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• W2146247615 abstract "The estimated survival rate of 8% to 10% after out-of-hospital cardiac arrest (OHCA) remains dismal. Few studies have addressed predictors of functional neurologic outcome after successful resuscitation. The objective of the study was to identify variables associated with favorable neurologic outcomes, defined by a Glasgow Coma Scale of 14 or 15, after OHCA. We used a propensity analysis and classification and regression tree model of 184 OHCA patients surviving to hospital admission at a cardiac arrest receiving center in Los Angeles County from 2008 to 2013. Forty-three patients (23%) had a favorable outcome, median age was 65 years (interquartile range [IQR] 54 to 76), and 98 (53%) were men. Sixty-six patients (36%) presented with a shockable rhythm. The majority were witnessed, either by a civilian (n=115, 63%) or a paramedic (n=25, 14%). Bystander cardiopulmonary resuscitation was performed on 84 patients (46%); median dose of epinephrine was 2 mg (IQR 1 to 3). Median time to return of spontaneous circulation was 21 minutes (IQR 16 to 29); the median lactate level was 5.2 mmol/L (IQR 2.8 to 9.2). Lower epinephrine doses (<1.5 mg) and lactate levels<5 mmol/L were predictive of a normal Glasgow Coma Scale, with 90.7% sensitivity (95% confidence interval [CI] 76.9% to 96.9%), 47.5% specificity (95% CI 39.1% to 56.1%), a positive predictive value of 34.5% (95% CI 31.6% to 46.1%), a negative predictive value of 94.4% (95% CI 85.5% to 98.2%), and an area under the curve of 0.89. The propensity score-adjusted logistic regression model demonstrated that receiving <1.5 mg of epinephrine was associated with a favorable neurologic outcome (odds ratio 3.3, 95% CI 1.1 to 10, p=0.04). In conclusion, for patients surviving to hospital admission, a good neurologic outcome was associated with having received <1.5 mg of epinephrine and a lactate level<5 mmol/L." @default.
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• W2146247615 date "2014-10-01" @default.
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• W2146247615 title "Predictors of Neurologic Outcome in Patients Resuscitated from Out-of-Hospital Cardiac Arrest Using Classification and Regression Tree Analysis" @default.
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• W2146247615 doi "https://doi.org/10.1016/j.amjcard.2014.06.031" @default.
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