Resuscitation
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Observational Study
The Effect of Hand Position on Chest Compression Quality During CPR in Young Children: Findings from the Videography in Pediatric Emergency Research (VIPER) Collaborative.
To determine the effect of hand position on chest compression (CC) quality during CPR in young children. ⋯ In infants, 1H resulted in greater CC depth than 2 T. In children 1 to 8 yo, 2H resulted in greater depth than 1H.. These data suggest that different hand position during CPR in young children from what is currently recommended may result in better CPR quality.
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Increasing venous return during cardiopulmonary resuscitation (CPR) has been shown to improve hemodynamics during CPR and outcomes following cardiac arrest (CA). We hypothesized that a high central venous pressure amplitude (CVP-A), the difference between the maximum and minimum central venous pressure during chest compressions, could serve as a robust predictor of return of spontaneous circulation (ROSC) in addition to traditional measurements of coronary perfusion pressure (CPP) and end-tidal CO2 (etCO2) in a porcine model of CA. ⋯ In our study, CVP-A was a potentially useful predictor of successful defibrillation and return of spontaneous circulation. Overall, CVP-A could serve as a marker for prediction of ROSC with increased venous return and thereby monitoring the beneficial effects of ACD and ITD.
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Efficient ventilation is important during cardiopulmonary resuscitation (CPR). Nevertheless, there is insufficient knowledge on how the patient's position affects ventilatory parameters during mechanically assisted CPR. We studied ventilatory parameters at different positive end-expiratory pressure (PEEP) levels and when using an inspiratory impedance valve (ITD) during horizontal and head-up CPR (HUP-CPR). ⋯ When using mechanical ventilation during CPR, it seems that the PEEP level and patient position are important determinants of respiratory parameters. Moreover, tidal volume seems to be lower when the thorax is positioned at 35°.
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Cardiac arrest is a leading cause of mortality prior to discharge for children admitted to the pediatric intensive care unit. To address this problem, we used machine learning to predict cardiac arrest up to three hours in advance. ⋯ We have created high-performing models that identify signatures of in-hospital cardiac arrest (IHCA) that may not be evident to clinicians. These signatures include a combination of heart rate variability metrics, vital signs data, and therapeutic drug classes. These machine learning models can predict IHCA up to three hours prior to onset with high performance, allowing clinicians to intervene earlier, improving patient outcomes.
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Observational Study
Calcium Use during Paediatric In-hospital Cardiac Arrest is Associated with Worse Outcomes.
To evaluate associations between calcium administration and outcomes among children with in-hospital cardiac arrest and among specific subgroups in which calcium use is hypothesized to provide clinical benefit. ⋯ Calcium use was common during paediatric in-hospital cardiac arrest and associated with worse outcomes at hospital discharge.