TY - JOUR
T1 - Sudden cardiac arrest risk assessment
T2 - Population science and the individual risk mandate
AU - Myerburg, Robert J.
AU - Goldberger, Jeffrey J.
N1 - Funding Information:
have completed and submitted the ICMJE Form for Disclosure of Potential Conflicts of Interest. Dr Myerburg is chair of the data and safety monitoring board for the Vest Prevention of Early Sudden Death trial funded by Zoll Corporation and chaired the data and safety monitoring board for the former Vest Prevention of Early Sudden Death and Prediction of ICD Therapies Trial, which also received funding from Zoll in addition to National Heart, Lung, and Blood Institute; General Electric; and Medtronic. Dr Goldberger is director of the Path to Improved Risk Stratification, a not-for-profit think tank on risk stratification for sudden cardiac death that has received unrestricted educational grants from Boston Scientific, GE Healthcare, Gilead Sciences, Medtronic, and St Jude Medical. No other disclosures were reported.
Funding Information:
part by the American Heart Association. Dr Goldberger is director of the Path to Improved Risk Stratification, which has received grants 1R13HL132512-01 (2016) and 1R13HL123252-01 (2014) from the National Heart, Lung, and Blood Institute and unrestricted educational grants from Boston Scientific, GE Healthcare, Gilead Sciences, Medtronic, and St Jude Medical.
PY - 2017/6
Y1 - 2017/6
N2 - Importance: High-resolution stratification of risk of sudden cardiac arrest (SCA) in individual patients is a tool that is necessary for achieving effective and efficient application of data generated by population-based research. This concept is at the core of initiatives for merging cost effectiveness with maximized clinical efficiency and individual patient treatment. Observations: For this review, we analyzed data on sudden cardiac death and SCA available from population studies that included large longitudinal and cross-sectional databases, observational cohort studies, and randomized clinical trials. In the context of population science, we treated clinical trials as small, scientifically rigid population studies that generate outcomes focused on defined segments of the population. Application of probabilistic outcomes from these available sources to individual patients generally and patients at risk for SCA and sudden cardiac death in particular is limited by the diversity of the study population based on inclusion criteria and/or the absence of uniformly large effect sizes. Limited information is available on the requirements for defining small high-risk density subgroups that would lead to identification of individuals at a sufficiently high probability of SCA to have a significant effect on clinical decision making. Conclusions and Relevance: Synthesis of available population and clinical science data demonstrates the limitations for prediction and prevention of SCA and sudden cardiac death and provides justification for a research mandate for improving risk prediction at the level of individual patients. This leads to suggested approaches to new data generation and required research funding to address this large public health burden.
AB - Importance: High-resolution stratification of risk of sudden cardiac arrest (SCA) in individual patients is a tool that is necessary for achieving effective and efficient application of data generated by population-based research. This concept is at the core of initiatives for merging cost effectiveness with maximized clinical efficiency and individual patient treatment. Observations: For this review, we analyzed data on sudden cardiac death and SCA available from population studies that included large longitudinal and cross-sectional databases, observational cohort studies, and randomized clinical trials. In the context of population science, we treated clinical trials as small, scientifically rigid population studies that generate outcomes focused on defined segments of the population. Application of probabilistic outcomes from these available sources to individual patients generally and patients at risk for SCA and sudden cardiac death in particular is limited by the diversity of the study population based on inclusion criteria and/or the absence of uniformly large effect sizes. Limited information is available on the requirements for defining small high-risk density subgroups that would lead to identification of individuals at a sufficiently high probability of SCA to have a significant effect on clinical decision making. Conclusions and Relevance: Synthesis of available population and clinical science data demonstrates the limitations for prediction and prevention of SCA and sudden cardiac death and provides justification for a research mandate for improving risk prediction at the level of individual patients. This leads to suggested approaches to new data generation and required research funding to address this large public health burden.
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U2 - 10.1001/jamacardio.2017.0266
DO - 10.1001/jamacardio.2017.0266
M3 - Review article
C2 - 28329250
AN - SCOPUS:85031704930
VL - 2
SP - 689
EP - 694
JO - JAMA Cardiology
JF - JAMA Cardiology
SN - 2380-6583
IS - 6
ER -