Your browser doesn't support javascript.
loading
Warning symptoms associated with imminent sudden cardiac arrest: a population-based case-control study with external validation.
Reinier, Kyndaron; Dizon, Bernadine; Chugh, Harpriya; Bhanji, Ziana; Seifer, Madison; Sargsyan, Arayik; Uy-Evanado, Audrey; Norby, Faye L; Nakamura, Kotoka; Hadduck, Katy; Shepherd, Daniel; Grogan, Tristan; Elashoff, David; Jui, Jonathan; Salvucci, Angelo; Chugh, Sumeet S.
Afiliación
  • Reinier K; Center for Cardiac Arrest Prevention, Department of Cardiology, Smidt Heart Institute, Cedars-Sinai Health System, Los Angeles, CA, USA.
  • Dizon B; Center for Cardiac Arrest Prevention, Department of Cardiology, Smidt Heart Institute, Cedars-Sinai Health System, Los Angeles, CA, USA.
  • Chugh H; Center for Cardiac Arrest Prevention, Department of Cardiology, Smidt Heart Institute, Cedars-Sinai Health System, Los Angeles, CA, USA.
  • Bhanji Z; Center for Cardiac Arrest Prevention, Department of Cardiology, Smidt Heart Institute, Cedars-Sinai Health System, Los Angeles, CA, USA.
  • Seifer M; Center for Cardiac Arrest Prevention, Department of Cardiology, Smidt Heart Institute, Cedars-Sinai Health System, Los Angeles, CA, USA.
  • Sargsyan A; Center for Cardiac Arrest Prevention, Department of Cardiology, Smidt Heart Institute, Cedars-Sinai Health System, Los Angeles, CA, USA.
  • Uy-Evanado A; Center for Cardiac Arrest Prevention, Department of Cardiology, Smidt Heart Institute, Cedars-Sinai Health System, Los Angeles, CA, USA.
  • Norby FL; Center for Cardiac Arrest Prevention, Department of Cardiology, Smidt Heart Institute, Cedars-Sinai Health System, Los Angeles, CA, USA.
  • Nakamura K; Center for Cardiac Arrest Prevention, Department of Cardiology, Smidt Heart Institute, Cedars-Sinai Health System, Los Angeles, CA, USA.
  • Hadduck K; Ventura County Health Care Agency, Ventura, CA, USA.
  • Shepherd D; Ventura County Health Care Agency, Ventura, CA, USA.
  • Grogan T; Department of Medicine, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA.
  • Elashoff D; Department of Medicine, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA.
  • Jui J; Department of Emergency Medicine, Oregon Health and Science University, Portland, OR, USA.
  • Salvucci A; Ventura County Health Care Agency, Ventura, CA, USA.
  • Chugh SS; Center for Cardiac Arrest Prevention, Department of Cardiology, Smidt Heart Institute, Cedars-Sinai Health System, Los Angeles, CA, USA; Division of Artificial Intelligence in Medicine, Department of Medicine, Cedars-Sinai Health System, Los Angeles, CA, USA. Electronic address: sumeet.chugh@cshs.or
Lancet Digit Health ; 5(11): e763-e773, 2023 11.
Article en En | MEDLINE | ID: mdl-37640599
BACKGROUND: Sudden 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. METHODS: We 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. FINDINGS: We 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. INTERPRETATION: The 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. FUNDING: US National Heart Lung and Blood Institute.
Asunto(s)

Texto completo: 1 Base de datos: MEDLINE Asunto principal: Paro Cardíaco Tipo de estudio: Diagnostic_studies / Observational_studies / Prognostic_studies / Risk_factors_studies Idioma: En Revista: Lancet Digit Health Año: 2023 Tipo del documento: Article

Texto completo: 1 Base de datos: MEDLINE Asunto principal: Paro Cardíaco Tipo de estudio: Diagnostic_studies / Observational_studies / Prognostic_studies / Risk_factors_studies Idioma: En Revista: Lancet Digit Health Año: 2023 Tipo del documento: Article