Literature DB >> 28329250

Sudden Cardiac Arrest Risk Assessment: Population Science and the Individual Risk Mandate.

Robert J Myerburg1, Jeffrey J Goldberger1.   

Abstract

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.

Entities:  

Mesh:

Year:  2017        PMID: 28329250     DOI: 10.1001/jamacardio.2017.0266

Source DB:  PubMed          Journal:  JAMA Cardiol            Impact factor:   14.676


  17 in total

1.  The additive role of echocardiography in the screening for sudden death.

Authors:  Leonardo Tamariz; Jeffrey J Goldberger; Ana Palacio; Gordon Chen; Elissa Dawkins; Emancia Forbes; Thiago Tajiri; Reyan Ghany
Journal:  Echocardiography       Date:  2019-02-03       Impact factor: 1.724

2.  Sudden Arrhythmic Death: What Is the Gold Standard?

Authors:  Neal A Chatterjee; Christine M Albert
Journal:  Circ Arrhythm Electrophysiol       Date:  2019-06-28

Review 3.  Cardiac and Vascular Causes of Syncope and Atherosclerosis.

Authors:  Rose Mary Ferreira Lisboa da Silva; Josep Brugada
Journal:  Curr Cardiol Rep       Date:  2022-08-01       Impact factor: 3.955

Review 4.  Psychological Distress After Sudden Cardiac Arrest and Its Impact on Recovery.

Authors:  Sachin Agarwal; Jeffrey L Birk; Sabine L Abukhadra; Danielle A Rojas; Talea M Cornelius; Maja Bergman; Bernard P Chang; Donald E Edmondson; Ian M Kronish
Journal:  Curr Cardiol Rep       Date:  2022-08-03       Impact factor: 3.955

5.  Usefulness of Single Nucleotide Polymorphisms as Predictors of Sudden Cardiac Death.

Authors:  Leonardo Tamariz; Javier Balda; Dennise Pareja; Ana Palacio; Robert J Myerburg; Douglas Conway; Lea Davis; Jeffrey J Goldberger
Journal:  Am J Cardiol       Date:  2019-03-20       Impact factor: 2.778

6.  Circulating miRNAs and Risk of Sudden Death in Patients With Coronary Heart Disease.

Authors:  Michael G Silverman; Ashish Yeri; M Vinayaga Moorthy; Fernando Camacho Garcia; Neal A Chatterjee; Charlotte S A Glinge; Jacob Tfelt-Hansen; Ane M Salvador; Alexander R Pico; Ravi Shah; Christine M Albert; Saumya Das
Journal:  JACC Clin Electrophysiol       Date:  2019-10-30

Review 7.  Sudden Cardiac Death (SCD) - risk stratification and prediction with molecular biomarkers.

Authors:  Junaida Osman; Shing Cheng Tan; Pey Yee Lee; Teck Yew Low; Rahman Jamal
Journal:  J Biomed Sci       Date:  2019-05-22       Impact factor: 12.771

8.  Improving Clinical Translation of Machine Learning Approaches Through Clinician-Tailored Visual Displays of Black Box Algorithms: Development and Validation.

Authors:  Shannon Wongvibulsin; Katherine C Wu; Scott L Zeger
Journal:  JMIR Med Inform       Date:  2020-06-09

Review 9.  Ethical aspects of sudden cardiac arrest research using observational data: a narrative review.

Authors:  Marieke A R Bak; Marieke T Blom; Hanno L Tan; Dick L Willems
Journal:  Crit Care       Date:  2018-09-13       Impact factor: 9.097

10.  Clinical risk prediction with random forests for survival, longitudinal, and multivariate (RF-SLAM) data analysis.

Authors:  Shannon Wongvibulsin; Katherine C Wu; Scott L Zeger
Journal:  BMC Med Res Methodol       Date:  2019-12-31       Impact factor: 4.615

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