CBS 2019
CBSMD教育中心
English

科学研究

科研文章

荐读文献

Universal Definition and Classification of Heart Failure: A Report of the Heart Failure Society of America, Heart Failure Association of the European Society of Cardiology, Japanese Heart Failure Society and Writing Committee of the Universal Definition of Heart Failure Clinical applications of machine learning in the diagnosis, classification, and prediction of heart failure Angiotensin–Neprilysin Inhibition in Heart Failure with Preserved Ejection Fraction Rationale and design of the GUIDE-IT study: Guiding Evidence Based Therapy Using Biomarker Intensified Treatment in Heart Failure From Subclinical Atherosclerosis to Plaque Progression and Acute Coronary Events Prevalence and clinical implications of valvular calcification on coronary computed tomography angiography Association of Abnormal Left Ventricular Functional Reserve With Outcome in Heart Failure With Preserved Ejection Fraction Percutaneous Atriotomy for Levoatrial–to–Coronary Sinus Shunting in Symptomatic Heart Failure: First-in-Human Experience The year in cardiology: heart failure: The year in cardiology 2019 Minimizing Permanent Pacemaker Following Repositionable Self-Expanding Transcatheter Aortic Valve Replacement

Clinical TrialJune 2018

JOURNAL:JACC Clin Electrophysiol. Article Link

Improving the Use of Primary Prevention Implantable Cardioverter-Defibrillators Therapy With Validated Patient-Centric Risk Estimates

WC Levy, AS Hellkamp, DB Mark et al. Keywords: heart failure; ICD; non-sudden death; prognosis; proportional risk; regression analysis; risk prediction model; sudden death

ABSTRACT


OBJECTIVES - The authors previously developed the Seattle Proportional Risk Model (SPRM) in systolic heart failure patients without implantable cardioverter-defibrillators (ICDs)to predict the proportion of deaths that were sudden. They subsequently validated the SPRM in 2 observational ICD data sets. The objectives in the present study were to determine whether this validated model could improve identification of clinically important variations in the expected magnitude of ICD survival benefit by using a pivotal randomized trial of primary prevention ICD therapy.


BACKGROUND - Recent data show that <50% of nominally eligible subjects receive guideline- recommended primary prevention ICDs.

METHODS - In the SCD-HeFT (Sudden Cardiac Death in Heart Failure Trial), a placebo-controlled ICD trial in 2,521 patients with an ejection fraction ≤35% and symptomatic heart failure, we tested the use of patient-level SPRM-predicted probability of sudden death (relative to that of non-sudden death) as a summary measurement of the potential for ICD benefit. A Cox proportional hazards model was used to estimate variations in the relationship between patient-level SPRM predictions and ICD benefit.

RESULTS - Relative to use of mortality predictions with the Seattle Heart Failure Model, the SPRM was much better at partitioning treatment benefit from ICD therapy (effect size was 2- to 3.6-fold larger for the ICD×SPRM interaction). ICD benefit varied significantly across SPRM-predicted risk quartiles: for all-cause mortality, a +10% increase with ICD therapy in the first quartile (highest risk of death, lowest proportion of sudden death) to a decrease of 66% in the fourth quartile (lowest risk of death, highest proportion of sudden death; p = 0.0013); for sudden death mortality, a 19% reduction in SPRM quartile 1 to 95% reduction in SPRM quartile 4 (p < 0.0001).

CONCLUSIONS - In symptomatic systolic heart failure patients with a Class I recommendation for primary prevention ICD therapy, the SPRM offers a useful patient-centric tool for guiding shared decision making.