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The Wait for High-Sensitivity Troponin Is Over—Proceed Cautiously Clinical Outcomes Following Intravascular Imaging-Guided Versus Coronary Angiography–Guided Percutaneous Coronary Intervention With Stent Implantation: A Systematic Review and Bayesian Network Meta-Analysis of 31 Studies and 17,882 Patients Impact of the US Food and Drug Administration–Approved Sex-Specific Cutoff Values for High-Sensitivity Cardiac Troponin T to Diagnose Myocardial Infarction Good response to tolvaptan shortens hospitalization in patients with congestive heart failure Cardiac Implantable Electronic Devices in Patients With Left Ventricular Assist Systems Revision: prognostic impact of baseline glucose levels in acute myocardial infarction complicated by cardiogenic shock-a substudy of the IABP-SHOCK II-trial Usefulness of longitudinal reconstructed optical coherence tomography images for predicting the need for the reverse wire technique during coronary bifurcation interventions Wearable Cardioverter-Defibrillator after Myocardial Infarction Can We Use the Intrinsic Left Ventricular Delay (QLV) to Optimize the Pacing Configuration for Cardiac Resynchronization Therapy With a Quadripolar Left Ventricular Lead? Use of Risk Assessment Tools to Guide Decision-Making in the Primary Prevention of Atherosclerotic Cardiovascular Disease A Special Report From the American Heart Association and American College of Cardiology

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.