Active clinical trials for "Heart Arrest"

The purpose of this study is to evaluate the accuracy of medical personnel in their ability to predict the likelihood of non-intensive care (ICU), ward patients to clinically deteriorate (defined as a cardiac arrest, unplanned ICU transfer, or unexpected death)via the use of a clinical judgement-based tool designed for this study, Patient Acuity Rating (PAR), to predict short-term clinical deterioration. We will compare the ability of this tool to predict clinical deterioration compared to accepted physiology-based tools and tools combining judgment and physiology as well as other markers of deterioration such as physician order changes. We will compare the sensitivity, specificity and area under the curve of these combined models to the predictive models including only physiology or clinical judgment. We will assess the correlation between specific physician orders and patient deterioration to determine whether specific clinical activities, such as emergently obtained radiology exams, predict impending deterioration. We hypothesize that PAR will be a useful tool for predicting clinical deterioration across the institution and that it will have a higher average accuracy for predicting clinical deterioration in non-ICU inpatients within 24 hours than the physiology-based tools alone. We further hypothesize that a combined metric which includes both the PAR and the individual physiologic components that comprise physiologic tools will not significantly improve prediction over the PAR alone. We further propose to use PAR to prospectively risk stratify patients for preemptive evaluation by the Rapid Response Team. We hypothesize that intervening on high risk patients by preemptively activating the hospital's Rapid Response Team (to assess and treat patients as needed) will decrease cardiac arrest rates and mortality.

Safety of healthcare professionals working in high-risk environments is of upmost importance. Personal protective equipment (PPE) may affect the performance of individuals and teams by altering their senses, manual skills and ability to communicate. Current guidelines offer flexibility in terms of which specific PPE components can safely be used. Yet, in some organisations, healthcare workers become used to using PPE well above the recommended standards (termed further in text as super-safe setup, SSS). Impact of this PPE policy on team performance and in turn to patient safety is unknown. The investigators hypothesise that SSS, as compared to WHO PPE standard, would negatively impact team performance and patient outcomes in a simulated crisis scenario.

Context: Chest compressions quality is known to be essential in cardiopulmonary resuscitation. Despite a known harmful effect of chest compressions interruptions, current guidelines still recommend provider switch every 2 minutes. Feedback impact on chest compressions quality preservation during cardiopulmonary resuscitation remains to be assessed. Study design: simulated prospective monocentric randomized crossover trial. Participants and methods: Sixty five professionals rescuers of the pre-hospital care unit of University Hospital of Caen (doctors, nurses and ambulance drivers) are enrolled to performed continuous chest compression on manikin (ResusciAnne®, Laerdal), twice, with and without a feedback device (CPRmeter®). Correct compression score (the main criterion) is defined by reached target of rate, depth and leaning at the same time (recorded continuously). Hypothesis: Feedback device preserve chest compression quality above the 2 minutes recommended switch over during cardiopulmonary resuscitation.

The overall goal of the project is to reduce the number of unexpected patient deteriorations by 50% at Emergency Departments (ED) by investigating if the novel Patient Deterioration Warning Systems (PDWS), can improve clinicians' ability to identify deterioration at an earlier stage. A third of all acute medical patients with normal vital signs at arrival, experience a deterioration in vital signs during the 24 first hours. This can potentially lead to dire consequences for these patients, as the risk of deterioration is present across all severity levels. The utilization of patient monitoring systems in the dispersed and shared working environments of EDs and acute wards may help to identify some of the reasons for failure to rescue patients. Thus, quantifying the extent to which a patient is being monitored, may be an aid to bridge the current gap between usage of automated and manual monitoring as clinical work will continue to depend on tacit knowledge and intuition. Several systems and protocols have been established to swiftly deal with identified deterioration. Most systems struggle with issues of clinical adherence and are difficult to assess on-the-fly, and in some cases nurses failed to notice abnormality in 43% of patients experiencing deterioration. Although the trajectories of patients' vital signs have been identified as more important than the initial scoring value, most of the widely used Track and Trigger systems lack a temporal aspect. Furthermore, a limited number of these Track and Trigger systems have been integrated into real time clinical decision support systems, which has not evolved much in the last decades. The PDWS deals with these challenges by aggregating and summarizing all vital values measured with the ED's patient monitors in the ongoing admission to intuitively present the state and trajectory. The investigators intend to determine if making the PDWS system available to nurses and physicians throughout the entire ED improves their ability to identify patients at risk of deterioration. To make this assessment, the PDWS will be evaluated in a cluster randomized trial (CRT) at two ED facilities in Denmark. The CRT is structured in three 5-week intervention, and three 5-week control periods, separated by a washout period of at least one week. The primary outcome is in-hospital deterioration - defined as transfer to the intensive care unit, heart/respiratory failure or death. The effect the PDWS will be assessed by comparing the proportions of events in each study arm using Pearsons's chi-squared test on these two samples. Furthermore, the technical and economical effects are evaluated using the Technology Acceptance Model, and the Model for Assessment of Telemedicine.

There is significant data showing that the quality of CPR performed is quite poor. Recent studies have shown that when real-time visual corrective feedback is available to CPR providers, quality (compression depth and rate) improves. Pilot work at John's Hopkins Children's Hospital indicates that providing a CPR Coach whose role it is to provide real-time coaching during cardiac arrest, further improves the quality of CPR. This study will assess the impact of a CPR Coach for improving CPR quality and CPR perception in a team of healthcare providers during simulated CPA.

The investigators hypothesize that if decrease in SctO2 level is caused by the degree of hypothermia, SctO2 level in the 33-TH may be lower than that in the 36-TH group. if decrease in SctO2 level is not caused by the degree of hypothermia but caused by brain injury, SctO2 level may be associated with only the prognosis of cardiac arrest victims regardless of core temperatures. The primary objective of this study is to compare the 72-hour changes in SctO2 level between the 36-TH and 33-TH groups in cardiac arrest victims.

1. Hypothesis The early elevation of the lower extremities during out-of-hospital cardiopulmonary resuscitation increases survival to one month by improving cardiac preload and blood flow to the heart and brain during chest compression.

The study is designed as a pilot, open-label study to investigate the feasibility and safety of selective cerebral hypothermia in OHCA patients receiving ECPR.

"Sudden cardiac arrest" occurs when someone's heart stops beating unexpectedly. Each year, more than 45,000 Canadians have a cardiac arrest. A bystander can do three things to improve survival: Call 911,start chest compressions and apply a defibrillator. Together, these actions can increase survival by up to 800%. The problem is that bystanders to cardiac arrest only provide CPR in about 3 of every 10 cardiac arrest cases and AED use in about 3 of every 100 cardiac arrest cases. There are many people in the community who are trained and willing to provide help for cardiac arrest victims such as off-duty paramedics, fire fighters, nurses, etc. When a cardiac arrest occurs in the city, it is likely that one of these people is nearby, but unaware of the emergency. The PulsePoint smartphone application enables these people to be notified by the local emergency 911 service when there is a cardiac arrest near to them. It can be freely downloaded to several common types of smartphones. When there is a cardiac arrest emergency, all nearby PulsePoint users are sent an alert from the 911 service. When the phones receive the alert, they ring, vibrate and display a text message saying "CPR NEEDED". The user's current location and the exact location of the cardiac arrest are then displayed on a map. Nearby public access AEDs are also indicated on the map. The smartphone users can then go to provide chest compressions and use an AED while paramedics are on their way. A video at www.pulsepoint.org shows how this works. The objective of the investigators is to measure whether the PulsePoint smartphone application increases bystander CPR or AED use for victims of cardiac arrest outside the hospital. This project will happen in the City of Toronto. The investigators have a plan to get as many people as possible to download the application, focusing on health care professionals who know CPR. The investigators will set up a webpage that helps people download the software to their phone. The investigators will randomize 911 calls to have a PulsePoint alert sent or not. The investigators will use statistical analysis to measure whether sending an alert to a smartphone increases the chances of bystander resuscitation.

Rescu Epistry includes data points pertaining to prehospital and in-hospital clinical treatments and responses to therapy, survival to discharge and functional outcome data for all cases.