Survival from out-of-hospital cardiac arrest in cities with populations of more than 1 million has not been studied adequately. This study was undertaken to determine the overall survival rate for Chicago and the effect of previously reported variables on survival, and to compare the observed survival rates with those previously reported.
Consecutive prehospital arrest patients were studied prospectively during 1987.
The study area was the city of Chicago, which has more than 3 million inhabitants in 228 square miles. The emergency medical services system, with 55 around-the-clock ambulances and 550 paramedics, is single-tiered and responds to more than 200,000 emergencies per year.
We studied 3,221 victims of out-of-hospital cardiac arrest on whom paramedics attempted resuscitation.
Ninety-one percent of patients were pronounced dead in emergency departments, 7% died in hospitals, and 2% survived to hospital discharge. Survival was significantly greater with bystander-witnessed arrest, bystander-initiated CPR, paramedic-witnessed arrest, initial rhythm of ventricular fibrillation, and shorter treatment intervals.
The overall survival rates were significantly lower than those reported in most previous studies, all based on smaller communities; they were consistent with the rates reported in the one comparable study of a large city. The single factor that most likely contributed to the poor overall survival was the relatively long interval between collapse and defibrillation. Logistical, demographic, and other special characteristics of large cities may have affected the rates. To improve treatment of cardiac arrest in large cities and maximize the use of community resources, we recommend further study of comparable metropolitan areas using standardized terms and methodology. Detailed analysis of each component of the emergency medical services systems will aid in making improvements to maximize survival of out-of-hospital cardiac arrest.
"During the last ten years, researchers have determined that cancer patients have a particularly low rate of return of spontaneous circulation (ROSC) and survival to hospital discharge after CPR (Varon and Marik 2007; Schneider et al. 1993; Bedell et al. 1983; Roberts et al. 1990; Berger and Kelley 1994; Stiell et al. 1992; Brown et al. 1992; Becker et al. 1991; Wenzel et al. 2004; Taran et al. 2012; Leak et al. 2013; Fu et al. 2011, 2012; Tan and Jatoi 2011; Ho et al. 2011; Myrianthefs et al. 2010; Hwang et al. 2010; Reisfield et al. 2006; Wallace et al. 2002). The survival to discharge rates for out-of-hospital CPR and in-hospital CPR in unselected CPR populations is 1% to 10% and 15% respectively (Schneider et al. 1993; Bedell et al. 1983; Roberts et al. 1990; Berger and Kelley 1994; Stiell et al. 1992; Brown et al. 1992; Becker et al. 1991; Wenzel et al. 2004) and for cancer populations it is <6% (Myrianthefs et al. 2010; Hwang et al. 2010). An increased emphasis on palliative care for cancer patients and the incorporation of patient goals of care in planning therapeutic interventions holds the promise that CPR might be used more selectively among those with cancer, thereby resulting in higher rates of ROSC and longer term survival after cardiac arrest. "
[Show abstract][Hide abstract] ABSTRACT: Cardiopulmonary resuscitation (CPR) after cardiac arrest is utilized indiscriminately among unselected populations. Cancer patients have particularly low rates of return of spontaneous circulation (ROSC) and survival to hospital discharge after CPR. Our study determines rates of ROSC and survival to hospital discharge among cancer patients undergoing CPR in our cancer center. We examined whether these rates have changed over the past decade.
This IRB-approved retrospective observational study was conducted in our cancer center. The ED and cancer center provide medical care for ≥ 115,000 patients annually. Cases of CPR presenting to the cancer center for years 2003-2012 were identified using Institutional CPR and Administrative Data for Resuscitation and Billing databases. Age, gender, ethnicity, ROSC and Discharge Alive using a modified Utsein template was used to compare proportions achieving ROSC and survival to hospital discharge for two time periods: 2003-2007 (Group 1) and 2008-2012 (Group 2), using traditional Pearson chi-square statistics.
One hundred twenty-six cancer center patients received CPR from 2003-2012. Group 1 (N = 64) and Group 2 (N = 62) were similar; age (60 vs. 60 years), gender (63% vs. 58% male), and race/ethnicity (67% vs. 56% White). Proportions achieving ROSC were similar in the two time periods (36% Group 1 vs. 45% Group 2, OR = 1.47, 95% CI 0.72 - 3.00) as was survival to hospital discharge (11% Group 1 vs. 10% Group 2, OR 0.87, 95% CI 0.28 - 2.76).
ROSC after CPR in cancer patients and survival to hospital discharge did not change over time.
"Once VF has transitioned into the mother rotor form , defibrillation should occur as soon as possible. Passage of time, in any pulseless rhythm, is the most significant of survival determinants [9,25]. Effects of VF duration, which may or may not be countered by CPR, may be a pre-determining factor for defibrillation outcome. "
[Show abstract][Hide abstract] ABSTRACT: Background
Ventricular Fibrillation (VF) is a common presenting dysrhythmia in the setting of cardiac arrest whose main treatment is defibrillation through direct current countershock to achieve return of spontaneous circulation. However, often defibrillation is unsuccessful and may even lead to the transition of VF to more nefarious rhythms such as asystole or pulseless electrical activity. Multiple methods have been proposed for predicting defibrillation success based on examination of the VF waveform. To date, however, no analytical technique has been widely accepted. We developed a unique approach of computational VF waveform analysis, with and without addition of the signal of end-tidal carbon dioxide (PetCO2), using advanced machine learning algorithms. We compare these results with those obtained using the Amplitude Spectral Area (AMSA) technique.
A total of 90 pre-countershock ECG signals were analyzed form an accessible preshosptial cardiac arrest database. A unified predictive model, based on signal processing and machine learning, was developed with time-series and dual-tree complex wavelet transform features. Upon selection of correlated variables, a parametrically optimized support vector machine (SVM) model was trained for predicting outcomes on the test sets. Training and testing was performed with nested 10-fold cross validation and 6–10 features for each test fold.
The integrative model performs real-time, short-term (7.8 second) analysis of the Electrocardiogram (ECG). For a total of 90 signals, 34 successful and 56 unsuccessful defibrillations were classified with an average Accuracy and Receiver Operator Characteristic (ROC) Area Under the Curve (AUC) of 82.2% and 85%, respectively. Incorporation of the end-tidal carbon dioxide signal boosted Accuracy and ROC AUC to 83.3% and 93.8%, respectively, for a smaller dataset containing 48 signals. VF analysis using AMSA resulted in accuracy and ROC AUC of 64.6% and 60.9%, respectively.
We report the development and first-use of a nontraditional non-linear method of analyzing the VF ECG signal, yielding high predictive accuracies of defibrillation success. Furthermore, incorporation of features from the PetCO2 signal noticeably increased model robustness. These predictive capabilities should further improve with the availability of a larger database.
BMC Medical Informatics and Decision Making 10/2012; 12(1):116. DOI:10.1186/1472-6947-12-116 · 1.83 Impact Factor
"The overall survival rate of 13.9% (110 of 793 of our study) patients compares favorably to a 3.8% (1.7%–13%) pooled analysis of 3220 prehospital arrest patients suggesting improved prehospital outcome in this study.17 "
[Show abstract][Hide abstract] ABSTRACT: This study attempted to correlate the initial cardiac rhythm and survival from prehospital cardiac arrest, as a secondary end-point.
Prospective, randomized, double-blinded clinical intervention trial where bicarbonate was administered to 874 prehospital cardiopulmonary arrest patients in prehospital urban, suburban, and rural emergency medical service environments.
This group's manifested an overall survival rate of 13.9% (110 of 793) of prehospital cardiac arrest patients. The most common presenting arrhythmia was ventricular fibrillation (VF) (45.0%), asystole (ASY) (34.4%), and pulseless electrical activity (PEA) (15.7%). Less commonly found were normal sinus rhythm (NSR) (1.8%), other (1.8%), ventricular tachycardia (VT) (0.6%), and atrioventricular block (AVB) (0.5%) as prearrest rhythms. The best survival was noted in those with a presenting rhythm of AVB (57.1%), VT (33.3%), VF (15.7%), NSR (14.3%), PEA (11.2%), and ASY (11.1%) (p = 0.02). However, there was no correlation between the final cardiac rhythm and outcome, other than an obvious end-of-life rhythm.
The most common presenting arrhythmia was VF (45%), while survival is greatest in those presenting with AVB (57.1%).
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