Prediction of imminent sudden cardiac death based on warning signs

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Sudden cardiac arrest (SCA), a sudden catastrophic loss of the pulse, affects >350,000 in the US annually. Most will suffer sudden cardiac death (SCD) within 10 minutes of presentation, yielding a mortality rate >90%. Based on our recent work, we have proposed a novel paradigm for SCD called “near-term prevention”. SCA is often not as sudden as one might expect. At least 50% of individuals will have warning symptoms at some time in the 4 weeks prior to SCD, but these can be non-specific, so are often not acted upon. The overall goal of this proposal is to refine the identification of the symptomatic individual at high-risk of SCD, during this 4-week window of opportunity. We propose that a simultaneous examination of symptoms, clinical factors and biomarkers may identify individuals at highest risk of imminent SCD, which could enable prediction and pre-emptive management, thereby preventing SCD. We are proposing to develop a comprehensive risk score from two population-based studies founded by the PI. The Portland, Oregon Sudden Unexpected Death Study (Oregon-SUDS, catchment area ≈ 1 million) is now in its 17th year and the Ventura, California PRESTO study (Prediction of Sudden Death in Multi-Ethnic Communities, catchment area ≈ 850,000) is in its 5th year. The resulting combined databank contains information on >7500 SCD cases and controls, with detailed clinical phenotyping and a biobank of plasma samples. From Oregon-SUDS, we recently reported that 51% (n=430) of 839 individuals who suffered SCD presented with at least one symptom within the 4 weeks prior to their lethal event. The main symptom was chest pain, but dyspnea, fatigue, syncope and palpitations were also recorded. Warning signs could represent an opportunity for near-term prediction of SCD. While these symptoms are common and may be non-specific for SCD, we hypothesize that a combination of specific symptoms and clinical profile could facilitate the identification of patients at high risk of impending SCA. In addition, the discovery of novel plasma biomarkers for SCD could have additional utility for risk stratification. We therefore hypothesize that biomarkers, when combined with specific symptoms and clinical profile, will maximize the likelihood of identifying symptomatic subjects at highest risk of SCD, allowing for early intervention. SCD remains a major public health problem with a critical need for novel prediction and prevention. Development of this user-friendly risk score for imminent SCD in those with warning symptoms would represent a practical and clinically meaningful advance for triage of patients for optimal care.