Resuscitation
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This study aimed to predict blood pressure during CPR using chest compression waveform information obtained from a CPR feedback device. ⋯ Blood pressure generated by chest compressions can be predicted with high accuracy by a machine learning method using chest compression waveform information obtained from a CPR feedback device and the patient's demographic characteristics. Real-time provision of the predicted blood pressure can be used to monitor the quality and efficacy of CPR.
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Given challenges in collecting long-term outcomes for survivors of in-hospital cardiac arrest (IHCA), most studies have focused on in-hospital survival. We evaluated the correlation between a hospital's risk-standardized survival rate (RSSR) at hospital discharge for IHCA with its RSSR for long-term survival. ⋯ There was a strong correlation between a hospital's RSSR at discharge and its 30-day RSSR for IHCA, although this correlation weakens over time. Our findings suggest that a hospital's RSSR at discharge for IHCA may be a reasonable surrogate of its 30-day post-discharge survival and could be used by Medicare to benchmark hospital performance for this condition without collecting 30-day survival data.