The relationship between time to arrival of emergency medical services (EMS) and survival from out-of-hospital ventricular fibrillation cardiac arrest |
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Authors: | Laura S. Gold Carol E. Fahrenbruch Mickey S. Eisenberg |
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Affiliation: | a University of Washington School of Public Health and Community Medicine, Department of Epidemiology, Seattle, WA, USA b Division of Emergency Medical Services, Public Health Seattle and King County, Seattle, WA, USA c University of Washington School of Medicine, Department of Medicine, Seattle, WA, USA |
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Abstract: | AimWe examined the relationship between time from collapse to arrival of emergency medical services (EMS) and survival to hospital discharge for out-of-hospital ventricular fibrillation cardiac arrests in order to determine meaningful interpretations of this association.MethodsWe calculated survival rates in 1-min intervals from collapse to EMS arrival. Additionally, we used logistic regression to determine the absolute probability of survival per minute of delayed EMS arrival. We created a logistic regression model with spline terms for the time variable to examine the decline in survival in intervals that are hypothesized to be physiologically relevant.ResultsThe observed data showed survival declined, on average, by 3% for each minute that EMS was delayed following collapse. Survival rates did not decline appreciably if the time between collapse and arrival of EMS was 4 min or less but they declined by 5.2% per minute between 5 and 10 min. EMS arrival 11-15 min after collapse showed a less steep decline in survival of 1.9% per minute. The spline model that incorporated changes in slope in the time interval variable modeled this relationship more accurately than a model with a continuous term for time (p = 0.01).ConclusionsThe results of our analyses show that survival from out-of-hospital cardiac arrest does not decline at a constant rate following collapse. Models that incorporate changes that reflect the physiological alterations that occur following cardiac arrests are a more accurate way to describe changes in survival rates over time than models that include only a continuous term for time. |
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Keywords: | Cardiac arrest Defibrillation Spline modeling Survival |
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