Prediction of imminent sudden cardiac death based on warning signs - 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.