Association of diastolic blood pressure with coronary perfusion pressure during resuscitation in pediatric swine.

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Diastolic blood pressure (DBP) is suggested as a surrogate for coronary perfusion pressure (CPP) during cardiopulmonary resuscitation. We examined the correlation between DBP and CPP and hypothesized that both would be associated with survival in a pediatric swine model of asphyxial cardiac arrest. We performed a retrospective, secondary analysis of 102 pediatric swine resuscitations. DBP and CPP were recorded every 30 s during resuscitation. Values were compared between survivors and non-survivors. DBP mirrored CPP in survivors and non-survivors throughout resuscitation and both were associated with survival. Improvements in DBP and CPP after the first epinephrine administration were greater in survivors (DBP: 25.1 ± 3.0 vs. 5.4 ± 0.8 mmHg, p < 0.01; CPP: 24.9 ± 3.2 vs. 4.8 ± 0.9 mmHg, p < 0.01). DBP and CPP after epinephrine administration were highly predictive of survival, with an area under the curve of 0.95 (0.89-1.00) for DBP and 0.90 (0.81-0.99) for CPP. The optimal threshold for DBP was 22.5 mmHg, whereas that for CPP was 14.5 mmHg. DBP and CPP were associated with survival throughout resuscitation, and the response of both to the first epinephrine administration was highly predictive of survivalin this model. Clinically, the availability of DBP makes it useful as a target for physiologic feedback during resuscitation. Diastolic blood pressure (DBP) mirrored coronary perfusion pressure (CPP) throughout prolonged resuscitation in a pediatric model of asphyxial cardiac arrest. Mean DBP and CPP were significantly greater in survivors than in non-survivors both before and after administration of epinephrine. The response of both DBP and CPP to the first dose of epinephrine was highly predictive of return of spontaneous circulation. Given the clinical availability of DBP, these findings support its use as a surrogate for CPP to guide high-quality cardiopulmonary resuscitation in this pediatric swine model.