• J S Stapczynski, J E Svenson, and C K Stone.
• Department of Emergency Medicine, University of Kentucky Medical Center, Lexington 40536-0084, USA. jsstap01@pop.uky.edu
• Acad Emerg Med. 1997 Jun 1;4(6):552-8.

ObjectiveTo determine whether population density is an independent predictor of survival from out-of-hospital cardiac arrest managed by basic life support (BLS) services using automated external defibrillators (AEDs).MethodsA retrospective, observational study in Kentucky of 34 BLS services covering 22 counties during the years 1992 to 1994 who used AEDs to treat patients who had out-of-hospital cardiac arrests.ResultsOf 311 patients who had out-of-hospital cardiac arrests, 110 (35%) were defibrillated, 46 (15%) were resuscitated to hospital admission, and 19 (6%) survived to hospital discharge. Univariate predictors for survival to hospital discharge were emergency medical services response interval (from call receipt to ambulance arrival) < 8 minutes, defibrillation by the AED, initial rhythm of ventricular fibrillation or ventricular tachycardia (VF/VT), and population density > 100/square mile (sq mi) for the BLS service area (p < 0.001). A forced logistic regression model of survival to hospital discharge, using these 4 factors plus the presence of a witnessed arrest or bystander CPR, demonstrated that population density > 100/sq mi was highly significant (OR 9.4, 95% CI: 1.7 to 51.4, p < 0.01). Stepwise logistic regression models with combinations of these 6 factors found that survival to hospital discharge was best predicted by an initial rhythm of VF/VT (p = 0.004) and population density > 100/sq mi (p = 0.011).ConclusionsPopulation density is strongly associated with survival from out-of-hospital cardiac arrest. BLS services within areas with population densities < or = 100/sq mi sustained little benefit from the addition of AEDs to their treatment of patients who had out-of-hospital cardiac arrests.

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