The inter-arm difference in systolic blood pressure is a novel risk marker for subclinical atherosclerosis in patients with type 2 ... View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2014-03-06

AUTHORS

Yoshimitsu Tanaka, Michiaki Fukui, Muhei Tanaka, Yukiko Fukuda, Kazuteru Mitsuhashi, Hiroshi Okada, Masahiro Yamazaki, Goji Hasegawa, Keiji Yoshioka, Naoto Nakamura

ABSTRACT

Recent studies have suggested that the inter-arm blood pressure difference (IAD) is associated with cardiovascular events and mortality. The aim of this study was to assess whether the IAD could be a marker for subclinical atherosclerosis in patients with type 2 diabetes who are at high risk of cardiovascular disease (CVD). In a cross-sectional retrospective study of 206 Japanese patients with type 2 diabetes aged 49–76 years, we examined the correlation of the IAD with the carotid intima-media thickness (IMT), ankle-brachial index (ABI) or cardio ankle vascular index (CAVI). The IAD was positively correlated with the maximum IMT (r=0.266, P<0.0001), mean IMT (r=0.209, P=0.00726) or CAVI (r=0.240, P=0.0005). The IAD was higher in patients with CVD than in those without (P=0.0020). A multiple linear regression analysis demonstrated that the IAD was an independent determinant of maximum IMT (β=0.169, P=0.0167), mean IMT (β=0.178, P=0.0153), ABI (β=−0.222, P=0.0033) or CAVI (β=0.213, P=0.0011) after adjusting for known risk factors. The area under the receiver operating characteristic curve (AUC) of the IAD as a predictor of subclinical atherosclerosis was similar to the AUC of the Framingham 10-year coronary heart disease risk score. In conclusion, the IAD could be a novel risk marker for subclinical atherosclerosis in patients with type 2 diabetes. More... »

PAGES

548-552

Identifiers

URI

http://scigraph.springernature.com/pub.10.1038/hr.2014.30

DOI

http://dx.doi.org/10.1038/hr.2014.30

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1024371545

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/24599017


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": "Aged", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Ankle Brachial Index", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Arm", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Asian Continental Ancestry Group", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Atherosclerosis", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Blood Pressure", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Blood Pressure Monitors", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Carotid Intima-Media Thickness", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Cross-Sectional Studies", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Diabetes Mellitus, Type 2", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Diagnostic Techniques, Cardiovascular", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Female", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Humans", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Linear Models", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Male", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Middle Aged", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Retrospective Studies", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Risk Factors", 
        "type": "DefinedTerm"
      }
    ], 
    "author": [
      {
        "affiliation": {
          "alternateName": "Department of Diabetes and Endocrine Diseases, Matsushita Memorial Hospital, Osaka, Moriguchi, Japan", 
          "id": "http://www.grid.ac/institutes/grid.416591.e", 
          "name": [
            "Department of Diabetes and Endocrine Diseases, Matsushita Memorial Hospital, Osaka, Moriguchi, Japan"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Tanaka", 
        "givenName": "Yoshimitsu", 
        "id": "sg:person.01314057106.13", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01314057106.13"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Department of Endocrinology and Metabolism, Kyoto Prefectural University of Medicine, Graduate School of Medical Science, Kyoto, Japan", 
          "id": "http://www.grid.ac/institutes/grid.272458.e", 
          "name": [
            "Department of Endocrinology and Metabolism, Kyoto Prefectural University of Medicine, Graduate School of Medical Science, Kyoto, Japan"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Fukui", 
        "givenName": "Michiaki", 
        "id": "sg:person.016357516722.38", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.016357516722.38"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Department of Endocrinology and Metabolism, Kyoto Prefectural University of Medicine, Graduate School of Medical Science, Kyoto, Japan", 
          "id": "http://www.grid.ac/institutes/grid.272458.e", 
          "name": [
            "Department of Endocrinology and Metabolism, Kyoto Prefectural University of Medicine, Graduate School of Medical Science, Kyoto, Japan"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Tanaka", 
        "givenName": "Muhei", 
        "id": "sg:person.0703420760.35", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0703420760.35"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Department of Diabetes and Endocrine Diseases, Matsushita Memorial Hospital, Osaka, Moriguchi, Japan", 
          "id": "http://www.grid.ac/institutes/grid.416591.e", 
          "name": [
            "Department of Diabetes and Endocrine Diseases, Matsushita Memorial Hospital, Osaka, Moriguchi, Japan"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Fukuda", 
        "givenName": "Yukiko", 
        "id": "sg:person.0662513645.13", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0662513645.13"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Department of Endocrinology and Metabolism, Kyoto Prefectural University of Medicine, Graduate School of Medical Science, Kyoto, Japan", 
          "id": "http://www.grid.ac/institutes/grid.272458.e", 
          "name": [
            "Department of Endocrinology and Metabolism, Kyoto Prefectural University of Medicine, Graduate School of Medical Science, Kyoto, Japan"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Mitsuhashi", 
        "givenName": "Kazuteru", 
        "id": "sg:person.01016276136.59", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01016276136.59"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Department of Endocrinology and Metabolism, Kyoto Prefectural University of Medicine, Graduate School of Medical Science, Kyoto, Japan", 
          "id": "http://www.grid.ac/institutes/grid.272458.e", 
          "name": [
            "Department of Endocrinology and Metabolism, Kyoto Prefectural University of Medicine, Graduate School of Medical Science, Kyoto, Japan"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Okada", 
        "givenName": "Hiroshi", 
        "id": "sg:person.01261542332.81", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01261542332.81"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Department of Endocrinology and Metabolism, Kyoto Prefectural University of Medicine, Graduate School of Medical Science, Kyoto, Japan", 
          "id": "http://www.grid.ac/institutes/grid.272458.e", 
          "name": [
            "Department of Endocrinology and Metabolism, Kyoto Prefectural University of Medicine, Graduate School of Medical Science, Kyoto, Japan"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Yamazaki", 
        "givenName": "Masahiro", 
        "id": "sg:person.01103041632.87", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01103041632.87"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Department of Endocrinology and Metabolism, Kyoto Prefectural University of Medicine, Graduate School of Medical Science, Kyoto, Japan", 
          "id": "http://www.grid.ac/institutes/grid.272458.e", 
          "name": [
            "Department of Endocrinology and Metabolism, Kyoto Prefectural University of Medicine, Graduate School of Medical Science, Kyoto, Japan"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Hasegawa", 
        "givenName": "Goji", 
        "id": "sg:person.01162763674.43", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01162763674.43"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Yoshioka Diabetes Clinic, Osaka, Moriguchi, Japan", 
          "id": "http://www.grid.ac/institutes/None", 
          "name": [
            "Yoshioka Diabetes Clinic, Osaka, Moriguchi, Japan"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Yoshioka", 
        "givenName": "Keiji", 
        "id": "sg:person.01125266650.19", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01125266650.19"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Department of Endocrinology and Metabolism, Kyoto Prefectural University of Medicine, Graduate School of Medical Science, Kyoto, Japan", 
          "id": "http://www.grid.ac/institutes/grid.272458.e", 
          "name": [
            "Department of Endocrinology and Metabolism, Kyoto Prefectural University of Medicine, Graduate School of Medical Science, Kyoto, Japan"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Nakamura", 
        "givenName": "Naoto", 
        "id": "sg:person.0677442163.58", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0677442163.58"
        ], 
        "type": "Person"
      }
    ], 
    "citation": [
      {
        "id": "sg:pub.10.1038/hr.2012.207", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1030679161", 
          "https://doi.org/10.1038/hr.2012.207"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/sj.jhh.1002093", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1005374653", 
          "https://doi.org/10.1038/sj.jhh.1002093"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/sj.jhh.1000998", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1033572649", 
          "https://doi.org/10.1038/sj.jhh.1000998"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/sj.jhh.1002209", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1046954653", 
          "https://doi.org/10.1038/sj.jhh.1002209"
        ], 
        "type": "CreativeWork"
      }
    ], 
    "datePublished": "2014-03-06", 
    "datePublishedReg": "2014-03-06", 
    "description": "Recent studies have suggested that the inter-arm blood pressure difference (IAD) is associated with cardiovascular events and mortality. The aim of this study was to assess whether the IAD could be a marker for subclinical atherosclerosis in patients with type 2 diabetes who are at high risk of cardiovascular disease (CVD). In a cross-sectional retrospective study of 206 Japanese patients with type 2 diabetes aged 49\u201376 years, we examined the correlation of the IAD with the carotid intima-media thickness (IMT), ankle-brachial index (ABI) or cardio ankle vascular index (CAVI). The IAD was positively correlated with the maximum IMT (r=0.266, P<0.0001), mean IMT (r=0.209, P=0.00726) or CAVI (r=0.240, P=0.0005). The IAD was higher in patients with CVD than in those without (P=0.0020). A multiple linear regression analysis demonstrated that the IAD was an independent determinant of maximum IMT (\u03b2=0.169, P=0.0167), mean IMT (\u03b2=0.178, P=0.0153), ABI (\u03b2=\u22120.222, P=0.0033) or CAVI (\u03b2=0.213, P=0.0011) after adjusting for known risk factors. The area under the receiver operating characteristic curve (AUC) of the IAD as a predictor of subclinical atherosclerosis was similar to the AUC of the Framingham 10-year coronary heart disease risk score. In conclusion, the IAD could be a novel risk marker for subclinical atherosclerosis in patients with type 2 diabetes.", 
    "genre": "article", 
    "id": "sg:pub.10.1038/hr.2014.30", 
    "inLanguage": "en", 
    "isAccessibleForFree": false, 
    "isPartOf": [
      {
        "id": "sg:journal.1313717", 
        "issn": [
          "0916-9636", 
          "1348-4214"
        ], 
        "name": "Hypertension Research", 
        "publisher": "Springer Nature", 
        "type": "Periodical"
      }, 
      {
        "issueNumber": "6", 
        "type": "PublicationIssue"
      }, 
      {
        "type": "PublicationVolume", 
        "volumeNumber": "37"
      }
    ], 
    "keywords": [
      "inter-arm blood pressure difference", 
      "cardio-ankle vascular index", 
      "intima-media thickness", 
      "ankle-brachial index", 
      "type 2 diabetes", 
      "maximum intima-media thickness", 
      "novel risk markers", 
      "subclinical atherosclerosis", 
      "cardiovascular disease", 
      "risk markers", 
      "coronary heart disease risk score", 
      "carotid intima-media thickness", 
      "cross-sectional retrospective study", 
      "systolic blood pressure", 
      "blood pressure difference", 
      "inter-arm difference", 
      "disease risk score", 
      "cardiovascular events", 
      "vascular index", 
      "blood pressure", 
      "retrospective study", 
      "independent determinants", 
      "risk factors", 
      "Japanese patients", 
      "multiple linear regression analysis", 
      "high risk", 
      "risk score", 
      "linear regression analysis", 
      "patients", 
      "type 2", 
      "atherosclerosis", 
      "diabetes", 
      "characteristic curve", 
      "regression analysis", 
      "markers", 
      "Recent studies", 
      "Framingham", 
      "mortality", 
      "disease", 
      "study", 
      "AUC", 
      "index", 
      "differences", 
      "risk", 
      "scores", 
      "predictors", 
      "conclusion", 
      "aim", 
      "years", 
      "determinants", 
      "factors", 
      "correlation", 
      "events", 
      "pressure", 
      "pressure difference", 
      "curves", 
      "analysis", 
      "area", 
      "receiver", 
      "thickness", 
      "ankle vascular index", 
      "heart disease risk score"
    ], 
    "name": "The inter-arm difference in systolic blood pressure is a novel risk marker for subclinical atherosclerosis in patients with type 2 diabetes", 
    "pagination": "548-552", 
    "productId": [
      {
        "name": "dimensions_id", 
        "type": "PropertyValue", 
        "value": [
          "pub.1024371545"
        ]
      }, 
      {
        "name": "doi", 
        "type": "PropertyValue", 
        "value": [
          "10.1038/hr.2014.30"
        ]
      }, 
      {
        "name": "pubmed_id", 
        "type": "PropertyValue", 
        "value": [
          "24599017"
        ]
      }
    ], 
    "sameAs": [
      "https://doi.org/10.1038/hr.2014.30", 
      "https://app.dimensions.ai/details/publication/pub.1024371545"
    ], 
    "sdDataset": "articles", 
    "sdDatePublished": "2022-01-01T18:31", 
    "sdLicense": "https://scigraph.springernature.com/explorer/license/", 
    "sdPublisher": {
      "name": "Springer Nature - SN SciGraph project", 
      "type": "Organization"
    }, 
    "sdSource": "s3://com-springernature-scigraph/baseset/20220101/entities/gbq_results/article/article_619.jsonl", 
    "type": "ScholarlyArticle", 
    "url": "https://doi.org/10.1038/hr.2014.30"
  }
]
 

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.10.1038/hr.2014.30'

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

curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1038/hr.2014.30'

Turtle is a human-readable linked data format.

curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1038/hr.2014.30'

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

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1038/hr.2014.30'


 

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

281 TRIPLES      22 PREDICATES      110 URIs      98 LITERALS      25 BLANK NODES

Subject Predicate Object
1 sg:pub.10.1038/hr.2014.30 schema:about N0d55b088fb7e4cce97e4a4c4dbb27eb0
2 N118720026b8f4227a7cfe33c54ca7065
3 N21d80828412b40829025829dd701fdee
4 N2408a27ba07346be88724f289cdb2247
5 N28ca4bc79dcc40aeaf63d42b67920f79
6 N32c6f0138d164564bb3bfc224e375e36
7 N34598c50015249e6a45ef764d7317755
8 N3cb255075cc347cbbb8c03ed2451bd88
9 N4e5ff7fcfc824707b93fa8c468357429
10 N5f91e22fe8d949819f6d635f19054931
11 N7014caa4c5774631be0787a9106af078
12 N9a86f4151ceb424ab34788a4e73bb378
13 Na549e21c1f784451961dce4a4553cb0e
14 Nc97ea14f3c32458c9a23991e5d9e6f76
15 Nce1caac97dee45048d23986b78f92291
16 Ne0ef65efa2574fa1ac44b8fc02cb1ba7
17 Nefeefd1e86d14cd9a1b41f610a23e61a
18 Nfb42ef12d6e94c46873ea5e750c4dd1f
19 anzsrc-for:11
20 anzsrc-for:1102
21 schema:author N58db58329ea5491893a77e3f9af10386
22 schema:citation sg:pub.10.1038/hr.2012.207
23 sg:pub.10.1038/sj.jhh.1000998
24 sg:pub.10.1038/sj.jhh.1002093
25 sg:pub.10.1038/sj.jhh.1002209
26 schema:datePublished 2014-03-06
27 schema:datePublishedReg 2014-03-06
28 schema:description Recent studies have suggested that the inter-arm blood pressure difference (IAD) is associated with cardiovascular events and mortality. The aim of this study was to assess whether the IAD could be a marker for subclinical atherosclerosis in patients with type 2 diabetes who are at high risk of cardiovascular disease (CVD). In a cross-sectional retrospective study of 206 Japanese patients with type 2 diabetes aged 49–76 years, we examined the correlation of the IAD with the carotid intima-media thickness (IMT), ankle-brachial index (ABI) or cardio ankle vascular index (CAVI). The IAD was positively correlated with the maximum IMT (r=0.266, P<0.0001), mean IMT (r=0.209, P=0.00726) or CAVI (r=0.240, P=0.0005). The IAD was higher in patients with CVD than in those without (P=0.0020). A multiple linear regression analysis demonstrated that the IAD was an independent determinant of maximum IMT (β=0.169, P=0.0167), mean IMT (β=0.178, P=0.0153), ABI (β=−0.222, P=0.0033) or CAVI (β=0.213, P=0.0011) after adjusting for known risk factors. The area under the receiver operating characteristic curve (AUC) of the IAD as a predictor of subclinical atherosclerosis was similar to the AUC of the Framingham 10-year coronary heart disease risk score. In conclusion, the IAD could be a novel risk marker for subclinical atherosclerosis in patients with type 2 diabetes.
29 schema:genre article
30 schema:inLanguage en
31 schema:isAccessibleForFree false
32 schema:isPartOf N9ee5288000f844808ff655c2ffc7374a
33 Nb1a9e85a8d4c41efb10d3de68608cb3f
34 sg:journal.1313717
35 schema:keywords AUC
36 Framingham
37 Japanese patients
38 Recent studies
39 aim
40 analysis
41 ankle vascular index
42 ankle-brachial index
43 area
44 atherosclerosis
45 blood pressure
46 blood pressure difference
47 cardio-ankle vascular index
48 cardiovascular disease
49 cardiovascular events
50 carotid intima-media thickness
51 characteristic curve
52 conclusion
53 coronary heart disease risk score
54 correlation
55 cross-sectional retrospective study
56 curves
57 determinants
58 diabetes
59 differences
60 disease
61 disease risk score
62 events
63 factors
64 heart disease risk score
65 high risk
66 independent determinants
67 index
68 inter-arm blood pressure difference
69 inter-arm difference
70 intima-media thickness
71 linear regression analysis
72 markers
73 maximum intima-media thickness
74 mortality
75 multiple linear regression analysis
76 novel risk markers
77 patients
78 predictors
79 pressure
80 pressure difference
81 receiver
82 regression analysis
83 retrospective study
84 risk
85 risk factors
86 risk markers
87 risk score
88 scores
89 study
90 subclinical atherosclerosis
91 systolic blood pressure
92 thickness
93 type 2
94 type 2 diabetes
95 vascular index
96 years
97 schema:name The inter-arm difference in systolic blood pressure is a novel risk marker for subclinical atherosclerosis in patients with type 2 diabetes
98 schema:pagination 548-552
99 schema:productId Na41c2f40c1d8428982e7d62f9c059dac
100 Nbd3fb273a3d54898b3d1db857221c9a0
101 Ncc5bd71461214dd38c8e2f6faa0e5c11
102 schema:sameAs https://app.dimensions.ai/details/publication/pub.1024371545
103 https://doi.org/10.1038/hr.2014.30
104 schema:sdDatePublished 2022-01-01T18:31
105 schema:sdLicense https://scigraph.springernature.com/explorer/license/
106 schema:sdPublisher N7a000988486b47f6b70ab3136387710c
107 schema:url https://doi.org/10.1038/hr.2014.30
108 sgo:license sg:explorer/license/
109 sgo:sdDataset articles
110 rdf:type schema:ScholarlyArticle
111 N0d55b088fb7e4cce97e4a4c4dbb27eb0 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
112 schema:name Humans
113 rdf:type schema:DefinedTerm
114 N118720026b8f4227a7cfe33c54ca7065 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
115 schema:name Female
116 rdf:type schema:DefinedTerm
117 N21d80828412b40829025829dd701fdee schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
118 schema:name Diabetes Mellitus, Type 2
119 rdf:type schema:DefinedTerm
120 N2408a27ba07346be88724f289cdb2247 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
121 schema:name Blood Pressure
122 rdf:type schema:DefinedTerm
123 N28ca4bc79dcc40aeaf63d42b67920f79 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
124 schema:name Asian Continental Ancestry Group
125 rdf:type schema:DefinedTerm
126 N32c6f0138d164564bb3bfc224e375e36 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
127 schema:name Male
128 rdf:type schema:DefinedTerm
129 N34598c50015249e6a45ef764d7317755 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
130 schema:name Retrospective Studies
131 rdf:type schema:DefinedTerm
132 N3cb255075cc347cbbb8c03ed2451bd88 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
133 schema:name Risk Factors
134 rdf:type schema:DefinedTerm
135 N4e5ff7fcfc824707b93fa8c468357429 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
136 schema:name Diagnostic Techniques, Cardiovascular
137 rdf:type schema:DefinedTerm
138 N5617a26228fb44ae8aed03cb424df598 rdf:first sg:person.01125266650.19
139 rdf:rest Nfd7e6410153546d3ae52172d0a1a7116
140 N58db58329ea5491893a77e3f9af10386 rdf:first sg:person.01314057106.13
141 rdf:rest Nfbb266a2277e4ec2857012aa117e7487
142 N5f91e22fe8d949819f6d635f19054931 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
143 schema:name Middle Aged
144 rdf:type schema:DefinedTerm
145 N6f353f0a01a249f2aaabe46f25e59402 rdf:first sg:person.01103041632.87
146 rdf:rest N858ebf9621a146deaa4d579acab87309
147 N7014caa4c5774631be0787a9106af078 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
148 schema:name Ankle Brachial Index
149 rdf:type schema:DefinedTerm
150 N7a000988486b47f6b70ab3136387710c schema:name Springer Nature - SN SciGraph project
151 rdf:type schema:Organization
152 N858ebf9621a146deaa4d579acab87309 rdf:first sg:person.01162763674.43
153 rdf:rest N5617a26228fb44ae8aed03cb424df598
154 N88ac419ff6f0447bbff26061d7851ac6 rdf:first sg:person.01261542332.81
155 rdf:rest N6f353f0a01a249f2aaabe46f25e59402
156 N9a86f4151ceb424ab34788a4e73bb378 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
157 schema:name Arm
158 rdf:type schema:DefinedTerm
159 N9ee5288000f844808ff655c2ffc7374a schema:volumeNumber 37
160 rdf:type schema:PublicationVolume
161 Na41c2f40c1d8428982e7d62f9c059dac schema:name doi
162 schema:value 10.1038/hr.2014.30
163 rdf:type schema:PropertyValue
164 Na549e21c1f784451961dce4a4553cb0e schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
165 schema:name Linear Models
166 rdf:type schema:DefinedTerm
167 Nafe88d6bc5434db59ec05683cce9b861 rdf:first sg:person.0662513645.13
168 rdf:rest Neda6092bd797474093fecc7930f01ae5
169 Nb1a9e85a8d4c41efb10d3de68608cb3f schema:issueNumber 6
170 rdf:type schema:PublicationIssue
171 Nbd3fb273a3d54898b3d1db857221c9a0 schema:name dimensions_id
172 schema:value pub.1024371545
173 rdf:type schema:PropertyValue
174 Nc97ea14f3c32458c9a23991e5d9e6f76 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
175 schema:name Atherosclerosis
176 rdf:type schema:DefinedTerm
177 Ncc5bd71461214dd38c8e2f6faa0e5c11 schema:name pubmed_id
178 schema:value 24599017
179 rdf:type schema:PropertyValue
180 Nce1caac97dee45048d23986b78f92291 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
181 schema:name Aged
182 rdf:type schema:DefinedTerm
183 Ndc12d47884c7487d9da97405692e09f3 rdf:first sg:person.0703420760.35
184 rdf:rest Nafe88d6bc5434db59ec05683cce9b861
185 Ne0ef65efa2574fa1ac44b8fc02cb1ba7 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
186 schema:name Cross-Sectional Studies
187 rdf:type schema:DefinedTerm
188 Neda6092bd797474093fecc7930f01ae5 rdf:first sg:person.01016276136.59
189 rdf:rest N88ac419ff6f0447bbff26061d7851ac6
190 Nefeefd1e86d14cd9a1b41f610a23e61a schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
191 schema:name Blood Pressure Monitors
192 rdf:type schema:DefinedTerm
193 Nfb42ef12d6e94c46873ea5e750c4dd1f schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
194 schema:name Carotid Intima-Media Thickness
195 rdf:type schema:DefinedTerm
196 Nfbb266a2277e4ec2857012aa117e7487 rdf:first sg:person.016357516722.38
197 rdf:rest Ndc12d47884c7487d9da97405692e09f3
198 Nfd7e6410153546d3ae52172d0a1a7116 rdf:first sg:person.0677442163.58
199 rdf:rest rdf:nil
200 anzsrc-for:11 schema:inDefinedTermSet anzsrc-for:
201 schema:name Medical and Health Sciences
202 rdf:type schema:DefinedTerm
203 anzsrc-for:1102 schema:inDefinedTermSet anzsrc-for:
204 schema:name Cardiorespiratory Medicine and Haematology
205 rdf:type schema:DefinedTerm
206 sg:journal.1313717 schema:issn 0916-9636
207 1348-4214
208 schema:name Hypertension Research
209 schema:publisher Springer Nature
210 rdf:type schema:Periodical
211 sg:person.01016276136.59 schema:affiliation grid-institutes:grid.272458.e
212 schema:familyName Mitsuhashi
213 schema:givenName Kazuteru
214 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01016276136.59
215 rdf:type schema:Person
216 sg:person.01103041632.87 schema:affiliation grid-institutes:grid.272458.e
217 schema:familyName Yamazaki
218 schema:givenName Masahiro
219 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01103041632.87
220 rdf:type schema:Person
221 sg:person.01125266650.19 schema:affiliation grid-institutes:None
222 schema:familyName Yoshioka
223 schema:givenName Keiji
224 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01125266650.19
225 rdf:type schema:Person
226 sg:person.01162763674.43 schema:affiliation grid-institutes:grid.272458.e
227 schema:familyName Hasegawa
228 schema:givenName Goji
229 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01162763674.43
230 rdf:type schema:Person
231 sg:person.01261542332.81 schema:affiliation grid-institutes:grid.272458.e
232 schema:familyName Okada
233 schema:givenName Hiroshi
234 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01261542332.81
235 rdf:type schema:Person
236 sg:person.01314057106.13 schema:affiliation grid-institutes:grid.416591.e
237 schema:familyName Tanaka
238 schema:givenName Yoshimitsu
239 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01314057106.13
240 rdf:type schema:Person
241 sg:person.016357516722.38 schema:affiliation grid-institutes:grid.272458.e
242 schema:familyName Fukui
243 schema:givenName Michiaki
244 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.016357516722.38
245 rdf:type schema:Person
246 sg:person.0662513645.13 schema:affiliation grid-institutes:grid.416591.e
247 schema:familyName Fukuda
248 schema:givenName Yukiko
249 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0662513645.13
250 rdf:type schema:Person
251 sg:person.0677442163.58 schema:affiliation grid-institutes:grid.272458.e
252 schema:familyName Nakamura
253 schema:givenName Naoto
254 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0677442163.58
255 rdf:type schema:Person
256 sg:person.0703420760.35 schema:affiliation grid-institutes:grid.272458.e
257 schema:familyName Tanaka
258 schema:givenName Muhei
259 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0703420760.35
260 rdf:type schema:Person
261 sg:pub.10.1038/hr.2012.207 schema:sameAs https://app.dimensions.ai/details/publication/pub.1030679161
262 https://doi.org/10.1038/hr.2012.207
263 rdf:type schema:CreativeWork
264 sg:pub.10.1038/sj.jhh.1000998 schema:sameAs https://app.dimensions.ai/details/publication/pub.1033572649
265 https://doi.org/10.1038/sj.jhh.1000998
266 rdf:type schema:CreativeWork
267 sg:pub.10.1038/sj.jhh.1002093 schema:sameAs https://app.dimensions.ai/details/publication/pub.1005374653
268 https://doi.org/10.1038/sj.jhh.1002093
269 rdf:type schema:CreativeWork
270 sg:pub.10.1038/sj.jhh.1002209 schema:sameAs https://app.dimensions.ai/details/publication/pub.1046954653
271 https://doi.org/10.1038/sj.jhh.1002209
272 rdf:type schema:CreativeWork
273 grid-institutes:None schema:alternateName Yoshioka Diabetes Clinic, Osaka, Moriguchi, Japan
274 schema:name Yoshioka Diabetes Clinic, Osaka, Moriguchi, Japan
275 rdf:type schema:Organization
276 grid-institutes:grid.272458.e schema:alternateName Department of Endocrinology and Metabolism, Kyoto Prefectural University of Medicine, Graduate School of Medical Science, Kyoto, Japan
277 schema:name Department of Endocrinology and Metabolism, Kyoto Prefectural University of Medicine, Graduate School of Medical Science, Kyoto, Japan
278 rdf:type schema:Organization
279 grid-institutes:grid.416591.e schema:alternateName Department of Diabetes and Endocrine Diseases, Matsushita Memorial Hospital, Osaka, Moriguchi, Japan
280 schema:name Department of Diabetes and Endocrine Diseases, Matsushita Memorial Hospital, Osaka, Moriguchi, Japan
281 rdf:type schema:Organization
 




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


...