Evaluation of Sudden Cardiac Arrest by Race/Ethnicity Among Residents of Ventura County, California, 2015-2020

Examining the association between ethnicity and out-of-hospital cardiac arrest interventions in Salt Lake City, Utah

Aims

Previous research has reported racial disparities in out-of-hospital cardiac arrest (OHCA) interventions, including bystander CPR and AED use. However, studies on other prehospital interventions are limited. The primary objective of this study was to investigate race/ethnic disparities in out-of-hospital cardiac arrest (OHCA) interventions: EMS response times, medication administration, and decisions for intra-arrest transport. The secondary objective was to evaluate differences in the provision of Bystander CPR (CPR) and application of AED.

Methods

We retrospectively analyzed data from the Salt Lake City Fire Department (2010-2023). We included adults 18 years or older with EMS-treated OHCA. Race/ethnicity was categorized as White people, Asian people, Black people, Hispanic people, and others. We employed multivariable regression analysis to evaluate the association between race/ethnicity and the outcomes of interest.

Results

Unadjusted analyses revealed no significant differences across ethnic groups in EMS response, medication administration, bystander CPR, or intra-arrest transport decisions. However, significant ethnic disparities were observed in Automated External Defibrillator (AED) utilization, Black people having the lowest rate (6.5%) and Asian people the highest (21.8%). The adjusted analysis found no significant association between race/ethnicity and all OHCA intervention measures, nor between race/ethnicity and survival outcomes.

Conclusions

Our multivariable analysis found no statistically significant association between race/ethnicity and EMS response time, epinephrine administration, antiarrhythmic medication use, bystander CPR, AED intervention, or intra-arrest transport. These results imply regional variations in ethnic disparities in OHCA may not be consistent across all areas, warranting further research into disparities in other regions and additional influential factors like neighborhood conditions and socioeconomic status.

Differences in Out-of-Hospital Cardiac Arrest Outcomes Among 5 Racial/Ethnic Groups

OBJECTIVE

Out-of-hospital cardiac arrest (OHCA) is a major health problem and one of the leading causes of death in adults older than 40. Multiple prior studies have demonstrated survival disparities based on race/ethnicity, but most of these focus on a single racial/ethnic group. This study evaluated OHCA variables and outcomes among on 5 racial/ethnic groups.

METHODS

This is a retrospective review of data for adult patients in the Cardiac Arrest Registry to Enhance Survival (CARES) from 3 racially diverse urban counties in the San Francisco Bay Area from May 2009 to October 2021. Stratifying by 5 racial/ethnic groups, we evaluated patient survival outcomes based on patient demographics, emergency medical services response location, cardiac arrest characteristics, and hospital interventions. Adjusted risk ratios were calculated for survival to hospital discharge, controlling for sex, age, response locations, median income of response location, arrest witness, shockable rhythm, and bystander cardiopulmonary resuscitation as well as clustering by census tract.

RESULTS

There were 10,757 patient entries analyzed: 42% White, 24% Black, 18% Asian, 9.3% Hispanic, 6.0% Pacific Islander, 0.7% American Indian/Alaska Native, and 0.1% multiple races selected; however, only the first 5 racial/ethnic groups had sufficient numbers for comparison. The adjusted risk ratio for survival to hospital discharge was lower among the 4 racial/ethnic groups compared with the White reference group: Black (0.79, p = 0.003), Asian (0.78 p = 0.004), Hispanic (0.79, p = 0.018), and Pacific Islander (0.78, p = 0.041) groups. The risk difference for positive neurologic outcome was also lower among all 4 racial/ethnic groups compared with the White reference group.

CONCLUSIONS

The Black, Asian, Hispanic, and Pacific Islander groups were less likely to survive to hospital discharge from OHCA when compared with the White reference group. No variables were associated with decreased survival across any of these 4 groups.

Risk Prediction for Sudden Cardiac Death in the General Population: A Systematic Review and Meta-Analysis

Objective: Identification of SCD risk is important in the general population from a public health perspective. The objective is to summarize and appraise the available prediction models for the risk of SCD among the general population. Methods: Data were obtained searching six electronic databases and reporting prediction models of SCD risk in the general population. Studies with duplicate cohorts and missing information were excluded from the meta-analysis. Results: Out of 8,407 studies identified, fifteen studies were included in the systematic review, while five studies were included in the meta-analysis. The Cox proportional hazards model was used in thirteen studies (96.67%). Study locations were limited to Europe and the United States. Our pooled meta-analyses included four predictors: diabetes mellitus (ES = 2.69, 95%CI: 1.93, 3.76), QRS duration (ES = 1.16, 95%CI: 1.06, 1.26), spatial QRS-T angle (ES = 1.46, 95%CI: 1.27, 1.69) and factional shortening (ES = 1.37, 95%CI: 1.15, 1.64). Conclusion: Risk prediction model may be useful as an adjunct for risk stratification strategies for SCD in the general population. Further studies among people except for white participants and more accessible factors are necessary to explore.

Dynamic electrocardiogram changes are a novel risk marker for sudden cardiac death

BACKGROUND AND AIMS

Electrocardiogram (ECG) abnormalities have been evaluated as static risk markers for sudden cardiac death (SCD), but the potential importance of dynamic ECG remodelling has not been investigated. In this study, the nature and prevalence of dynamic ECG remodelling were studied among individuals who eventually suffered SCD.

METHODS

The study population was drawn from two prospective community-based SCD studies in Oregon (2002, discovery cohort) and California, USA (2015, validation cohort). For this present sub-study, 231 discovery cases (2015-17) and 203 validation cases (2015-21) with ≥2 archived pre-SCD ECGs were ascertained and were matched to 234 discovery and 203 validation controls based on age, sex, and duration between the ECGs. Dynamic ECG remodelling was measured as progression of a previously validated cumulative six-variable ECG electrical risk score.

RESULTS

Oregon SCD cases displayed greater electrical risk score increase over time vs. controls [+1.06 (95% confidence interval +0.89 to +1.24) vs. -0.05 (-0.21 to +0.11); P < .001]. These findings were successfully replicated in California [+0.87 (+0.7 to +1.04) vs. -0.11 (-0.27 to 0.05); P < .001]. In multivariable models, abnormal dynamic ECG remodelling improved SCD prediction over baseline ECG, demographics, and clinical SCD risk factors in both Oregon [area under the receiver operating characteristic curve 0.770 (95% confidence interval 0.727-0.812) increased to area under the receiver operating characteristic curve 0.869 (95% confidence interval 0.837-0.902)] and California cohorts.

CONCLUSIONS

Dynamic ECG remodelling improved SCD risk prediction beyond clinical factors combined with the static ECG, with successful validation in a geographically distinct population. These findings introduce a novel concept of SCD dynamic risk and warrant further detailed investigation.

Racial and ethnic disparities in bystander resuscitation for out-of-hospital cardiac arrests

INTRODUCTION

Bystander-provided cardiopulmonary resuscitation (CRP) influences the survival rates of out-of-hospital cardiac arrests (OHCAs). Disparities on bystander resuscitation measures between Black, Hispanic, Asians and Non-Hispanic White OHCAs is unclear. Examining racial and ethnic differences in bystander resuscitations is essential to better target interventions.

METHODS

15,542 witnessed OHCAs were identified between April 1, 2011, and June 30, 2015 using the Resuscitation Outcomes Consortium Epidemiologic Registry 3, a multi-center, controlled trial about OHCAs in the United States and Canada. Multivariable logistic regression model was used to analyze the differences in bystander resuscitation (bystander CRP [B-CPR], CPR plus ventilation, automated external defibrillators/defibrillator application [B-AED/D], or delivery of shocks) and clinical outcomes (death at the scene or en route, return of spontaneous circulation upon first arrival at the emergency department [ROSC-ED], survival until ED discharge [S-ED], survival until hospital discharge [S-HOS], and favorable neurological outcome at discharge) between Black, Hispanic, or Asian victims and Non-Hispanic White victims.

RESULTS

Compared to OHCA victims in Non-Hispanic Whites, Black, Hispanic, and Asians were less likely to receive B-CPR (adjusted OR: 0.79; 95 % CI: 0.63-0.99), and B-AED/D (adjusted OR: 0.80; 95 % CI: 0.65-0.98) in public locations. And, Black, Hispanic, and Asian OHCAs were less likely to receive bystander resuscitation in street/highway locations and public buildings, and less likely to have better clinical outcomes, including ROSC-ED, S-ED and S-HOS.

CONCLUSION

Black, Hispanic and Asian victims with witnessed OHCAs are less likely to receive bystander resuscitation and more likely to get worse outcomes than Non-Hispanic White victims.

An ECG-based artificial intelligence model for assessment of sudden cardiac death risk

BACKGROUND

Conventional ECG-based algorithms could contribute to sudden cardiac death (SCD) risk stratification but demonstrate moderate predictive capabilities. Deep learning (DL) models use the entire digital signal and could potentially improve predictive power. We aimed to train and validate a 12 lead ECG-based DL algorithm for SCD risk assessment.

METHODS

Out-of-hospital SCD cases were prospectively ascertained in the Portland, Oregon, metro area. A total of 1,827 pre- cardiac arrest 12 lead ECGs from 1,796 SCD cases were retrospectively collected and analyzed to develop an ECG-based DL model. External validation was performed in 714 ECGs from 714 SCD cases from Ventura County, CA. Two separate control group samples were obtained from 1342 ECGs taken from 1325 individuals of which at least 50% had established coronary artery disease. The DL model was compared with a previously validated conventional 6 variable ECG risk model.

RESULTS

The DL model achieves an AUROC of 0.889 (95% CI 0.861-0.917) for the detection of SCD cases vs. controls in the internal held-out test dataset, and is successfully validated in external SCD cases with an AUROC of 0.820 (0.794-0.847). The DL model performs significantly better than the conventional ECG model that achieves an AUROC of 0.712 (0.668-0.756) in the internal and 0.743 (0.711-0.775) in the external cohort.

CONCLUSIONS

An ECG-based DL model distinguishes SCD cases from controls with improved accuracy and performs better than a conventional ECG risk model. Further detailed investigation is warranted to evaluate how the DL model could contribute to improved SCD risk stratification.

Artificial Intelligence Model Predicts Sudden Cardiac Arrest Manifesting With Pulseless Electric Activity Versus Ventricular Fibrillation

BACKGROUND

There is no specific treatment for sudden cardiac arrest (SCA) manifesting as pulseless electric activity (PEA) and survival rates are low; unlike ventricular fibrillation (VF), which is treatable by defibrillation. Development of novel treatments requires fundamental clinical studies, but access to the true initial rhythm has been a limiting factor.

METHODS

Using demographics and detailed clinical variables, we trained and tested an AI model (extreme gradient boosting) to differentiate PEA-SCA versus VF-SCA in a novel setting that provided the true initial rhythm. A subgroup of SCAs are witnessed by emergency medical services personnel, and because the response time is zero, the true SCA initial rhythm is recorded. The internal cohort consisted of 421 emergency medical services-witnessed out-of-hospital SCAs with PEA or VF as the initial rhythm in the Portland, Oregon metropolitan area. External validation was performed in 220 emergency medical services-witnessed SCAs from Ventura, CA.

RESULTS

In the internal cohort, the artificial intelligence model achieved an area under the receiver operating characteristic curve of 0.68 (95% CI, 0.61-0.76). Model performance was similar in the external cohort, achieving an area under the receiver operating characteristic curve of 0.72 (95% CI, 0.59-0.84). Anemia, older age, increased weight, and dyspnea as a warning symptom were the most important features of PEA-SCA; younger age, chest pain as a warning symptom and established coronary artery disease were important features associated with VF.

CONCLUSIONS

The artificial intelligence model identified novel features of PEA-SCA, differentiated from VF-SCA and was successfully replicated in an external cohort. These findings enhance the mechanistic understanding of PEA-SCA with potential implications for developing novel management strategies.

SMART System in the Assessment of Exercise Tolerance in Adults

Health-oriented physical activity should meet two key criteria: safety and an optimal level of exercise. The system of monitoring and rationalization of training (SMART) was designed to meet them. SMART integrates a custom-configured inertial measurement unit (IMU) and a sensor with real-time heart rate measurement (HR) using a proprietary computer application. SMART was used to evaluate the safety and exercise load with 115 study participants: 51 women (44.35%) and 64 men (55.65%) aged 19 to 65 years. The exercise test was the 6MWT test. In 35% of the participants, the mean HR exceeded the recognized safe limit of HR 75% max. Ongoing monitoring of HR allows for optimal exercise and its safety. Step count data were collected from the SMART system. The average step length was calculated by dividing the distance by the number of steps. The aim of the present study was to assess the risk of excessive cardiovascular stress during the 6MWT test using the SMART system.

Predicting Risk of Cardiac Arrest in Young Asian Americans: Insights from an Artificial Neural Network Analysis of the Nationwide Cohort

We used the Artificial Neural Network (ANN) model to identify predictors of Sudden Cardiac Arrest (SCA) in a national cohort of young Asian patients in the United States. The National Inpatient Sample (2019) was used to identify young Asians (18-44-year-old) who were hospitalized with SCA. The neural network's predicted criteria for SCA were selected. After eliminating missing data, young Asians (n = 65,413) were randomly divided into training (n = 45,094) and testing (n = 19347) groups. Training data (70%) was used to calibrate ANN while testing data (30%) was utilized to assess the algorithm's accuracy. To determine ANN's performance in predicting SCA, we compared the frequency of incorrect prediction between training and testing data and measured the area under the Receiver Operating Curve (AUC). The 2019 young Asian cohort had 327,065 admissions (median age 32 years; 84.2% female), with SCA accounting for 0.21%. The exact rate of error in predictions vs. tests was shown by training data (0.2% vs 0.2%). In descending order, the normalized importance of predictors to accurately predict SCA in young adults included prior history of cardiac arrest, sex, age, diabetes, anxiety disorders, prior coronary artery bypass grafting, hypertension, congenital heart disease, income, peripheral vascular disease, and cancer. The AUC was 0.821, indicating an excellent ANN model for SCA prediction. Our ANN models performed excellently in revealing the order of important predictors of SCA in young Asian American patients. These findings could have a considerable impact on clinical practice to develop risk prediction models to improve the survival outcome in high-risk patients.

Risk Factors for Sudden Cardiac Arrest Among Hispanic or Latino Adults in Southern California: Ventura PRESTO and HCHS/SOL

Background Out-of-hospital sudden cardiac arrest (SCA) is a leading cause of mortality, making prevention of SCA a public health priority. No studies have evaluated predictors of SCA risk among Hispanic or Latino individuals in the United States. Methods and Results In this case-control study, adult SCA cases ages 18-85 (n=1,468) were ascertained in the ongoing Ventura Prediction of Sudden Death in Multi-Ethnic Communities (PRESTO) study (2015-2021) in Ventura County, California. Control subjects were selected from 3033 Hispanic or Latino participants who completed Visit 2 examinations (2014-2017) at the San Diego site of the HCHS/SOL (Hispanic Community Health Survey/Study of Latinos). We used logistic regression to evaluate the association of clinical factors with SCA. Among Hispanic or Latino SCA cases (n=295) and frequency-matched HCHS/SOL controls (n=590) (70.2% men with mean age 63.4 and 61.2 years, respectively), the following clinical variables were associated with SCA in models adjusted for age, sex, and other clinical variables: chronic kidney disease (odds ratio [OR], 7.3 [95% CI, 3.8-14.3]), heavy drinking (OR, 4.5 [95% CI, 2.3-9.0]), stroke (OR, 3.1 [95% CI, 1.2-8.0]), atrial fibrillation (OR, 3.7 [95% CI, 1.7-7.9]), coronary artery disease (OR, 2.9 [95% CI, 1.5-5.9]), heart failure (OR, 2.5 [95% CI, 1.2-5.1]), and diabetes (OR, 1.5 [95% CI, 1.0-2.3]). Conclusions In this first population-based study, to our knowledge, of SCA risk predictors among Hispanic or Latino adults, chronic kidney disease was the strongest risk factor for SCA, and established cardiovascular disease was also important. Early identification and management of chronic kidney disease may reduce SCA risk among Hispanic or Latino individuals, in addition to prevention and treatment of cardiovascular disease.

Comparison of Out-of-Hospital Cardiac Arrest Outcomes Between Asian and White Individuals in the United States

Background Disparities in bystander cardiopulmonary resuscitation (CPR) and survival have been reported for Black and Hispanic individuals with out-of-hospital cardiac arrest (OHCA). Whether Asian individuals have lower rates of bystander CPR and survival for OHCA, as compared with White individuals, remains unknown. Methods and Results Within the US-based CARES (Cardiac Arrest Registry to Enhance Survival), we identified 278 989 OHCAs in Asian and White individuals during 2013 to 2021. Using hierarchical Poisson logistic regression with emergency medical service agency modeled as a random effect and patient and OHCA characteristics as fixed effects, we compared rates of bystander CPR, survival to discharge, and favorable neurological survival between Asian and White individuals with OHCA. Overall, 14 835 (5.3%) OHCAs occurred in Asian individuals. Compared with White individuals with OHCA, Asian individuals were older (67.0±17.6 versus 62.8±16.9 years) and were less likely to have drug overdose as the cause of OHCA (1.3% versus 6.6%) and a shockable arrest rhythm (19.2% versus 22.4%). Layperson bystander CPR rates were similar between Asian and White individuals (42.6% versus 42.1%; adjusted relative risk for Asian individuals, 0.99 [95% CI, 0.97-1.02]; P=0.69). However, rates of survival to discharge were lower in Asian individuals with OHCA (8.2% versus 10.3%; adjusted relative risk 0.92 [0.86-0.98] P=0.006). Similarly, the rate of favorable neurological survival was lower for Asian individuals (6.5% versus 8.7%; adjusted relative risk, 0.85 [0.79-0.91]; P<0.001). Conclusions Despite similar rates of bystander CPR, Asian individuals with OHCA have lower survival rates than White individuals with OHCA. The reasons for the lower survival rate deserve further study to determine whether there are disparities in resuscitation care between Asian and White individuals with OHCA.

Sudden cardiac arrest during the COVID-19 pandemic: A two-year prospective evaluation in a North American community

BACKGROUND

Early during the coronavirus disease 2019 (COVID-19) pandemic, higher sudden cardiac arrest (SCA) incidence and lower survival rates were reported. However, ongoing effects on SCA during the evolving pandemic have not been evaluated.

OBJECTIVE

The purpose of this study was to assess the impact of COVID-19 on SCA during 2 years of the pandemic.

METHODS

In a prospective study of Ventura County, California (2020 population 843,843; 44.1% Hispanic), we compared SCA incidence and outcomes during the first 2 years of the COVID-19 pandemic to the prior 4 years.

RESULTS

Of 2222 out-of-hospital SCA cases identified, 907 occurred during the pandemic (March 2020 to February 2022) and 1315 occurred prepandemic (March 2016 to February 2020). Overall age-standardized annual SCA incidence increased from 39 per 100,000 (95% confidence [CI] 37-41) prepandemic to 54 per 100,000 (95% CI 50-57; P <.001) during the pandemic. Among Hispanics, incidence increased by 77%, from 38 per 100,000 (95% CI 34-43) to 68 per 100,000 (95% CI 60-76; P <.001). Among non-Hispanics, incidence increased by 26%, from 39 per 100,000 (95% CI 37-42; P <.001) to 50 per 100,000 (95% CI 46-54). SCA incidence rates closely tracked COVID-19 infection rates. During the pandemic, SCA survival was significantly reduced (15% to 10%; P <.001), and Hispanics were less likely than non-Hispanics to receive bystander cardiopulmonary resuscitation (45% vs 55%; P = .005) and to present with shockable rhythm (15% vs 24%; P = .003).

CONCLUSION

Overall SCA rates remained consistently higher and survival outcomes consistently lower, with exaggerated effects during COVID infection peaks. This longer evaluation uncovered higher increases in SCA incidence among Hispanics, with worse resuscitation profiles. Potential ethnicity-specific barriers to acute SCA care warrant urgent evaluation and intervention.

Determinants of survival in sudden cardiac arrest manifesting with pulseless electrical activity

OBJECTIVE

The proportion of sudden cardiac arrests (SCA) manifesting with pulseless electrical activity (PEA) has increased significantly, and the survival rate remains lower than ventricular fibrillation (VF). However, a subgroup of PEA-SCA cases does survive and may yield key predictors of improved outcomes when compared to non-survivors. We aimed to identify key predictors of survival from PEA-SCA.

METHODS

Our study sample is drawn from two ongoing community-based, prospective studies of out-of-hospital SCA: Oregon SUDS from the Portland, OR metro area (Pop. approx. 1 million; 2002-2017) and Ventura PRESTO from Ventura County, CA (Pop. approx. 850,000, 2015-2021). For the present sub-study, we included SCA cases with PEA as the presenting rhythm where emergency medical services (EMS) personnel attempted resuscitation.

RESULTS

We identified 1,704 PEA-SCA cases, of which 173 (10.2%) were survivors and 1,531 (89.8%) non-survivors. Patients whose PEA-SCA occurred in a healthcare unit (16.9%) or public location (18.1%) had higher survival than those whose PEA-SCA occurred at home (9.3%) or in a care facility (5.7%). Young age, witness status, PEA-SCA location and pre-existing COPD/asthma were independent predictors of survival. Among witnessed cases the survival rate was 10% even if EMS response time was >10 minutes.

CONCLUSIONS

Key determinants for survival from PEA-SCA were young age, witnessed status, public location and pre-existing COPD/asthma. Survival outcomes in witnessed PEA cases were better than expected, even with delayed EMS response.

A Systematic Literature Review of Hispanic Adults' Experiences With the Emergency Medical Services System in the United States Between 2000 and 2021

OBJECTIVE

This systematic literature review presents an overview of studies that assess the experiences of Hispanic adults with (1) activation of emergency medical services (EMS); (2) on-scene care provided by EMS personnel; (3) mode of transport (EMS vs. non-EMS) to an emergency department (ED); and (4) experiences with EMS before and during the COVID-19 pandemic.

METHODS

A bibliographic database search was conducted to identify relevant studies on Ovid MEDLINE (PubMed), Web of Science, EMBASE, and CINAHL. Quantitative, mixed methods, and qualitative studies published in English or Spanish were included if they discussed Hispanic adults' experiences with EMS in the US between January 1, 2000 and December 31, 2021. The Hawker and colleagues quality assessment instrument was used to evaluate the quality of studies.

RESULTS

Of the 43 included studies, 13 examined EMS activation, 13 assessed on-scene care, 22 discussed the mode of transport to an ED, and 4 described Hispanic adults' experiences with EMS during the COVID-19 pandemic. Hispanics were less likely to activate EMS (N=7), less likely to receive certain types of on-scene care (N=6), and less likely to use EMS as the mode of transport to an ED (N=13), compared with non-Hispanic Whites. During the early COVID-19 pandemic period (March to May 2020), EMS use decreased by 26.5% compared with the same months during the previous 4 years.

CONCLUSIONS

The contribution of this study is its attention to Hispanic adults' experiences with the different phases of the US EMS system.

Ethnic disparities in out-of-hospital cardiac arrest: A population-based cohort study among adult Danish immigrants

Background

Ethnicity might impact out-of-hospital cardiac arrest (OHCA) risk, but it has scarcely been studied in Europe. We aimed to assess whether ethnicity influenced the risk of OHCA of cardiac cause in Danish immigrants and its interplay with risk factors for OHCA and socioeconomic status.

Methods

This nationwide study included all immigrants between 18 and 80 years present in Denmark at some point between 2001 and 2020. Regions of origin were defined as Africa, Arabic countries, Asia, Eastern Europe, Latin America, and Western countries. OHCAs with presumed cardiac cause were identified from the Danish Cardiac Arrest Registry.

Findings

Overall, among 1,011,565 immigrants, a total of 1,801 (0.2%) OHCAs (median age 64 (Q1-Q3 53–72) years, 72% males) occurred. The age- and sex- standardized (reference: Western countries) incidence of OHCA (/1,00,000 person-years) was 34.6 (27.8–43.4) in African, 34.1 (30.4–38.4) in Arabic, 33.5 (29.3–38.2) in Asian, 35.6 (31.9–39.6) in Eastern European, and 16.2 (9.0–27.2) in Latin American immigrants. When selecting Western origin as a reference, and after adjusting on OHCA risk factors, Arabic (HR 1.18, 95%CI 1.04–1.35; P=0.01), Eastern European (HR 1.28, 95%CI 1.13–1.46; P<0.001), and African origin (HR 1.34, 95%CI 1.10–1.63; P<0.01) were associated with higher risk of OHCA, whereas Latin American origin (HR 0.58, 95%CI 0.35–0.0.96; P=0.03) was associated with lower risk of OHCA. Comparable results were observed when adjusting on education level and economic status.

Interpretation

This study emphasizes that ethnicity is associated with OHCA risk, even when considering traditional cardiac arrest risk factors.

Funding

R Garcia received a grant from the Fédération Française de Cardiologie for his post-doctoral fellowship and this work was supported by the Novo Nordisk Foundation Tandem Programme 2022 (grant# 31364).

Ethnicity-Specific Effects on Cardiac Arrest During the COVID-19 Pandemic: A Two-Year Prospective Evaluation in a North American Community

Background

Out-of-hospital sudden cardiac arrest (SCA) is a major public health problem with mortality >90%, and incidence has increased during the COVID-19 pandemic. Information regarding ethnicity-specific effects on SCA incidence and survival is lacking.

Methods

In a prospective, population-based study of Ventura County, CA residents (2020 Pop. 843,843; 44.1% Hispanic), we compared SCA incidence and outcomes during the first two years of the COVID-19 pandemic to the prior four years, overall and by ethnicity (Hispanic vs non-Hispanic).

Findings

Of 2,222 OHCA cases identified, 907 occurred during the pandemic (March 2020 - Feb 2022) and 1315 occurred pre-pandemic (March 2016 - Feb 2020). Overall age-standardized annual SCA incidence increased from 38.9/100,000 [95% CI 36.8-41.0] pre-pandemic to 53.8/100,00 [95% CI 50.3 - 57.3, p<0.001] during the pandemic. Among Hispanics, incidence increased by 77%, from 38.2/100,00 [95% CI 33.8-42.5] to 67.7/100,00 [95% CI 59.5- 75.8, p<0.001]. Among non-Hispanics, incidence increased by 26% from 39.4/100,000 [95% CI 36.9-41.9, p<0.001] to 49.8/100,00 [95% CI 45.8-53.8]. SCA incidence rates closely tracked COVID-19 infection rates. During the pandemic, SCA survival was significantly reduced (15.3% to 10.0%, p<0.001) and Hispanics were less likely than non-Hispanics to have bystander CPR (44.6% vs. 54.7%, p=0.005) and shockable rhythm (15.3% vs. 24.1%, p=0.003).

Interpretation

Hispanic residents experienced higher SCA rates during the pandemic with less favorable resuscitation profiles. These findings implicate potential ethnicity-specific barriers to acute care and represent an urgent call to action at the community and health-system levels.

Funding

National Heart Lung and Blood Institute Grants R01HL145675 and R01HL147358.

Artificial Intelligence-Augmented Propensity Score, Cost Effectiveness and Computational Ethical Analysis of Cardiac Arrest and Active Cancer with Novel Mortality Predictive Score

Background and objectives: Little is known about outcome improvements and disparities in cardiac arrest and active cancer. We performed the first known AI and propensity score (PS)-augmented clinical, cost-effectiveness, and computational ethical analysis of cardio-oncology cardiac arrests including left heart catheterization (LHC)-related mortality reduction and related disparities. Materials and methods: A nationally representative cohort analysis was performed for mortality and cost by active cancer using the largest United States all-payer inpatient dataset, the National Inpatient Sample, from 2016 to 2018, using deep learning and machine learning augmented propensity score-adjusted (ML-PS) multivariable regression which informed cost-effectiveness and ethical analyses. The Cardiac Arrest Cardio-Oncology Score (CACOS) was then created for the above population and validated. The results informed the computational ethical analysis to determine ethical and related policy recommendations. Results: Of the 101,521,656 hospitalizations, 6,656,883 (6.56%) suffered cardiac arrest of whom 61,300 (0.92%) had active cancer. Patients with versus without active cancer were significantly less likely to receive an inpatient LHC (7.42% versus 20.79%, p < 0.001). In ML-PS regression in active cancer, post-arrest LHC significantly reduced mortality (OR 0.18, 95%CI 0.14−0.24, p < 0.001) which PS matching confirmed by up to 42.87% (95%CI 35.56−50.18, p < 0.001). The CACOS model included the predictors of no inpatient LHC, PEA initial rhythm, metastatic malignancy, and high-risk malignancy (leukemia, pancreas, liver, biliary, and lung). Cost-benefit analysis indicated 292 racial minorities and $2.16 billion could be saved annually by reducing racial disparities in LHC. Ethical analysis indicated the convergent consensus across diverse belief systems that such disparities should be eliminated to optimize just and equitable outcomes. Conclusions: This AI-guided empirical and ethical analysis provides a novel demonstration of LHC mortality reductions in cardio-oncology cardiac arrest and related disparities, along with an innovative predictive model that can be integrated within the digital ecosystem of modern healthcare systems to improve equitable clinical and public health outcomes.

Prediction of sudden cardiac arrest in the general population: Review of traditional and emerging risk factors

Sudden cardiac death (SCD) is the most common and devastating outcome of sudden cardiac arrest (SCA), defined as an abrupt and unexpected cessation of cardiovascular function leading to circulatory collapse. The incidence of SCD is relatively infrequent for individuals in the general population, in the range of 0.03-0.10% per year. Yet, the absolute number of cases around the world is high due to the sheer size of the population at risk, making SCA/SCD a major global health issue. Based on conservative estimates, there are at least 2 million cases of SCA occurring worldwide on a yearly basis. As such, identification of risk factors associated with SCA in the general population is an important objective from a clinical and public health standpoint. This review will provide an in-depth discussion of established and emerging factors predictive of SCA/SCD in the general population beyond coronary artery disease and impaired left ventricular ejection fraction. Contemporary studies evaluating the association between age, sex, race, socioeconomic status and the emerging contribution of diabetes and obesity to SCD risk beyond their role as atherosclerotic risk factors will be reviewed. In addition, the role of biomarkers, particularly electrocardiographic ones, on SCA/SCD risk prediction in the general population will be discussed. Finally, the use of machine learning as a tool to facilitate SCA/SCD risk prediction will be examined.