ArticleThe Lancet. Digital health2023
Warning symptoms associated with imminent sudden cardiac arrest: a population-based case-control study with external validation.
Article in The Lancet. Digital health, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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Who cites it
11 citing papers in PubMed, 19 citations in OpenAlex.
- Clinical Triage of Individuals With Warning Symptoms of Imminent Cardiac Arrest.Circulation. Arrhythmia and electrophysiology · 2026Observational
- Article
- Incidence and clinical manifestations of sudden death in young adults: a two-decade, nationwide, retrospective, cross-sectional study.Resuscitation plus · 2026Article
- Stratifying risk of heart failure death and arrhythmic events: a ¹²³I-meta-iodobenzylguanidine-based multinomial logistic model.European journal of nuclear medicine and molecular imaging · 2026Article
- Moderate Kidney Dysfunction Independently Increases Sudden Cardiac Arrest Risk: A Community-Based Study.Journal of the American Heart Association · 2025Article
- The Singapore Physical Activity Readiness Questionnaire 2021 (SPARQ 2021)-Results of Public Feedback.Healthcare (Basel, Switzerland) · 2025Article
- Diagnostic value and clinical impact of cardiac magnetic resonance imaging in patients after sudden cardiac arrest: a retrospective study.Open heart · 2025Article
- Sudden cardiac death associated with fatty liver disease.International journal of cardiology. Heart & vasculature · 2025Article
- [Early classification and recognition algorithm for sudden cardiac arrest based on limited electrocardiogram data trained with a two-stages convolutional neural network].Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi · 2024Article
- Prevention of Sudden Cardiac Death: Beyond Automated External Defibrillators and Implantable Cardioverter Defibrillators.Circulation · 2024Article
- Sudden cardiac arrest: Limitations in risk-stratification and treatment, and the potential for digital technologies and artificial intelligence to improve prediction and outcomes.Progress in cardiovascular diseasesReview
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Authors and funding
16 authors at 5 institutions in 1 country.
Funding
Abstract
backgroundSudden cardiac arrest is a global public health problem with a mortality rate of more than 90%. Prearrest warning symptoms could be harnessed using digital technology to potentially improve survival outcomes. We aimed to estimate the strength of association between symptoms and imminent sudden cardiac arrest.
methodsWe conducted a case-control study of individuals with sudden cardiac arrest and participants without sudden cardiac arrest who had similar symptoms identified from two US community-based studies of patients with sudden cardiac arrest in California state, USA (discovery population; the Ventura Prediction of Sudden Death in Multi-Ethnic Communities [PRESTO] study), and Oregon state, USA (replication population; the Oregon Sudden Unexpected Death Study [SUDS]). Participant data were obtained from emergency medical services reports for people aged 18-85 years with witnessed sudden cardiac arrest (between Feb 1, 2015, and Jan 31, 2021) and an inclusion symptom. Data were also obtained from corresponding control populations without sudden cardiac arrest who were attended by emergency medical services for similar symptoms (between Jan 1 and Dec 31, 2019). We evaluated the association of symptoms with sudden cardiac arrest in the discovery population and validated our results in the replication population by use of logistic regression models.
findingsWe identified 1672 individuals with sudden cardiac arrest from the PRESTO study, of whom 411 patients (mean age 65·7 [SD 12·4] years; 125 women and 286 men) were included in the analysis for the discovery population. From a total of 76 734 calls to emergency medical services, 1171 patients (mean age 61·8 [SD 17·3] years; 643 women, 514 men, and 14 participants without data for sex) were included in the control group. Patients with sudden cardiac arrest were more likely to have dyspnoea (168 [41%] of 411 vs 262 [22%] of 1171; p<0·0001), chest pain (136 [33%] vs 296 [25%]; p=0·0022), diaphoresis (50 [12%] vs 90 [8%]; p=0·0059), and seizure-like activity (43 [11%] vs 77 [7%], p=0·011). Symptom frequencies and patterns differed significantly by sex. Among men, chest pain (odds ratio [OR] 2·2, 95% CI 1·6-3·0), dyspnoea (2·2, 1·6-3·0), and diaphoresis (1·7, 1·1-2·7) were significantly associated with sudden cardiac arrest, whereas among women, only dyspnoea was significantly associated with sudden cardiac arrest (2·9, 1·9-4·3). 427 patients with sudden cardiac arrest (mean age 62·2 [SD 13·5]; 122 women and 305 men) were included in the analysis for the replication population and 1238 patients (mean age 59·3 [16·5] years; 689 women, 548 men, and one participant missing data for sex) were included in the control group. Findings were mostly consistent in the replication population; however, notable differences included that, among men, diaphoresis was not associated with sudden cardiac arrest and chest pain was associated with sudden cardiac arrest only in the sex-stratified multivariable analysis.
interpretationThe prevalence of warning symptoms was sex-specific and differed significantly between patients with sudden cardiac arrest and controls. Warning symptoms hold promise for prediction of imminent sudden cardiac arrest but might need to be augmented with additional features to maximise predictive power.
fundingUS National Heart Lung and Blood Institute.
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