Predictive value of CHADS2 and CHA2DS2-VASc scores for acute myocardial infarction in patients with atrial fibrillation View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2017-12

AUTHORS

Hui Pang, Bing Han, Qiang Fu, Zhenkun Zong

ABSTRACT

The presence of acute myocardial infarction (AMI) confers a poor prognosis in atrial fibrillation (AF), associated with increased mortality dramatically. This study aimed to evaluate the predictive value of CHADS2 and CHA2DS2-VASc scores for AMI in patients with AF. This retrospective study enrolled 5140 consecutive nonvalvular AF patients, 300 patients with AMI and 4840 patients without AMI. We identified the optimal cut-off values of the CHADS2 and CHA2DS2-VASc scores each based on receiver operating characteristic curves to predict the risk of AMI. Both CHADS2 score and CHA2DS2-VASc score were associated with an increased odds ratio of the prevalence of AMI in patients with AF, after adjustment for hyperlipidaemia, hyperuricemia, hyperthyroidism, hypothyroidism and obstructive sleep apnea. The present results showed that the area under the curve (AUC) for CHADS2 score was 0.787 with a similar accuracy of the CHA2DS2-VASc score (AUC 0.750) in predicting "high-risk" AF patients who developed AMI. However, the predictive accuracy of the two clinical-based risk scores was fair. The CHA2DS2-VASc score has fair predictive value for identifying high-risk patients with AF and is not significantly superior to CHADS2 in predicting patients who develop AMI. More... »

PAGES

4730

Identifiers

URI

http://scigraph.springernature.com/pub.10.1038/s41598-017-04604-w

DOI

http://dx.doi.org/10.1038/s41598-017-04604-w

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1090351659

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/28680116


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/2008/1102", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Cardiorespiratory Medicine and Haematology", 
        "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": "Xuzhou Central Hospital", 
          "id": "https://www.grid.ac/institutes/grid.452207.6", 
          "name": [
            "Department of Cardiology, Xuzhou Central Hospital, Xuzhou Clinical School of Xuzhou Medical College, Affiliated Xuzhou Hospital of Medical College of Southeast University, Xuzhou, Jiangsu, China"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Pang", 
        "givenName": "Hui", 
        "id": "sg:person.0745323234.48", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0745323234.48"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Xuzhou Central Hospital", 
          "id": "https://www.grid.ac/institutes/grid.452207.6", 
          "name": [
            "Department of Cardiology, Xuzhou Central Hospital, Xuzhou Clinical School of Xuzhou Medical College, Affiliated Xuzhou Hospital of Medical College of Southeast University, Xuzhou, Jiangsu, China"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Han", 
        "givenName": "Bing", 
        "id": "sg:person.01013436434.68", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01013436434.68"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Xuzhou Central Hospital", 
          "id": "https://www.grid.ac/institutes/grid.452207.6", 
          "name": [
            "Department of Cardiology, Xuzhou Central Hospital, Xuzhou Clinical School of Xuzhou Medical College, Affiliated Xuzhou Hospital of Medical College of Southeast University, Xuzhou, Jiangsu, China"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Fu", 
        "givenName": "Qiang", 
        "id": "sg:person.01171657162.36", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01171657162.36"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Affiliated Hospital of Xuzhou Medical College", 
          "id": "https://www.grid.ac/institutes/grid.413389.4", 
          "name": [
            "Department of Neurosurgery, Affiliated Hospital of Xuzhou Medical College, Xuzhou, Jiangsu, China"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Zong", 
        "givenName": "Zhenkun", 
        "id": "sg:person.01100466600.44", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01100466600.44"
        ], 
        "type": "Person"
      }
    ], 
    "citation": [
      {
        "id": "https://doi.org/10.1016/j.jjcc.2013.08.007", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1002273989"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.respe.2014.11.003", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1003047190"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.ijcard.2014.10.039", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1004857749"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1161/circimaging.110.959403", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1006230314"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1161/circimaging.110.959403", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1006230314"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1161/circimaging.110.959403", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1006230314"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1161/circimaging.110.959403", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1006230314"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1161/circimaging.110.959403", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1006230314"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1161/circimaging.110.959403", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1006230314"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1159/000353670", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1006797297"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.recesp.2010.12.004", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1008342409"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1161/circulationaha.113.002250", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1010604349"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1161/circulationaha.113.002250", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1010604349"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1161/circulationaha.113.002250", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1010604349"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1111/j.1468-1331.2011.03518.x", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1010726404"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1161/circulationaha.115.017534", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1014369901"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1161/circulationaha.115.017534", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1014369901"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.hrthm.2014.08.003", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1019487688"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1001/jama.2015.10725", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1021110878"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1161/circulationaha.114.014145", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1023406789"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1161/circulationaha.114.014145", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1023406789"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1161/circulationaha.114.014145", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1023406789"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.amjcard.2016.07.063", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1024784124"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/srep39323", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1027106804", 
          "https://doi.org/10.1038/srep39323"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.jfma.2015.12.008", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1029047260"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.jjcc.2013.09.010", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1029874782"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1093/europace/eus305", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1030385418"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.ijcard.2016.11.114", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1030389919"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.ijcard.2016.11.114", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1030389919"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.amjcard.2016.11.035", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1032094791"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.amjcard.2014.09.005", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1034013598"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1002/sim.4085", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1037258459"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1002/sim.4085", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1037258459"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.2147/clep.s47385", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1037288120"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.jacc.2014.03.022", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1037324913"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1161/circulationaha.114.015134", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1037550571"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1161/circulationaha.114.015134", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1037550571"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.ijcard.2015.08.054", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1038560450"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1177/0003319711427391", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1039235778"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1177/0003319711427391", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1039235778"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s11999-016-4717-3", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1039274356", 
          "https://doi.org/10.1007/s11999-016-4717-3"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1007/s11999-016-4717-3", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1039274356"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.amjcard.2016.11.033", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1040877334"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1253/circj.cj-14-0038", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1049988760"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1001/jamainternmed.2013.11912", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1053438245"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1160/th12-08-0539", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1063293141"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1160/th15-07-0612", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1063294127"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.3904/kjim.2016.31.1.73", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1071557064"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.20452/pamw.2709", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1079038769"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.11909/j.issn.1671-5411.2016.08.004", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1079346675"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1136/openhrt-2016-000573", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1079402099"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1136/openhrt-2016-000573", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1079402099"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.mayocp.2016.10.008", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1084095255"
        ], 
        "type": "CreativeWork"
      }
    ], 
    "datePublished": "2017-12", 
    "datePublishedReg": "2017-12-01", 
    "description": "The presence of acute myocardial infarction (AMI) confers a poor prognosis in atrial fibrillation (AF), associated with increased mortality dramatically. This study aimed to evaluate the predictive value of CHADS2 and CHA2DS2-VASc scores for AMI in patients with AF. This retrospective study enrolled 5140 consecutive nonvalvular AF patients, 300 patients with AMI and 4840 patients without AMI. We identified the optimal cut-off values of the CHADS2 and CHA2DS2-VASc scores each based on receiver operating characteristic curves to predict the risk of AMI. Both CHADS2 score and CHA2DS2-VASc score were associated with an increased odds ratio of the prevalence of AMI in patients with AF, after adjustment for hyperlipidaemia, hyperuricemia, hyperthyroidism, hypothyroidism and obstructive sleep apnea. The present results showed that the area under the curve (AUC) for CHADS2 score was 0.787 with a similar accuracy of the CHA2DS2-VASc score (AUC 0.750) in predicting \"high-risk\" AF patients who developed AMI. However, the predictive accuracy of the two clinical-based risk scores was fair. The CHA2DS2-VASc score has fair predictive value for identifying high-risk patients with AF and is not significantly superior to CHADS2 in predicting patients who develop AMI.", 
    "genre": "research_article", 
    "id": "sg:pub.10.1038/s41598-017-04604-w", 
    "inLanguage": [
      "en"
    ], 
    "isAccessibleForFree": true, 
    "isPartOf": [
      {
        "id": "sg:journal.1045337", 
        "issn": [
          "2045-2322"
        ], 
        "name": "Scientific Reports", 
        "type": "Periodical"
      }, 
      {
        "issueNumber": "1", 
        "type": "PublicationIssue"
      }, 
      {
        "type": "PublicationVolume", 
        "volumeNumber": "7"
      }
    ], 
    "name": "Predictive value of CHADS2 and CHA2DS2-VASc scores for acute myocardial infarction in patients with atrial fibrillation", 
    "pagination": "4730", 
    "productId": [
      {
        "name": "readcube_id", 
        "type": "PropertyValue", 
        "value": [
          "dbe936fee5b2c43e06f3363b7a5adb3be5f3819e3fd380d1d59c154129c8d739"
        ]
      }, 
      {
        "name": "pubmed_id", 
        "type": "PropertyValue", 
        "value": [
          "28680116"
        ]
      }, 
      {
        "name": "nlm_unique_id", 
        "type": "PropertyValue", 
        "value": [
          "101563288"
        ]
      }, 
      {
        "name": "doi", 
        "type": "PropertyValue", 
        "value": [
          "10.1038/s41598-017-04604-w"
        ]
      }, 
      {
        "name": "dimensions_id", 
        "type": "PropertyValue", 
        "value": [
          "pub.1090351659"
        ]
      }
    ], 
    "sameAs": [
      "https://doi.org/10.1038/s41598-017-04604-w", 
      "https://app.dimensions.ai/details/publication/pub.1090351659"
    ], 
    "sdDataset": "articles", 
    "sdDatePublished": "2019-04-10T22:27", 
    "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_8690_00000493.jsonl", 
    "type": "ScholarlyArticle", 
    "url": "https://www.nature.com/articles/s41598-017-04604-w"
  }
]
 

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/s41598-017-04604-w'

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/s41598-017-04604-w'

Turtle is a human-readable linked data format.

curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1038/s41598-017-04604-w'

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

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1038/s41598-017-04604-w'


 

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

208 TRIPLES      21 PREDICATES      67 URIs      21 LITERALS      9 BLANK NODES

Subject Predicate Object
1 sg:pub.10.1038/s41598-017-04604-w schema:about anzsrc-for:11
2 anzsrc-for:1102
3 schema:author Neda5e34ae6c2448ba8341199614543a2
4 schema:citation sg:pub.10.1007/s11999-016-4717-3
5 sg:pub.10.1038/srep39323
6 https://doi.org/10.1001/jama.2015.10725
7 https://doi.org/10.1001/jamainternmed.2013.11912
8 https://doi.org/10.1002/sim.4085
9 https://doi.org/10.1007/s11999-016-4717-3
10 https://doi.org/10.1016/j.amjcard.2014.09.005
11 https://doi.org/10.1016/j.amjcard.2016.07.063
12 https://doi.org/10.1016/j.amjcard.2016.11.033
13 https://doi.org/10.1016/j.amjcard.2016.11.035
14 https://doi.org/10.1016/j.hrthm.2014.08.003
15 https://doi.org/10.1016/j.ijcard.2014.10.039
16 https://doi.org/10.1016/j.ijcard.2015.08.054
17 https://doi.org/10.1016/j.ijcard.2016.11.114
18 https://doi.org/10.1016/j.jacc.2014.03.022
19 https://doi.org/10.1016/j.jfma.2015.12.008
20 https://doi.org/10.1016/j.jjcc.2013.08.007
21 https://doi.org/10.1016/j.jjcc.2013.09.010
22 https://doi.org/10.1016/j.mayocp.2016.10.008
23 https://doi.org/10.1016/j.recesp.2010.12.004
24 https://doi.org/10.1016/j.respe.2014.11.003
25 https://doi.org/10.1093/europace/eus305
26 https://doi.org/10.1111/j.1468-1331.2011.03518.x
27 https://doi.org/10.1136/openhrt-2016-000573
28 https://doi.org/10.1159/000353670
29 https://doi.org/10.1160/th12-08-0539
30 https://doi.org/10.1160/th15-07-0612
31 https://doi.org/10.1161/circimaging.110.959403
32 https://doi.org/10.1161/circulationaha.113.002250
33 https://doi.org/10.1161/circulationaha.114.014145
34 https://doi.org/10.1161/circulationaha.114.015134
35 https://doi.org/10.1161/circulationaha.115.017534
36 https://doi.org/10.1177/0003319711427391
37 https://doi.org/10.11909/j.issn.1671-5411.2016.08.004
38 https://doi.org/10.1253/circj.cj-14-0038
39 https://doi.org/10.20452/pamw.2709
40 https://doi.org/10.2147/clep.s47385
41 https://doi.org/10.3904/kjim.2016.31.1.73
42 schema:datePublished 2017-12
43 schema:datePublishedReg 2017-12-01
44 schema:description The presence of acute myocardial infarction (AMI) confers a poor prognosis in atrial fibrillation (AF), associated with increased mortality dramatically. This study aimed to evaluate the predictive value of CHADS<sub>2</sub> and CHA<sub>2</sub>DS<sub>2</sub>-VASc scores for AMI in patients with AF. This retrospective study enrolled 5140 consecutive nonvalvular AF patients, 300 patients with AMI and 4840 patients without AMI. We identified the optimal cut-off values of the CHADS<sub>2</sub> and CHA<sub>2</sub>DS<sub>2</sub>-VASc scores each based on receiver operating characteristic curves to predict the risk of AMI. Both CHADS<sub>2</sub> score and CHA<sub>2</sub>DS<sub>2</sub>-VASc score were associated with an increased odds ratio of the prevalence of AMI in patients with AF, after adjustment for hyperlipidaemia, hyperuricemia, hyperthyroidism, hypothyroidism and obstructive sleep apnea. The present results showed that the area under the curve (AUC) for CHADS<sub>2</sub> score was 0.787 with a similar accuracy of the CHA<sub>2</sub>DS<sub>2</sub>-VASc score (AUC 0.750) in predicting "high-risk" AF patients who developed AMI. However, the predictive accuracy of the two clinical-based risk scores was fair. The CHA<sub>2</sub>DS<sub>2</sub>-VASc score has fair predictive value for identifying high-risk patients with AF and is not significantly superior to CHADS<sub>2</sub> in predicting patients who develop AMI.
45 schema:genre research_article
46 schema:inLanguage en
47 schema:isAccessibleForFree true
48 schema:isPartOf Naafd17e45d0444dea0620b5d7318119a
49 Nccd24354f8c74de197e648fa57edc439
50 sg:journal.1045337
51 schema:name Predictive value of CHADS2 and CHA2DS2-VASc scores for acute myocardial infarction in patients with atrial fibrillation
52 schema:pagination 4730
53 schema:productId N25f361fa446c439693611b50d0bbd93f
54 N29e53a75cc0c4d7e8ccec95986be6fff
55 N2c6bcd7d15de4ed48a243e4b86459a9c
56 N85c033e3a36a4fb695b31a50a9038aa9
57 N8d8ebe44f290498ab070978697f26a15
58 schema:sameAs https://app.dimensions.ai/details/publication/pub.1090351659
59 https://doi.org/10.1038/s41598-017-04604-w
60 schema:sdDatePublished 2019-04-10T22:27
61 schema:sdLicense https://scigraph.springernature.com/explorer/license/
62 schema:sdPublisher N7f9ceb6e7f804ab5b12da724a5a7530e
63 schema:url https://www.nature.com/articles/s41598-017-04604-w
64 sgo:license sg:explorer/license/
65 sgo:sdDataset articles
66 rdf:type schema:ScholarlyArticle
67 N25f361fa446c439693611b50d0bbd93f schema:name readcube_id
68 schema:value dbe936fee5b2c43e06f3363b7a5adb3be5f3819e3fd380d1d59c154129c8d739
69 rdf:type schema:PropertyValue
70 N29e53a75cc0c4d7e8ccec95986be6fff schema:name nlm_unique_id
71 schema:value 101563288
72 rdf:type schema:PropertyValue
73 N2c6bcd7d15de4ed48a243e4b86459a9c schema:name doi
74 schema:value 10.1038/s41598-017-04604-w
75 rdf:type schema:PropertyValue
76 N41117ff4125f466ab71a16a0943882ec rdf:first sg:person.01171657162.36
77 rdf:rest Nca714da1ea1c4e56aecafe47a429c1b5
78 N7f9ceb6e7f804ab5b12da724a5a7530e schema:name Springer Nature - SN SciGraph project
79 rdf:type schema:Organization
80 N85c033e3a36a4fb695b31a50a9038aa9 schema:name pubmed_id
81 schema:value 28680116
82 rdf:type schema:PropertyValue
83 N8d8ebe44f290498ab070978697f26a15 schema:name dimensions_id
84 schema:value pub.1090351659
85 rdf:type schema:PropertyValue
86 Naafd17e45d0444dea0620b5d7318119a schema:volumeNumber 7
87 rdf:type schema:PublicationVolume
88 Naef697026aa14db2b732e8e08356807c rdf:first sg:person.01013436434.68
89 rdf:rest N41117ff4125f466ab71a16a0943882ec
90 Nca714da1ea1c4e56aecafe47a429c1b5 rdf:first sg:person.01100466600.44
91 rdf:rest rdf:nil
92 Nccd24354f8c74de197e648fa57edc439 schema:issueNumber 1
93 rdf:type schema:PublicationIssue
94 Neda5e34ae6c2448ba8341199614543a2 rdf:first sg:person.0745323234.48
95 rdf:rest Naef697026aa14db2b732e8e08356807c
96 anzsrc-for:11 schema:inDefinedTermSet anzsrc-for:
97 schema:name Medical and Health Sciences
98 rdf:type schema:DefinedTerm
99 anzsrc-for:1102 schema:inDefinedTermSet anzsrc-for:
100 schema:name Cardiorespiratory Medicine and Haematology
101 rdf:type schema:DefinedTerm
102 sg:journal.1045337 schema:issn 2045-2322
103 schema:name Scientific Reports
104 rdf:type schema:Periodical
105 sg:person.01013436434.68 schema:affiliation https://www.grid.ac/institutes/grid.452207.6
106 schema:familyName Han
107 schema:givenName Bing
108 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01013436434.68
109 rdf:type schema:Person
110 sg:person.01100466600.44 schema:affiliation https://www.grid.ac/institutes/grid.413389.4
111 schema:familyName Zong
112 schema:givenName Zhenkun
113 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01100466600.44
114 rdf:type schema:Person
115 sg:person.01171657162.36 schema:affiliation https://www.grid.ac/institutes/grid.452207.6
116 schema:familyName Fu
117 schema:givenName Qiang
118 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01171657162.36
119 rdf:type schema:Person
120 sg:person.0745323234.48 schema:affiliation https://www.grid.ac/institutes/grid.452207.6
121 schema:familyName Pang
122 schema:givenName Hui
123 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0745323234.48
124 rdf:type schema:Person
125 sg:pub.10.1007/s11999-016-4717-3 schema:sameAs https://app.dimensions.ai/details/publication/pub.1039274356
126 https://doi.org/10.1007/s11999-016-4717-3
127 rdf:type schema:CreativeWork
128 sg:pub.10.1038/srep39323 schema:sameAs https://app.dimensions.ai/details/publication/pub.1027106804
129 https://doi.org/10.1038/srep39323
130 rdf:type schema:CreativeWork
131 https://doi.org/10.1001/jama.2015.10725 schema:sameAs https://app.dimensions.ai/details/publication/pub.1021110878
132 rdf:type schema:CreativeWork
133 https://doi.org/10.1001/jamainternmed.2013.11912 schema:sameAs https://app.dimensions.ai/details/publication/pub.1053438245
134 rdf:type schema:CreativeWork
135 https://doi.org/10.1002/sim.4085 schema:sameAs https://app.dimensions.ai/details/publication/pub.1037258459
136 rdf:type schema:CreativeWork
137 https://doi.org/10.1007/s11999-016-4717-3 schema:sameAs https://app.dimensions.ai/details/publication/pub.1039274356
138 rdf:type schema:CreativeWork
139 https://doi.org/10.1016/j.amjcard.2014.09.005 schema:sameAs https://app.dimensions.ai/details/publication/pub.1034013598
140 rdf:type schema:CreativeWork
141 https://doi.org/10.1016/j.amjcard.2016.07.063 schema:sameAs https://app.dimensions.ai/details/publication/pub.1024784124
142 rdf:type schema:CreativeWork
143 https://doi.org/10.1016/j.amjcard.2016.11.033 schema:sameAs https://app.dimensions.ai/details/publication/pub.1040877334
144 rdf:type schema:CreativeWork
145 https://doi.org/10.1016/j.amjcard.2016.11.035 schema:sameAs https://app.dimensions.ai/details/publication/pub.1032094791
146 rdf:type schema:CreativeWork
147 https://doi.org/10.1016/j.hrthm.2014.08.003 schema:sameAs https://app.dimensions.ai/details/publication/pub.1019487688
148 rdf:type schema:CreativeWork
149 https://doi.org/10.1016/j.ijcard.2014.10.039 schema:sameAs https://app.dimensions.ai/details/publication/pub.1004857749
150 rdf:type schema:CreativeWork
151 https://doi.org/10.1016/j.ijcard.2015.08.054 schema:sameAs https://app.dimensions.ai/details/publication/pub.1038560450
152 rdf:type schema:CreativeWork
153 https://doi.org/10.1016/j.ijcard.2016.11.114 schema:sameAs https://app.dimensions.ai/details/publication/pub.1030389919
154 rdf:type schema:CreativeWork
155 https://doi.org/10.1016/j.jacc.2014.03.022 schema:sameAs https://app.dimensions.ai/details/publication/pub.1037324913
156 rdf:type schema:CreativeWork
157 https://doi.org/10.1016/j.jfma.2015.12.008 schema:sameAs https://app.dimensions.ai/details/publication/pub.1029047260
158 rdf:type schema:CreativeWork
159 https://doi.org/10.1016/j.jjcc.2013.08.007 schema:sameAs https://app.dimensions.ai/details/publication/pub.1002273989
160 rdf:type schema:CreativeWork
161 https://doi.org/10.1016/j.jjcc.2013.09.010 schema:sameAs https://app.dimensions.ai/details/publication/pub.1029874782
162 rdf:type schema:CreativeWork
163 https://doi.org/10.1016/j.mayocp.2016.10.008 schema:sameAs https://app.dimensions.ai/details/publication/pub.1084095255
164 rdf:type schema:CreativeWork
165 https://doi.org/10.1016/j.recesp.2010.12.004 schema:sameAs https://app.dimensions.ai/details/publication/pub.1008342409
166 rdf:type schema:CreativeWork
167 https://doi.org/10.1016/j.respe.2014.11.003 schema:sameAs https://app.dimensions.ai/details/publication/pub.1003047190
168 rdf:type schema:CreativeWork
169 https://doi.org/10.1093/europace/eus305 schema:sameAs https://app.dimensions.ai/details/publication/pub.1030385418
170 rdf:type schema:CreativeWork
171 https://doi.org/10.1111/j.1468-1331.2011.03518.x schema:sameAs https://app.dimensions.ai/details/publication/pub.1010726404
172 rdf:type schema:CreativeWork
173 https://doi.org/10.1136/openhrt-2016-000573 schema:sameAs https://app.dimensions.ai/details/publication/pub.1079402099
174 rdf:type schema:CreativeWork
175 https://doi.org/10.1159/000353670 schema:sameAs https://app.dimensions.ai/details/publication/pub.1006797297
176 rdf:type schema:CreativeWork
177 https://doi.org/10.1160/th12-08-0539 schema:sameAs https://app.dimensions.ai/details/publication/pub.1063293141
178 rdf:type schema:CreativeWork
179 https://doi.org/10.1160/th15-07-0612 schema:sameAs https://app.dimensions.ai/details/publication/pub.1063294127
180 rdf:type schema:CreativeWork
181 https://doi.org/10.1161/circimaging.110.959403 schema:sameAs https://app.dimensions.ai/details/publication/pub.1006230314
182 rdf:type schema:CreativeWork
183 https://doi.org/10.1161/circulationaha.113.002250 schema:sameAs https://app.dimensions.ai/details/publication/pub.1010604349
184 rdf:type schema:CreativeWork
185 https://doi.org/10.1161/circulationaha.114.014145 schema:sameAs https://app.dimensions.ai/details/publication/pub.1023406789
186 rdf:type schema:CreativeWork
187 https://doi.org/10.1161/circulationaha.114.015134 schema:sameAs https://app.dimensions.ai/details/publication/pub.1037550571
188 rdf:type schema:CreativeWork
189 https://doi.org/10.1161/circulationaha.115.017534 schema:sameAs https://app.dimensions.ai/details/publication/pub.1014369901
190 rdf:type schema:CreativeWork
191 https://doi.org/10.1177/0003319711427391 schema:sameAs https://app.dimensions.ai/details/publication/pub.1039235778
192 rdf:type schema:CreativeWork
193 https://doi.org/10.11909/j.issn.1671-5411.2016.08.004 schema:sameAs https://app.dimensions.ai/details/publication/pub.1079346675
194 rdf:type schema:CreativeWork
195 https://doi.org/10.1253/circj.cj-14-0038 schema:sameAs https://app.dimensions.ai/details/publication/pub.1049988760
196 rdf:type schema:CreativeWork
197 https://doi.org/10.20452/pamw.2709 schema:sameAs https://app.dimensions.ai/details/publication/pub.1079038769
198 rdf:type schema:CreativeWork
199 https://doi.org/10.2147/clep.s47385 schema:sameAs https://app.dimensions.ai/details/publication/pub.1037288120
200 rdf:type schema:CreativeWork
201 https://doi.org/10.3904/kjim.2016.31.1.73 schema:sameAs https://app.dimensions.ai/details/publication/pub.1071557064
202 rdf:type schema:CreativeWork
203 https://www.grid.ac/institutes/grid.413389.4 schema:alternateName Affiliated Hospital of Xuzhou Medical College
204 schema:name Department of Neurosurgery, Affiliated Hospital of Xuzhou Medical College, Xuzhou, Jiangsu, China
205 rdf:type schema:Organization
206 https://www.grid.ac/institutes/grid.452207.6 schema:alternateName Xuzhou Central Hospital
207 schema:name Department of Cardiology, Xuzhou Central Hospital, Xuzhou Clinical School of Xuzhou Medical College, Affiliated Xuzhou Hospital of Medical College of Southeast University, Xuzhou, Jiangsu, China
208 rdf:type schema:Organization
 




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


...