Show simple item record

dc.contributor.authorHuynh, Q
dc.contributor.authorNegishi, K
dc.contributor.authorDe Pasquale, CG
dc.contributor.authorHare, JL
dc.contributor.authorLeung, D
dc.contributor.authorStanton, T
dc.contributor.authorMarwick, TH
dc.date.accessioned2020-01-02T04:31:19Z
dc.date.available2020-01-02T04:31:19Z
dc.date.issued2018
dc.identifier.issn0002-9149
dc.identifier.doi10.1016/j.amjcard.2017.10.031
dc.identifier.urihttp://hdl.handle.net/10072/389990
dc.description.abstractExisting prediction algorithms for the identification of patients with heart failure (HF) at high risk of readmission or death after hospital discharge are only modestly effective. We sought to validate a recently developed predictive model of 30-day readmission or death in HF using an Australia-wide sample of patients. This study used data from 1,046 patients with HF at teaching hospitals in 5 Australian capital cities to validate a predictive model of 30-day readmission or death in HF. Besides standard clinical and administrative data, we collected data on individual sociodemographic and socioeconomic status, mental health (Patient Health Questionnaire [PHQ]-9 and Generalized Anxiety Disorder [GAD]-7 scale score), cognitive function (Montreal Cognitive Assessment [MoCA] score), and 2-dimensional echocardiograms. The original sample used to develop the predictive model and the validation sample had similar proportions of patients with an adverse event within 30 days (30% vs 29%, p = 0.35) and 90 days (52% vs 49%, p = 0.36). Applying the predicted risk score to the validation sample provided very good discriminatory power (C-statistic = 0.77) in the prediction of 30-day readmission or death. This discrimination was greater for predicting 30-day death (C-statistic = 0.85) than for predicting 30-day readmission (C-statistic = 0.73). There was a small difference in the performance of the predictive model among patients with either a left ventricular ejection fraction of <40% or a left ventricular ejection fraction of ≥40%, but an attenuation in discrimination when used to predict longer-term adverse outcomes. In conclusion, our findings confirm the generalizability of the predictive model that may be a powerful tool for targeting high-risk patients with HF for intensive management.
dc.description.peerreviewedYes
dc.languageeng
dc.publisherElsevier BV
dc.relation.ispartofpagefrom322
dc.relation.ispartofpageto329
dc.relation.ispartofissue3
dc.relation.ispartofjournalThe American Journal of Cardiology
dc.relation.ispartofvolume121
dc.subject.fieldofresearchCardiorespiratory Medicine and Haematology
dc.subject.fieldofresearchcode1102
dc.titleValidation of Predictive Score of 30-Day Hospital Readmission or Death in Patients With Heart Failure
dc.typeJournal article
dc.type.descriptionC1 - Articles
dcterms.bibliographicCitationHuynh, Q; Negishi, K; De Pasquale, CG; Hare, JL; Leung, D; Stanton, T; Marwick, TH, Validation of Predictive Score of 30-Day Hospital Readmission or Death in Patients With Heart Failure, The American Journal of Cardiology, 2018, 121 (3), pp. 322-329
dcterms.dateAccepted2017-10-13
dcterms.licensehttp://creativecommons.org/licenses/by-nc-nd/4.0/
dc.date.updated2020-01-02T04:26:55Z
dc.description.versionPost-print
gro.rights.copyright© 2018 Elsevier. Licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International Licence (http://creativecommons.org/licenses/by-nc-nd/4.0/) which permits unrestricted, non-commercial use, distribution and reproduction in any medium, providing that the work is properly cited.
gro.hasfulltextFull Text
gro.griffith.authorStanton, Tony
gro.griffith.authorHuynh, Quan


Files in this item

This item appears in the following Collection(s)

  • Journal articles
    Contains articles published by Griffith authors in scholarly journals.

Show simple item record