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Cardiopulmonary Resuscitation

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The effects of sternal intraosseous and intravenous administration of amiodarone in a hypovolemic swine cardiac arrest model.

American journal of disaster medicine
OBJECTIVE: This study compared the effects of amiodarone via sternal intraosseous (SIO) and intravenous (IV) routes on return of spontaneous circulation (ROSC), time to ROSC, concentration maximum (C), time to maximum concentration (T), and mean conc...

The effects of tibial intraosseous versus intravenous amiodarone administration in a hypovolemic cardiac arrest procine model.

American journal of disaster medicine
OBJECTIVE: This study compared the effects of amiodarone via tibial intraosseous (TIO) and intravenous (IV) routes on return of spontaneous circulation (ROSC), time to ROSC, maximum drug concentration (Cmax), time to maximum concentration (Tmax), and...

The comparison of humeral intraosseous and intravenous administration of vasopressin on return of spontaneous circulation and pharmacokinetics in a hypovolemic cardiac arrest swine model.

American journal of disaster medicine
INTRODUCTION: The American Heart Association (AHA) recommends intravenous (IV) or intraosseous (IO) vasopressin in Advanced Cardiac Life Support (ACLS). Obtaining IV access in hypovolemic cardiac arrest patients can be difficult, and IO access is oft...

Predict In-Hospital Code Blue Events using Monitor Alarms through Deep Learning Approach.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Bedside monitors in hospital intensive care units (ICUs) are known to produce excessive false alarms that could desensitize caregivers, resulting in delayed or even missed clinical interventions to life-threatening events. Our previous studies propos...

A Machine Learning Shock Decision Algorithm for Use During Piston-Driven Chest Compressions.

IEEE transactions on bio-medical engineering
GOAL: Accurate shock decision methods during piston-driven cardiopulmonary resuscitation (CPR) would contribute to improve therapy and increase cardiac arrest survival rates. The best current methods are computationally demanding, and their accuracy ...

Newborn self-inflating manual resuscitators: precision robotic testing of safety and reliability.

Archives of disease in childhood. Fetal and neonatal edition
AIM: A controlled bench test was undertaken to determine the performance variability among a range of neonatal self-inflating bags (SIB) compliant with current International Standards Organisation (ISO).

Machine learning as a supportive tool to recognize cardiac arrest in emergency calls.

Resuscitation
BACKGROUND: Emergency medical dispatchers fail to identify approximately 25% of cases of out of hospital cardiac arrest, thus lose the opportunity to provide the caller instructions in cardiopulmonary resuscitation. We examined whether a machine lear...

A machine learning based model for Out of Hospital cardiac arrest outcome classification and sensitivity analysis.

Resuscitation
BACKGROUND: Out-of-hospital cardiac arrest (OHCA) affects nearly 400,000 people each year in the United States of which only 10% survive. Using data from the Cardiac Arrest Registry to Enhance Survival (CARES), and machine learning (ML) techniques, w...

Detecting Mistakes in CPR Training with Multimodal Data and Neural Networks.

Sensors (Basel, Switzerland)
This study investigated to what extent multimodal data can be used to detect mistakes during Cardiopulmonary Resuscitation (CPR) training. We complemented the Laerdal QCPR ResusciAnne manikin with the Multimodal Tutor for CPR, a multi-sensor system c...