DefinedTerm
161 sg:journal.1036334 schema:issn 1349-0222
162 1880-344X
163 schema:name Journal of Echocardiography
164 schema:publisher Springer Nature
165 rdf:type schema:Periodical
166 sg:person.01042334674.03 schema:affiliation grid-institutes:grid.412857.d
167 schema:familyName Shimamura
168 schema:givenName Kunihiro
169 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01042334674.03
170 rdf:type schema:Person
171 sg:person.01051432331.47 schema:affiliation grid-institutes:grid.412857.d
172 schema:familyName Kashiwagi
173 schema:givenName Manabu
174 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01051432331.47
175 rdf:type schema:Person
176 sg:person.010772153323.77 schema:affiliation grid-institutes:grid.412857.d
177 schema:familyName Nakajima
178 schema:givenName Yuki
179 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.010772153323.77
180 rdf:type schema:Person
181 sg:person.01266125010.66 schema:affiliation grid-institutes:grid.412857.d
182 schema:familyName Takemoto
183 schema:givenName Kazushi
184 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01266125010.66
185 rdf:type schema:Person
186 sg:person.01347751771.77 schema:affiliation grid-institutes:grid.412857.d
187 schema:familyName Kubo
188 schema:givenName Takashi
189 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01347751771.77
190 rdf:type schema:Person
191 sg:person.01364434455.38 schema:affiliation grid-institutes:grid.412857.d
192 schema:familyName Hozumi
193 schema:givenName Takeshi
194 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01364434455.38
195 rdf:type schema:Person
196 sg:person.0611657674.62 schema:affiliation grid-institutes:grid.412857.d
197 schema:familyName Tanimoto
198 schema:givenName Takashi
199 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0611657674.62
200 rdf:type schema:Person
201 sg:person.0647415353.43 schema:affiliation grid-institutes:grid.412857.d
202 schema:familyName Akasaka
203 schema:givenName Takashi
204 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0647415353.43
205 rdf:type schema:Person
206 sg:person.0710230113.99 schema:affiliation grid-institutes:grid.412857.d
207 schema:familyName Kuroi
208 schema:givenName Akio
209 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0710230113.99
210 rdf:type schema:Person
211 sg:person.0715625754.71 schema:affiliation grid-institutes:grid.412857.d
212 schema:familyName Fujita
213 schema:givenName Suwako
214 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0715625754.71
215 rdf:type schema:Person
216 sg:person.0723621375.10 schema:affiliation grid-institutes:grid.412857.d
217 schema:familyName Wada
218 schema:givenName Teruaki
219 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0723621375.10
220 rdf:type schema:Person
221 sg:person.0736227535.42 schema:affiliation grid-institutes:grid.412857.d
222 schema:familyName Tanaka
223 schema:givenName Atsushi
224 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0736227535.42
225 rdf:type schema:Person
226 sg:person.0774221474.24 schema:affiliation grid-institutes:grid.412857.d
227 schema:familyName Shiono
228 schema:givenName Yasutsugu
229 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0774221474.24
230 rdf:type schema:Person
231 sg:pub.10.1007/bf03181570 schema:sameAs https://app.dimensions.ai/details/publication/pub.1000615577
232 https://doi.org/10.1007/bf03181570
233 rdf:type schema:CreativeWork
234 sg:pub.10.1007/s12574-016-0321-5 schema:sameAs https://app.dimensions.ai/details/publication/pub.1035769505
235 https://doi.org/10.1007/s12574-016-0321-5
236 rdf:type schema:CreativeWork
237 grid-institutes:grid.412857.d schema:alternateName Department of Cardiovascular Medicine, Wakayama Medical University, 811-1 Kimiidera, 641-8509, Wakayama, Japan
238 schema:name Department of Cardiovascular Medicine, Wakayama Medical University, 811-1 Kimiidera, 641-8509, Wakayama, Japan
239 rdf:type schema:Organization
 




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


...