Literature DB >> 22581736

Clinical prediction model for death prior to appropriate therapy in primary prevention implantable cardioverter defibrillator patients with ischaemic heart disease: the FADES risk score.

Johannes B van Rees1, C Jan Willem Borleffs, Guido H van Welsenes, Enno T van der Velde, Jeroen J Bax, Lieselot van Erven, Hein Putter, Johanna G van der Bom, Martin J Schalij.   

Abstract

OBJECTIVES: To construct a risk score out of baseline variables to estimate the risk of death without prior implantable cardioverter defibrillator (ICD) in primary prevention ICD patients with ischaemic heart disease.
DESIGN: Retrospective cohort study.
SETTING: Tertiary care facility in The Netherlands. PATIENTS: All patients with ischaemic heart disease who received an ICD for primary prevention of sudden cardiac death at the Leiden University Medical Center, Leiden, The Netherlands in the period 1996-2009. MAIN OUTCOME MEASURE: All-cause mortality without prior appropriate ICD therapy (anti-tachycardia pacing or shock).
RESULTS: 900 patients (87% men, mean age 64±10 years) were included in the analysis. During a median follow-up of 669 days (IQR 363-1322 days), 150 patients (17%) died and 191 (21%) patients received appropriate device therapy. 114 (13%) patients died without prior appropriate therapy. Stratification of the risk for death without prior appropriate therapy resulted in risk categorisation of patients as low, intermediate or high risk. NYHA ≥III, advanced age, diabetes mellitus, left ventricular ejection fraction ≤25% and a history of smoking were significant independent predictors of death without appropriate ICD therapy. 5-year cumulative incidence for death without prior appropriate therapy ranged from 10% (95% CI 6% to 16%) in low-risk patients to 41% (95% CI 33% to 51%) in high-risk patients.
CONCLUSIONS: The risk of death without prior appropriate ICD therapy can be predicted in primary prevention ICD patients with ischaemic heart disease, which facilitates patient-tailored risk estimation.

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Year:  2012        PMID: 22581736     DOI: 10.1136/heartjnl-2011-300632

Source DB:  PubMed          Journal:  Heart        ISSN: 1355-6037            Impact factor:   5.994


  17 in total

1.  Application and comparison of the FADES, MADIT, and SHFM-D risk models for risk stratification of prophylactic implantable cardioverter-defibrillator treatment.

Authors:  Aafke C van der Heijden; Johannes B van Rees; Wayne C Levy; Johanna G van der Bom; Suzanne C Cannegieter; Mihàly K de Bie; Lieselot van Erven; Martin J Schalij; C Jan Willem Borleffs
Journal:  Europace       Date:  2017-01       Impact factor: 5.214

2.  Protein biomarkers identify patients unlikely to benefit from primary prevention implantable cardioverter defibrillators: findings from the Prospective Observational Study of Implantable Cardioverter Defibrillators (PROSE-ICD).

Authors:  Alan Cheng; Yiyi Zhang; Elena Blasco-Colmenares; Darshan Dalal; Barbara Butcher; Sanaz Norgard; Zayd Eldadah; Kenneth A Ellenbogen; Timm Dickfeld; David D Spragg; Joseph E Marine; Eliseo Guallar; Gordon F Tomaselli
Journal:  Circ Arrhythm Electrophysiol       Date:  2014-10-01

Review 3.  Implantable cardioverter defibrillators in diabetics: efficacy and safety in patients at risk of sudden cardiac death.

Authors:  Muhammad Shahreyar; Vijayadershan Mupiddi; Indrajit Choudhuri; Jasbir Sra; Abdul Jamil Tajik; Arshad Jahangir
Journal:  Expert Rev Cardiovasc Ther       Date:  2015-06-22

4.  National Trends in the Use of Cardiac Resynchronization Therapy With or Without Implantable Cardioverter-Defibrillator.

Authors:  Charlotta Lindvall; Neal A Chatterjee; Yuchiao Chang; Betty Chernack; Vicki A Jackson; Jagmeet P Singh; Joshua P Metlay
Journal:  Circulation       Date:  2015-12-03       Impact factor: 29.690

Review 5.  Co-Morbidities and Cardiac Resynchronization Therapy: When Should They Modify Patient Selection?

Authors:  Martin H Ruwald
Journal:  J Atr Fibrillation       Date:  2015-06-30

6.  Increasing sex differences in the use of cardiac resynchronization therapy with or without implantable cardioverter-defibrillator.

Authors:  Neal A Chatterjee; Rasmus Borgquist; Yuchiao Chang; Jennifer Lewey; Vicki A Jackson; Jagmeet P Singh; Joshua P Metlay; Charlotta Lindvall
Journal:  Eur Heart J       Date:  2017-05-14       Impact factor: 29.983

7.  Characteristics and outcomes of diabetic patients with an implantable cardioverter defibrillator in a real world setting: results from the Israeli ICD registry.

Authors:  Hillel Steiner; Michael Geist; Ilan Goldenberg; Mahmoud Suleiman; Michael Glikson; Alexander Tenenbaum; Moshe Swissa; Enrique Z Fisman; Gregory Golovchiner; Boris Strasberg; Alon Barsheshet
Journal:  Cardiovasc Diabetol       Date:  2016-12-01       Impact factor: 9.951

8.  Implementation of guidelines for implantable cardioverter-defibrillator therapy in clinical practice: Which patients do benefit?

Authors:  S C Wijers; B Y M van der Kolk; A E Tuinenburg; P A F Doevendans; M A Vos; M Meine
Journal:  Neth Heart J       Date:  2013-06       Impact factor: 2.380

9.  Clinical Risk Stratification for Primary Prevention Implantable Cardioverter Defibrillators.

Authors:  Douglas S Lee; Judy Hardy; Raymond Yee; Jeffrey S Healey; David Birnie; Christopher S Simpson; Eugene Crystal; Iqwal Mangat; Kumaraswamy Nanthakumar; Xuesong Wang; Andrew D Krahn; Paul Dorian; Peter C Austin; Jack V Tu
Journal:  Circ Heart Fail       Date:  2015-07-29       Impact factor: 8.790

10.  Cost-Effectiveness Analysis of Iodine-123 Meta-Iodobenzylguanidine Imaging for Screening Heart Failure Patients Eligible for an Implantable Cardioverter Defibrillator in the USA.

Authors:  Ken O'Day; Wayne C Levy; Meridith Johnson; Arnold F Jacobson
Journal:  Appl Health Econ Health Policy       Date:  2016-06       Impact factor: 2.561

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