Utility of the HAS-BLED score for risk stratification of patients with acute coronary syndrome. View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2019-04-10

AUTHORS

Diego Castini, Simone Persampieri, Ludovico Sabatelli, Massimo Erba, Giulia Ferrante, Federica Valli, Marco Centola, Stefano Carugo

ABSTRACT

HAS-BLED score was developed for bleeding prediction in patients with atrial fibrillation (AF). Recently, it was also used in patients undergoing percutaneous coronary interventions (PCI). This study analyzes the HAS-BLED predictivity for bleedings and mortality in patients with acute coronary syndromes (ACS) without AF, and evaluates the utilization of alternative criteria for renal dysfunction. The study population was composed of 704 patients with ACS. Six-hundred and eleven patients completed the follow-up. The HAS-BLED score was calculated both using the original definition of renal dysfunction, both using three alternative eGFR thresholds (< 30, < 60 and ≤ 90 ml/min/1.73 mq). In-hospital and post-discharge bleedings and mortality were recorded, and calibration and discrimination of the various risk models were evaluated using the Hosmer-Lemeshow test and the C-statistic. In-hospital bleedings were 4.7% and mortality was 2.7%. Post-discharge bleedings were 3.1% and mortality was 4.4%. Regarding bleeding events and in-hospital mortality, the HAS-BLED original risk model demonstrated a moderate-to-good discriminative performance (C-statistics from 0.65 to 0.76). No significant differences were found in predictive accuracy when applying alternative definitions of renal dysfunction based on eGFR, with the exception of post-discharge mortality, for which HAS-BLED model assuming an eGFR value < 60 ml/min/1.73 mq showed a discriminative performance significantly higher in comparison to the other risk models (C-statistic 0.71 versus 0.64-0.66). In conclusion, in our ACS population, the HAS-BLED risk score showed a fairly good predictive accuracy regarding in-hospital and follow-up bleeding events and in-hospital mortality. The use of renal dysfunction alternative criteria based on eGFR values resulted in out-of hospital mortality predictive accuracy enhancement. More... »

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/s00380-019-01405-1

DOI

http://dx.doi.org/10.1007/s00380-019-01405-1

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1113328984

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/30969359


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/2008/1117", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Public Health and Health Services", 
        "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": "Ospedale San Paolo", 
          "id": "https://www.grid.ac/institutes/grid.415093.a", 
          "name": [
            "Division of Cardiology, San Paolo Hospital, Via A. di Rudin\u00ec 8, 20142, Milan, Italy. diegocarlo.castini@fastwebnet.it."
          ], 
          "type": "Organization"
        }, 
        "familyName": "Castini", 
        "givenName": "Diego", 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Ospedale San Paolo", 
          "id": "https://www.grid.ac/institutes/grid.415093.a", 
          "name": [
            "Division of Cardiology, San Paolo Hospital, Via A. di Rudin\u00ec 8, 20142, Milan, Italy."
          ], 
          "type": "Organization"
        }, 
        "familyName": "Persampieri", 
        "givenName": "Simone", 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Ospedale San Paolo", 
          "id": "https://www.grid.ac/institutes/grid.415093.a", 
          "name": [
            "Division of Cardiology, San Paolo Hospital, Via A. di Rudin\u00ec 8, 20142, Milan, Italy."
          ], 
          "type": "Organization"
        }, 
        "familyName": "Sabatelli", 
        "givenName": "Ludovico", 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Ospedale San Paolo", 
          "id": "https://www.grid.ac/institutes/grid.415093.a", 
          "name": [
            "Division of Cardiology, San Paolo Hospital, Via A. di Rudin\u00ec 8, 20142, Milan, Italy."
          ], 
          "type": "Organization"
        }, 
        "familyName": "Erba", 
        "givenName": "Massimo", 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Ospedale San Paolo", 
          "id": "https://www.grid.ac/institutes/grid.415093.a", 
          "name": [
            "Division of Cardiology, San Paolo Hospital, Via A. di Rudin\u00ec 8, 20142, Milan, Italy."
          ], 
          "type": "Organization"
        }, 
        "familyName": "Ferrante", 
        "givenName": "Giulia", 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Ospedale San Paolo", 
          "id": "https://www.grid.ac/institutes/grid.415093.a", 
          "name": [
            "Division of Cardiology, San Paolo Hospital, Via A. di Rudin\u00ec 8, 20142, Milan, Italy."
          ], 
          "type": "Organization"
        }, 
        "familyName": "Valli", 
        "givenName": "Federica", 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Ospedale San Paolo", 
          "id": "https://www.grid.ac/institutes/grid.415093.a", 
          "name": [
            "Division of Cardiology, San Paolo Hospital, Via A. di Rudin\u00ec 8, 20142, Milan, Italy."
          ], 
          "type": "Organization"
        }, 
        "familyName": "Centola", 
        "givenName": "Marco", 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Ospedale San Paolo", 
          "id": "https://www.grid.ac/institutes/grid.415093.a", 
          "name": [
            "Division of Cardiology, San Paolo Hospital, Via A. di Rudin\u00ec 8, 20142, Milan, Italy."
          ], 
          "type": "Organization"
        }, 
        "familyName": "Carugo", 
        "givenName": "Stefano", 
        "type": "Person"
      }
    ], 
    "citation": [
      {
        "id": "https://doi.org/10.1016/j.jacc.2016.02.064", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1002332702"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.jacc.2016.02.064", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1002332702"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1093/ndt/gft209", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1003593939"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1093/ndt/gft209", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1003593939"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.amjcard.2014.03.038", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1004140370"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1378/chest.10-0134", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1005759865"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.jcin.2012.07.011", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1007181033"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.jcin.2012.07.011", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1007181033"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.ahj.2008.08.031", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1007385211"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.jjcc.2014.06.011", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1010042662"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.jjcc.2014.06.011", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1010042662"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.jjcc.2016.02.005", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1010537375"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.amjcard.2005.06.056", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1010777963"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.amjcard.2005.06.056", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1010777963"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1097/crd.0b013e31815685fa", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1014677383"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1097/crd.0b013e31815685fa", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1014677383"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/s0735-1097(02)01745-x", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1016598771"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1136/heart.89.9.1003", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1018531110"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1002/ccd.26588", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1019027838"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1002/ccd.26588", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1019027838"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.jacc.2009.09.076", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1020758560"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.amjcard.2015.05.015", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1023237910"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1161/circep.111.967000", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1024823563"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1161/circep.111.967000", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1024823563"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1161/circulationaha.110.009449", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1025074445"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.thromres.2015.08.015", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1025940826"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.ijcard.2015.07.064", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1025956415"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.jacc.2016.02.056", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1026352336"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1093/eurheartj/ehp499", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1035063548"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1093/eurheartj/ehr204", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1035258191"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.jacc.2011.07.021", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1038378249"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.jacc.2011.07.021", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1038378249"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1056/nejmoa1500857", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1041478315"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.jacc.2007.10.040", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1042103235"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.jcin.2010.08.015", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1042255502"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.jcin.2010.08.015", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1042255502"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.jacc.2007.02.027", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1043018713"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.amjcard.2010.12.009", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1044233910"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.thromres.2014.01.007", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1044298505"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.thromres.2014.01.007", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1044298505"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1161/circulationaha.111.060871", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1045623683"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1161/circulationaha.111.060871", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1045623683"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1161/circulationaha.108.828541", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1052020248"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1161/circulationaha.106.612812", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1052919720"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1097/aln.0b013e318287b72c", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1053629860"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1097/aln.0b013e318287b72c", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1053629860"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1093/eurheartj/ehw525", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1059577257"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.2307/2531595", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1069977037"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.4244/eijv11i1a11", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1072398509"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.4244/eijv8i6a105", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1072399932"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.7326/0003-4819-150-9-200905050-00006", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1073710774"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1161/jaha.115.002524", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1079190843"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1093/oxfordjournals.aje.a113284", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1082126726"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/s0140-6736(17)30397-5", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1084043504"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/s0140-6736(17)30397-5", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1084043504"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.amjcard.2018.08.025", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1106875080"
        ], 
        "type": "CreativeWork"
      }
    ], 
    "datePublished": "2019-04-10", 
    "datePublishedReg": "2019-04-10", 
    "description": "HAS-BLED score was developed for bleeding prediction in patients with atrial fibrillation (AF). Recently, it was also used in patients undergoing percutaneous coronary interventions (PCI). This study analyzes the HAS-BLED predictivity for bleedings and mortality in patients with acute coronary syndromes (ACS) without AF, and evaluates the utilization of alternative criteria for renal dysfunction. The study population was composed of 704 patients with ACS. Six-hundred and eleven patients completed the follow-up. The HAS-BLED score was calculated both using the original definition of renal dysfunction, both using three alternative eGFR thresholds (<\u200930,\u2009<\u200960 and\u2009\u2264\u200990\u00a0ml/min/1.73 mq). In-hospital and post-discharge bleedings and mortality were recorded, and calibration and discrimination of the various risk models were evaluated using the Hosmer-Lemeshow test and the C-statistic. In-hospital bleedings were 4.7% and mortality was 2.7%. Post-discharge bleedings were 3.1% and mortality was 4.4%. Regarding bleeding events and in-hospital mortality, the HAS-BLED original risk model demonstrated a moderate-to-good discriminative performance (C-statistics from 0.65 to 0.76). No significant differences were found in predictive accuracy when applying alternative definitions of renal dysfunction based on eGFR, with the exception of post-discharge mortality, for which HAS-BLED model assuming an eGFR value\u2009<\u200960\u00a0ml/min/1.73 mq showed a discriminative performance significantly higher in comparison to the other risk models (C-statistic 0.71 versus 0.64-0.66). In conclusion, in our ACS population, the HAS-BLED risk score showed a fairly good predictive accuracy regarding in-hospital and follow-up bleeding events and in-hospital mortality. The use of renal dysfunction alternative criteria based on eGFR values resulted in out-of hospital mortality predictive accuracy enhancement.", 
    "genre": "research_article", 
    "id": "sg:pub.10.1007/s00380-019-01405-1", 
    "inLanguage": [
      "en"
    ], 
    "isAccessibleForFree": false, 
    "isPartOf": [
      {
        "id": "sg:journal.1095887", 
        "issn": [
          "0910-8327", 
          "1615-2573"
        ], 
        "name": "Heart and Vessels", 
        "type": "Periodical"
      }
    ], 
    "name": "Utility of the HAS-BLED score for risk stratification of patients with acute coronary syndrome.", 
    "productId": [
      {
        "name": "doi", 
        "type": "PropertyValue", 
        "value": [
          "10.1007/s00380-019-01405-1"
        ]
      }, 
      {
        "name": "dimensions_id", 
        "type": "PropertyValue", 
        "value": [
          "pub.1113328984"
        ]
      }, 
      {
        "name": "nlm_unique_id", 
        "type": "PropertyValue", 
        "value": [
          "8511258"
        ]
      }, 
      {
        "name": "pubmed_id", 
        "type": "PropertyValue", 
        "value": [
          "30969359"
        ]
      }
    ], 
    "sameAs": [
      "https://doi.org/10.1007/s00380-019-01405-1", 
      "https://app.dimensions.ai/details/publication/pub.1113328984"
    ], 
    "sdDataset": "articles", 
    "sdDatePublished": "2019-04-15T09:15", 
    "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/v90/0000000376_0000000376/records_56167_00000006.jsonl", 
    "type": "ScholarlyArticle", 
    "url": "http://link.springer.com/10.1007/s00380-019-01405-1"
  }
]
 

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/s00380-019-01405-1'

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/s00380-019-01405-1'

Turtle is a human-readable linked data format.

curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1007/s00380-019-01405-1'

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

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1007/s00380-019-01405-1'


 

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

226 TRIPLES      20 PREDICATES      66 URIs      16 LITERALS      6 BLANK NODES

Subject Predicate Object
1 sg:pub.10.1007/s00380-019-01405-1 schema:about anzsrc-for:11
2 anzsrc-for:1117
3 schema:author N7c4c4cf0047b4b50b03f11124369c58f
4 schema:citation https://doi.org/10.1002/ccd.26588
5 https://doi.org/10.1016/j.ahj.2008.08.031
6 https://doi.org/10.1016/j.amjcard.2005.06.056
7 https://doi.org/10.1016/j.amjcard.2010.12.009
8 https://doi.org/10.1016/j.amjcard.2014.03.038
9 https://doi.org/10.1016/j.amjcard.2015.05.015
10 https://doi.org/10.1016/j.amjcard.2018.08.025
11 https://doi.org/10.1016/j.ijcard.2015.07.064
12 https://doi.org/10.1016/j.jacc.2007.02.027
13 https://doi.org/10.1016/j.jacc.2007.10.040
14 https://doi.org/10.1016/j.jacc.2009.09.076
15 https://doi.org/10.1016/j.jacc.2011.07.021
16 https://doi.org/10.1016/j.jacc.2016.02.056
17 https://doi.org/10.1016/j.jacc.2016.02.064
18 https://doi.org/10.1016/j.jcin.2010.08.015
19 https://doi.org/10.1016/j.jcin.2012.07.011
20 https://doi.org/10.1016/j.jjcc.2014.06.011
21 https://doi.org/10.1016/j.jjcc.2016.02.005
22 https://doi.org/10.1016/j.thromres.2014.01.007
23 https://doi.org/10.1016/j.thromres.2015.08.015
24 https://doi.org/10.1016/s0140-6736(17)30397-5
25 https://doi.org/10.1016/s0735-1097(02)01745-x
26 https://doi.org/10.1056/nejmoa1500857
27 https://doi.org/10.1093/eurheartj/ehp499
28 https://doi.org/10.1093/eurheartj/ehr204
29 https://doi.org/10.1093/eurheartj/ehw525
30 https://doi.org/10.1093/ndt/gft209
31 https://doi.org/10.1093/oxfordjournals.aje.a113284
32 https://doi.org/10.1097/aln.0b013e318287b72c
33 https://doi.org/10.1097/crd.0b013e31815685fa
34 https://doi.org/10.1136/heart.89.9.1003
35 https://doi.org/10.1161/circep.111.967000
36 https://doi.org/10.1161/circulationaha.106.612812
37 https://doi.org/10.1161/circulationaha.108.828541
38 https://doi.org/10.1161/circulationaha.110.009449
39 https://doi.org/10.1161/circulationaha.111.060871
40 https://doi.org/10.1161/jaha.115.002524
41 https://doi.org/10.1378/chest.10-0134
42 https://doi.org/10.2307/2531595
43 https://doi.org/10.4244/eijv11i1a11
44 https://doi.org/10.4244/eijv8i6a105
45 https://doi.org/10.7326/0003-4819-150-9-200905050-00006
46 schema:datePublished 2019-04-10
47 schema:datePublishedReg 2019-04-10
48 schema:description HAS-BLED score was developed for bleeding prediction in patients with atrial fibrillation (AF). Recently, it was also used in patients undergoing percutaneous coronary interventions (PCI). This study analyzes the HAS-BLED predictivity for bleedings and mortality in patients with acute coronary syndromes (ACS) without AF, and evaluates the utilization of alternative criteria for renal dysfunction. The study population was composed of 704 patients with ACS. Six-hundred and eleven patients completed the follow-up. The HAS-BLED score was calculated both using the original definition of renal dysfunction, both using three alternative eGFR thresholds (< 30, < 60 and ≤ 90 ml/min/1.73 mq). In-hospital and post-discharge bleedings and mortality were recorded, and calibration and discrimination of the various risk models were evaluated using the Hosmer-Lemeshow test and the C-statistic. In-hospital bleedings were 4.7% and mortality was 2.7%. Post-discharge bleedings were 3.1% and mortality was 4.4%. Regarding bleeding events and in-hospital mortality, the HAS-BLED original risk model demonstrated a moderate-to-good discriminative performance (C-statistics from 0.65 to 0.76). No significant differences were found in predictive accuracy when applying alternative definitions of renal dysfunction based on eGFR, with the exception of post-discharge mortality, for which HAS-BLED model assuming an eGFR value < 60 ml/min/1.73 mq showed a discriminative performance significantly higher in comparison to the other risk models (C-statistic 0.71 versus 0.64-0.66). In conclusion, in our ACS population, the HAS-BLED risk score showed a fairly good predictive accuracy regarding in-hospital and follow-up bleeding events and in-hospital mortality. The use of renal dysfunction alternative criteria based on eGFR values resulted in out-of hospital mortality predictive accuracy enhancement.
49 schema:genre research_article
50 schema:inLanguage en
51 schema:isAccessibleForFree false
52 schema:isPartOf sg:journal.1095887
53 schema:name Utility of the HAS-BLED score for risk stratification of patients with acute coronary syndrome.
54 schema:productId N28dff565541e4fc2a8091be97283434d
55 N7e226009d1ff409ab7fea912758454c8
56 Nab2eab8956bd4e05a0dcc50ae85104d5
57 Nf22760f17f8240f7a7610e43de65fa97
58 schema:sameAs https://app.dimensions.ai/details/publication/pub.1113328984
59 https://doi.org/10.1007/s00380-019-01405-1
60 schema:sdDatePublished 2019-04-15T09:15
61 schema:sdLicense https://scigraph.springernature.com/explorer/license/
62 schema:sdPublisher Nf47f41228d544c5a86cd9f2f963a4a83
63 schema:url http://link.springer.com/10.1007/s00380-019-01405-1
64 sgo:license sg:explorer/license/
65 sgo:sdDataset articles
66 rdf:type schema:ScholarlyArticle
67 N2110eef79da54c828ba8709a755abf03 rdf:first Na117cc6985384dd799de4ab383dfdd5e
68 rdf:rest N54bf9806e51347a98f3484c1886f49b2
69 N27d0def1450f4d4faa27bfee85343317 schema:affiliation https://www.grid.ac/institutes/grid.415093.a
70 schema:familyName Sabatelli
71 schema:givenName Ludovico
72 rdf:type schema:Person
73 N28dff565541e4fc2a8091be97283434d schema:name doi
74 schema:value 10.1007/s00380-019-01405-1
75 rdf:type schema:PropertyValue
76 N3300283b5bdd4fb8ba8ed58d5c15c75b rdf:first Nca32cf7926ce4208ad5ae6e7f3ff55c8
77 rdf:rest N5b7b5327026e4f8e9a886ab6405bd36a
78 N3ccdd8bbe8f24b76b3dfc3cd19ce51e3 rdf:first N7a54a989b8174174b966cb31ff135d9a
79 rdf:rest Nec9a68e7207c43d0b5f727059a970aed
80 N49f845e2763f4ccfb8f36540f6d83595 schema:affiliation https://www.grid.ac/institutes/grid.415093.a
81 schema:familyName Valli
82 schema:givenName Federica
83 rdf:type schema:Person
84 N4d3b2687e63243f2a0f989f8f1492497 rdf:first Nb40a36b429f744fc840f99d0117e1908
85 rdf:rest N3ccdd8bbe8f24b76b3dfc3cd19ce51e3
86 N50e73011a4db47b290bfee1b2daba5c3 schema:affiliation https://www.grid.ac/institutes/grid.415093.a
87 schema:familyName Carugo
88 schema:givenName Stefano
89 rdf:type schema:Person
90 N54bf9806e51347a98f3484c1886f49b2 rdf:first N50e73011a4db47b290bfee1b2daba5c3
91 rdf:rest rdf:nil
92 N579f10b1c91245d1b1d438ac46e02435 schema:affiliation https://www.grid.ac/institutes/grid.415093.a
93 schema:familyName Castini
94 schema:givenName Diego
95 rdf:type schema:Person
96 N5b7b5327026e4f8e9a886ab6405bd36a rdf:first N27d0def1450f4d4faa27bfee85343317
97 rdf:rest N4d3b2687e63243f2a0f989f8f1492497
98 N7a54a989b8174174b966cb31ff135d9a schema:affiliation https://www.grid.ac/institutes/grid.415093.a
99 schema:familyName Ferrante
100 schema:givenName Giulia
101 rdf:type schema:Person
102 N7c4c4cf0047b4b50b03f11124369c58f rdf:first N579f10b1c91245d1b1d438ac46e02435
103 rdf:rest N3300283b5bdd4fb8ba8ed58d5c15c75b
104 N7e226009d1ff409ab7fea912758454c8 schema:name dimensions_id
105 schema:value pub.1113328984
106 rdf:type schema:PropertyValue
107 Na117cc6985384dd799de4ab383dfdd5e schema:affiliation https://www.grid.ac/institutes/grid.415093.a
108 schema:familyName Centola
109 schema:givenName Marco
110 rdf:type schema:Person
111 Nab2eab8956bd4e05a0dcc50ae85104d5 schema:name nlm_unique_id
112 schema:value 8511258
113 rdf:type schema:PropertyValue
114 Nb40a36b429f744fc840f99d0117e1908 schema:affiliation https://www.grid.ac/institutes/grid.415093.a
115 schema:familyName Erba
116 schema:givenName Massimo
117 rdf:type schema:Person
118 Nca32cf7926ce4208ad5ae6e7f3ff55c8 schema:affiliation https://www.grid.ac/institutes/grid.415093.a
119 schema:familyName Persampieri
120 schema:givenName Simone
121 rdf:type schema:Person
122 Nec9a68e7207c43d0b5f727059a970aed rdf:first N49f845e2763f4ccfb8f36540f6d83595
123 rdf:rest N2110eef79da54c828ba8709a755abf03
124 Nf22760f17f8240f7a7610e43de65fa97 schema:name pubmed_id
125 schema:value 30969359
126 rdf:type schema:PropertyValue
127 Nf47f41228d544c5a86cd9f2f963a4a83 schema:name Springer Nature - SN SciGraph project
128 rdf:type schema:Organization
129 anzsrc-for:11 schema:inDefinedTermSet anzsrc-for:
130 schema:name Medical and Health Sciences
131 rdf:type schema:DefinedTerm
132 anzsrc-for:1117 schema:inDefinedTermSet anzsrc-for:
133 schema:name Public Health and Health Services
134 rdf:type schema:DefinedTerm
135 sg:journal.1095887 schema:issn 0910-8327
136 1615-2573
137 schema:name Heart and Vessels
138 rdf:type schema:Periodical
139 https://doi.org/10.1002/ccd.26588 schema:sameAs https://app.dimensions.ai/details/publication/pub.1019027838
140 rdf:type schema:CreativeWork
141 https://doi.org/10.1016/j.ahj.2008.08.031 schema:sameAs https://app.dimensions.ai/details/publication/pub.1007385211
142 rdf:type schema:CreativeWork
143 https://doi.org/10.1016/j.amjcard.2005.06.056 schema:sameAs https://app.dimensions.ai/details/publication/pub.1010777963
144 rdf:type schema:CreativeWork
145 https://doi.org/10.1016/j.amjcard.2010.12.009 schema:sameAs https://app.dimensions.ai/details/publication/pub.1044233910
146 rdf:type schema:CreativeWork
147 https://doi.org/10.1016/j.amjcard.2014.03.038 schema:sameAs https://app.dimensions.ai/details/publication/pub.1004140370
148 rdf:type schema:CreativeWork
149 https://doi.org/10.1016/j.amjcard.2015.05.015 schema:sameAs https://app.dimensions.ai/details/publication/pub.1023237910
150 rdf:type schema:CreativeWork
151 https://doi.org/10.1016/j.amjcard.2018.08.025 schema:sameAs https://app.dimensions.ai/details/publication/pub.1106875080
152 rdf:type schema:CreativeWork
153 https://doi.org/10.1016/j.ijcard.2015.07.064 schema:sameAs https://app.dimensions.ai/details/publication/pub.1025956415
154 rdf:type schema:CreativeWork
155 https://doi.org/10.1016/j.jacc.2007.02.027 schema:sameAs https://app.dimensions.ai/details/publication/pub.1043018713
156 rdf:type schema:CreativeWork
157 https://doi.org/10.1016/j.jacc.2007.10.040 schema:sameAs https://app.dimensions.ai/details/publication/pub.1042103235
158 rdf:type schema:CreativeWork
159 https://doi.org/10.1016/j.jacc.2009.09.076 schema:sameAs https://app.dimensions.ai/details/publication/pub.1020758560
160 rdf:type schema:CreativeWork
161 https://doi.org/10.1016/j.jacc.2011.07.021 schema:sameAs https://app.dimensions.ai/details/publication/pub.1038378249
162 rdf:type schema:CreativeWork
163 https://doi.org/10.1016/j.jacc.2016.02.056 schema:sameAs https://app.dimensions.ai/details/publication/pub.1026352336
164 rdf:type schema:CreativeWork
165 https://doi.org/10.1016/j.jacc.2016.02.064 schema:sameAs https://app.dimensions.ai/details/publication/pub.1002332702
166 rdf:type schema:CreativeWork
167 https://doi.org/10.1016/j.jcin.2010.08.015 schema:sameAs https://app.dimensions.ai/details/publication/pub.1042255502
168 rdf:type schema:CreativeWork
169 https://doi.org/10.1016/j.jcin.2012.07.011 schema:sameAs https://app.dimensions.ai/details/publication/pub.1007181033
170 rdf:type schema:CreativeWork
171 https://doi.org/10.1016/j.jjcc.2014.06.011 schema:sameAs https://app.dimensions.ai/details/publication/pub.1010042662
172 rdf:type schema:CreativeWork
173 https://doi.org/10.1016/j.jjcc.2016.02.005 schema:sameAs https://app.dimensions.ai/details/publication/pub.1010537375
174 rdf:type schema:CreativeWork
175 https://doi.org/10.1016/j.thromres.2014.01.007 schema:sameAs https://app.dimensions.ai/details/publication/pub.1044298505
176 rdf:type schema:CreativeWork
177 https://doi.org/10.1016/j.thromres.2015.08.015 schema:sameAs https://app.dimensions.ai/details/publication/pub.1025940826
178 rdf:type schema:CreativeWork
179 https://doi.org/10.1016/s0140-6736(17)30397-5 schema:sameAs https://app.dimensions.ai/details/publication/pub.1084043504
180 rdf:type schema:CreativeWork
181 https://doi.org/10.1016/s0735-1097(02)01745-x schema:sameAs https://app.dimensions.ai/details/publication/pub.1016598771
182 rdf:type schema:CreativeWork
183 https://doi.org/10.1056/nejmoa1500857 schema:sameAs https://app.dimensions.ai/details/publication/pub.1041478315
184 rdf:type schema:CreativeWork
185 https://doi.org/10.1093/eurheartj/ehp499 schema:sameAs https://app.dimensions.ai/details/publication/pub.1035063548
186 rdf:type schema:CreativeWork
187 https://doi.org/10.1093/eurheartj/ehr204 schema:sameAs https://app.dimensions.ai/details/publication/pub.1035258191
188 rdf:type schema:CreativeWork
189 https://doi.org/10.1093/eurheartj/ehw525 schema:sameAs https://app.dimensions.ai/details/publication/pub.1059577257
190 rdf:type schema:CreativeWork
191 https://doi.org/10.1093/ndt/gft209 schema:sameAs https://app.dimensions.ai/details/publication/pub.1003593939
192 rdf:type schema:CreativeWork
193 https://doi.org/10.1093/oxfordjournals.aje.a113284 schema:sameAs https://app.dimensions.ai/details/publication/pub.1082126726
194 rdf:type schema:CreativeWork
195 https://doi.org/10.1097/aln.0b013e318287b72c schema:sameAs https://app.dimensions.ai/details/publication/pub.1053629860
196 rdf:type schema:CreativeWork
197 https://doi.org/10.1097/crd.0b013e31815685fa schema:sameAs https://app.dimensions.ai/details/publication/pub.1014677383
198 rdf:type schema:CreativeWork
199 https://doi.org/10.1136/heart.89.9.1003 schema:sameAs https://app.dimensions.ai/details/publication/pub.1018531110
200 rdf:type schema:CreativeWork
201 https://doi.org/10.1161/circep.111.967000 schema:sameAs https://app.dimensions.ai/details/publication/pub.1024823563
202 rdf:type schema:CreativeWork
203 https://doi.org/10.1161/circulationaha.106.612812 schema:sameAs https://app.dimensions.ai/details/publication/pub.1052919720
204 rdf:type schema:CreativeWork
205 https://doi.org/10.1161/circulationaha.108.828541 schema:sameAs https://app.dimensions.ai/details/publication/pub.1052020248
206 rdf:type schema:CreativeWork
207 https://doi.org/10.1161/circulationaha.110.009449 schema:sameAs https://app.dimensions.ai/details/publication/pub.1025074445
208 rdf:type schema:CreativeWork
209 https://doi.org/10.1161/circulationaha.111.060871 schema:sameAs https://app.dimensions.ai/details/publication/pub.1045623683
210 rdf:type schema:CreativeWork
211 https://doi.org/10.1161/jaha.115.002524 schema:sameAs https://app.dimensions.ai/details/publication/pub.1079190843
212 rdf:type schema:CreativeWork
213 https://doi.org/10.1378/chest.10-0134 schema:sameAs https://app.dimensions.ai/details/publication/pub.1005759865
214 rdf:type schema:CreativeWork
215 https://doi.org/10.2307/2531595 schema:sameAs https://app.dimensions.ai/details/publication/pub.1069977037
216 rdf:type schema:CreativeWork
217 https://doi.org/10.4244/eijv11i1a11 schema:sameAs https://app.dimensions.ai/details/publication/pub.1072398509
218 rdf:type schema:CreativeWork
219 https://doi.org/10.4244/eijv8i6a105 schema:sameAs https://app.dimensions.ai/details/publication/pub.1072399932
220 rdf:type schema:CreativeWork
221 https://doi.org/10.7326/0003-4819-150-9-200905050-00006 schema:sameAs https://app.dimensions.ai/details/publication/pub.1073710774
222 rdf:type schema:CreativeWork
223 https://www.grid.ac/institutes/grid.415093.a schema:alternateName Ospedale San Paolo
224 schema:name Division of Cardiology, San Paolo Hospital, Via A. di Rudinì 8, 20142, Milan, Italy.
225 Division of Cardiology, San Paolo Hospital, Via A. di Rudinì 8, 20142, Milan, Italy. diegocarlo.castini@fastwebnet.it.
226 rdf:type schema:Organization
 




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


...