Marco Mathias

All Publications

• DYNAMIC RISK TRAJECTORIES FOR SUDDEN CARDIAC ARREST: THE ROLE OF RECURRENT CARDIOVASCULAR EVENTS Heart Rhythm Pope, M., Chugh, H., Truyen, T., Mathias, M., Evanado, A., Lin, H., Atar, D., Bosson, N., Reinier, K., Benjamin, E. J., Chugh, S. S. 2026

  View details for DOI 10.1016/j.hrthm.2026.03.147

• Dynamic Risk Trajectories for Sudden Cardiac Arrest: The Role of Recurrent Cardiovascular Events. medRxiv : the preprint server for health sciences Pope, M. K., Chugh, H., Truyen, T. T., Mathias, M., Uy-Evanado, A., Lin, H., Atar, D., Bosson, N., Reinier, K., Benjamin, E. J., Chugh, S. S. 2025

  Abstract

  Emerging evidence suggests that dynamic risk assessment may enhance sudden cardiac arrest (SCA) risk stratification. While cardiovascular events, including acute coronary syndrome (ACS) and heart failure (HF) hospitalization, are associated with increased SCA risk, the impact of recurrent events on subsequent SCA risk in a contemporary, real-world population is unknown. This study aimed to assess whether patients with a first-time ACS or HF hospitalization who experience a recurrent cardiovascular event have higher risk of SCA compared to those who do not.The Observational Study of Cardiac Arrest Risk (OSCAR) is a prospective cohort study with adjudicated SCA outcomes. In the current study, patients who survived a first ACS or HF hospitalization were categorized into index ACS or HF cohorts. Participants were followed for recurrent cardiovascular events and SCA. Associations between recurrent events and SCA were assessed using Cox models with recurrent event modeled as a time-dependent variable. Findings were validated in the Framingham Heart Study (FHS).In the OSCAR discovery cohort, 2946 patients experienced an index ACS event. The incidence rate of SCA was higher following a recurrent ACS event than without (3.70 vs 1.28 per 100 patient-years). Recurrent ACS event was associated with a significantly higher risk of SCA (adjusted HR 3.15, 95% CI 2.06-4.83, p<0.0001). A total of 6711 patients experienced an index HF hospitalization, and the incidence rate of SCA was higher following a recurrent HF event than without (1.35 vs 0.97 per 100 patient-years). Recurrent HF hospitalization was associated with a significantly higher risk of SCA (HR 1.81, 95% CI 1.46-2.26, p<0.0001).In the FHS validation cohorts a recurrent event during follow-up was associated with a significantly higher risk of SCA in the ACS cohort (HR 2.85, 95% CI 1.66-4.90, p=0.0002), but the association was not statistically significant in the HF cohort (HR 1.49, 95% CI 0.73-3.03, p=0.27).Recurrent ACS event was associated with more than threefold higher risk of SCA, and a recurrent HF hospitalization with 80% higher risk of SCA. These findings suggest that dynamic clinical trajectories of recurrent cardiovascular events may inform management and prevention of SCA.

  View details for DOI 10.1101/2025.11.13.25340202

  View details for PubMedID 41292644

  View details for PubMedCentralID PMC12642720

• Validation of a Novel Risk Prediction Score for Sudden Cardiac Death in the Framingham Heart Study. Circulation. Arrhythmia and electrophysiology Truyen, T. T., Lin, H., Mathias, M., Chugh, H., Reinier, K., Benjamin, E. J., Chugh, S. S. 2025; 18 (6): e013647

  Abstract

  We have previously reported a novel clinical risk score (risk prediction score for shockable sudden cardiac arrest [VFRisk]) for the prediction of shockable sudden cardiac arrest, discovered and validated in 2 US west coast communities. We hypothesized that VFRisk predicts sudden cardiac death (SCD) risk in the geographically distinct FHS (Framingham Heart Study).We performed a nested case-referents study in the FHS to test VFRisk. Cases were participants who experienced SCD among the original and offspring FHS cohorts. Referents were randomly selected from FHS participants frequency-matched (ratio of 1:3) to cases on age, sex, cohort, and exam. VFRisk was the sum of 12 risk factors, each multiplied by its respective points.Among 312 cases and 935 referents, mean ages were 69.5 and 69.7 years with 70.8% men in both groups. SCD cases had significantly higher prevalence of diabetes, heart failure, stroke, atrial fibrillation, and myocardial infarction compared with the referents group. The VFRisk score was validated with good discrimination (C-statistic, 0.71 [95% CI, 0.66-0.77]) for SCD. Cases had higher VFRisk scores than referents (3.8±2.8 versus 1.8±1.7; P<0.001). A 1-unit increase in VFRisk score was associated with a 48% increase in odds of SCD (odds ratio, 1.48 [95% CI, 1.34-1.64]). The highest VFRisk quartile had 7.8-fold higher odds of SCD than the lowest quartile.The VFRisk score successfully predicted SCD in the FHS. The differences in discrimination between the 2 studies could partially be explained by the inability to distinguish shockable versus nonshockable events in the FHS.

  View details for DOI 10.1161/CIRCEP.124.013647

  View details for PubMedID 40391444

  View details for PubMedCentralID PMC12173765

• Prediction of Imminent Sudden Cardiac Arrest Using a Combination of Warning Symptoms and Clinical Features. medRxiv : the preprint server for health sciences Reinier, K., Chugh, H., Sargsyan, A., Uy-Evanado, A., Nakamura, K., Heckard, E., Mathias, M., Grogan, T., Elashoff, D., Salvucci, A., Jui, J., Chugh, S. S. 2025

  Abstract

  At least 50% of individuals who suffer sudden cardiac arrest (SCA) experience warning symptoms before their SCA. We have previously reported chest pain and dyspnea as the most common and potentially predictive symptoms. Combining with clinical features could improve sensitivity and specificity for prediction of imminent SCA (ISCA).A combination of warning symptoms and clinical profiles can predict ISCA.From two community-based studies of SCA in Oregon and California, we conducted a case-control study. Cases (n=364) were survivors of SCA who had experienced warning symptoms, and control subjects (n=313) were individuals who notified emergency medical services (EMS) for similar symptoms but did not have SCA. Symptom data were obtained from interviews with study subjects and from EMS pre-hospital care records. We constructed classification and regression tree (CART) models for major symptom categories to identify clinical predictors of ISCA. We used the area under the receiver operating characteristic curve (AUC) and 5-fold cross-validation to assess model performance and stability.Heart failure (HF) and/or coronary artery disease (CAD) were predictors of ISCA and displayed important sex differences. For example, among individuals presenting with only chest pain, male sex, particularly males with HF, was an important predictor of ISCA (AUC = 0.813). Among individuals with only dyspnea, CAD and HF were important predictors (AUC = 0.745) with no sex differences identified. The 5-fold cross-validation produced consistent results.Combinations of warning symptoms and clinical features distinguished individuals with SCA from individuals without SCA with good accuracy (AUCs 0.728 - 0.813).

  View details for DOI 10.1101/2025.03.05.25323376

  View details for PubMedID 40236404

  View details for PubMedCentralID PMC11996586

• Observational study of sudden cardiac arrest risk (OSCAR): Rationale and design of an electronic health records cohort. International journal of cardiology. Heart & vasculature Reinier, K., Chugh, H. S., Uy-Evanado, A., Heckard, E., Mathias, M., Bosson, N., Calsavara, V. F., Slomka, P. J., Elashoff, D. A., Bui, A. A., Chugh, S. S. 2025; 56: 101614

  Abstract

  Out-of-hospital sudden cardiac arrest (SCA) is a major cause of mortality and improved risk prediction is needed. The Observational Study of Sudden Cardiac Arrest Risk (OSCAR) is an electronic health records (EHR)-based cohort study of patients receiving routine medical care in the Cedars-Sinai Health System (CSHS) in Los Angeles County, CA designed to evaluate predictors of SCA. This paper describes the rationale, objectives, and study design for the OSCAR cohort.The OSCAR cohort includes 379,833 Los Angeles County residents with at least one patient encounter at CSHS in each of two consecutive calendar years from 2016 to 2020. We obtained baseline cohort characteristics from the EHR from 2012 until the start of follow-up, including demographics, vital signs, clinical diagnoses, cardiac tests and imaging, procedures, laboratory results, and medications. Follow-up will continue until Dec. 31, 2025, with an expected median follow-up time of ∼ 7 years. The primary outcome is out-of-hospital SCA of likely cardiac etiology attended by Los Angeles County Emergency Medical Services (LAC-EMS). The secondary outcome is total mortality identified using California Department of Public Health - Vital Records death certificates. We will use conventional approaches (diagnosis code algorithms) and artificial intelligence (natural language processing, deep learning) to define patient phenotypes and biostatistical and machine learning approaches for analysis.The OSCAR cohort will provide a large, diverse dataset and adjudicated SCA outcomes to facilitate the derivation and testing of risk prediction models for incident SCA.

  View details for DOI 10.1016/j.ijcha.2025.101614

  View details for PubMedID 39897418

  View details for PubMedCentralID PMC11787554

• Genetic Causes of Sudden Cardiac Arrest in the Community. medRxiv : the preprint server for health sciences Kransdorf, E. P., Mathias, M., Nakamura, K., Tyrer, J., Pharaoh, P. D., Chugh, H., Reinier, K., Akdemir, Z., Boerwinkle, E., Yu, B., Chugh, S. S. 2024

  Abstract

  Annually 300,000 Americans experience sudden cardiac arrest (SCA). Studies in referral SCA cohorts have observed rare variants in genes associated with arrhythmia and cardiomyopathy. We sought to: (1) establish the population prevalence of rare disease-causing variants in a set of candidate genes and (2) confirm the association of disease-causing variants in these genes with SCA in two prospective population-based studies.SCA patients (n=3264) were accrued from the Oregon Sudden Unexpected Death Study and the PREdiction of Sudden death in mulTi-ethnic cOmmunities (PRESTO) study and compared to control patients (n=13713) from the Atherosclerosis Risk in Communities (ARIC) study. Whole genome sequencing was performed. Disease-causing (likely pathogenic or pathogenic) variants in candidate genes associated with arrhythmia/cardiomyopathy were identified using updated American College of Medical Genetics and Genomics criteria. Gene- collapsing case-control analysis was performed using the conditional logistic regression-sequence kernel association test.We identified 300 disease-causing variants, the majority of which were in cardiomyopathy genes (71%). There were 136 patients (4.2%) in the SCA group and 351 patients (2.6%) in the control group with one or more disease-causing variants (OR 1.66, 95% confidence interval 1.33-2.07, p<0.001). We identified 13 genes associated with an increased risk of SCA, nine associated with cardiomyopathy ( BAG3, DSC2, DSG2, FLNC, LMNA, MYBPC3, TNNI3, TNNT2, TTN ) and four with arrhythmia ( CACNA1C, CASQ2, KCNH2, KCNQ1 ).Disease-causing variants in cardiomyopathy genes were the predominant genetic cause of SCA. These findings inform which genes to include in genetic screening for SCA.

  View details for DOI 10.1101/2024.12.08.24318665

  View details for PubMedID 39936145

  View details for PubMedCentralID PMC11812600

• A Risk Prediction Score for Shockable Sudden Cardiac Arrest: Validation in the Framingham Heart Study Tri, T., Tai Truyen, Lin, H., Mathias, M., Chugh, H., Reinier, K., Benjamin, E., Chugh, S. LIPPINCOTT WILLIAMS & WILKINS. 2024

  View details for DOI 10.1161/circ.150.suppl_1.4143297

  View details for Web of Science ID 001400066401028

• CHARACTERIZATION OF BYSTANDERS PRESENT DURING SUDDEN CARDIAC ARRESTS USING ARTIFICIAL INTELLIGENCE TOOLS: A COMMUNITY-BASED STUDY OF 1018 EVENTS Heart Rhythm Panahiazar, M., Chugh, H., Mathias, M., Heckard, E., Sargsyan, A., Hadduck, K., Salvucci, A., Jui, J., Reinier, K., Chugh, S. S. 2024

  View details for DOI 10.1016/j.hrthm.2024.03.490