View clinical trials related to Heart Arrest.
Filter by:Emergency medical services (EMS) provide emergency care not only in the urban but also in the remote areas which could be up to 40 minutes from the EMS station. Thus, a cardiac arrest victim in those remote areas has a low likelihood to survive the cardiopulmonary resuscitation. Therefore, we have organized first responders (who are mostly volunteer fire-fighters) in the remote areas and taught them how to perform basic life support (BLS) with use of an automated external defibrillator (AED). In the case of a cardiac arrest the medical dispatcher activates simultaneously the EMS and the first responders, who perform the BLS with the use of an AED before the arrival of EMS. The aim of the study is to analyze and compare the survival of the cardiac arrest victims in remote areas in the time period when the first responders were not organized yet compared to the time period when the first responders were activated to perform BLS.
COVID-19, which emerged in China in December 2019, has become a pandemic with its spread to many countries of the world. Although it is suggested that hospital admissions are reduced due to some reasons such as trauma, during COVID-19 pandemic, it is controversial whether in-hospital mortality rates changed. Therefore this multi-centered study aimed to determine how in-hospital mortality effected during the pandemic period according to the specific patient groups.
This study will be a prospective, single-center, randomized controlled trial in a tertiary pediatric emergency department with two parallel groups of voluntary pediatric physicians and nurses. The impact of a mHealth supportive tool will be compared with conventional communication methods on situational awareness, leadership, team communication effectiveness and performance during standardized, simulation-based, pediatric in-hospital cardiac arrest scenario using a high-fidelity manikin. Thirty-six participants will be randomized (1:1). The primary endpoint is the situational awareness score measured with the situation awareness global assessment technique (SAGAT) instrument.
Determine the benefits of implantable cardioverter defibrillator (ICD) patients participating in a structured, 8-week educational telephone intervention delivered by expert cardiovascular nurses post-ICD. To determine if individuals participating in a post-hospital telephone nursing intervention would demonstrate (1) increased physical functioning, (2) increased psychological adjustment, (3) improved self-efficacy in managing the challenges of ICD recovery, and (4) lower levels of health care utilization over usual care at 1, 3, 6 and 12 months post-ICD implantation.
The overall incidence of cardiorespiratory arrest in Europe is estimated at 350,000 to 700,000 cases per year. Survival rate is estimated at 10.7% for all rhythm disorders combined. Several examples of AI application in the medical field exist. Ting et al have developed a computer tool capable of diagnosing the presence of diabetic retinopathy with excellent power. In resuscitation, Celi et al proposed a tool capable of predicting the need for crystalloid vascular filling during a systemic inflammatory state. In Nature in 2018, Komorowski demonstrated the efficacy of AI in the hemodynamic management of sepsis. In a study of the renal response to fluid challenge, Zhang et al. demonstrate the effectiveness of the learning machine. Objectives: Determination of an algorithm capable of predicting the mortality of patients admitted to intensive care units (ICU) for ACR from hospitalization reports (CRH). Also use of the algorithm to predict the risk of recurrence of the arrest, the duration of mechanical ventilation, the appearance of sepsis, the development of organ failure, prediction of the CPC (Cerebral Performance Category), time to obtain catecholamine withdrawal, the appearance of acute renal failure with or without the need for extra-renal purification (EER) and duration under EER, the average length of stay. This project is part of a larger, nationwide project with greater power, and includes all the data generated during hospitalization in intensive care. Method: an estimated total number of patients included in this study to be between 300 and 500. The population will come from the intensive care units of Nice, Antibes, Cannes, Grasse. Inclusion will be retrospective, on CRH, CR of CT imaging (cerebral and thoraco-abdomino-pelvic), MRI, EEG, and daily follow-up words, from 2014 to the end of 2020. After anonymisation, application of semantisation using natural language processing (NLP) methods. The data to be extracted are entered in a document written by intensive care physicians. These data will then be stored in a database. In order to meet the main objective, we will develop a computer algorithm capable of predicting mortality in the study population. This algorithm, based on a large database, can be designed using machine learning or even deep learning techniques depending on the amount of data to be processed.
This is a clinical observation study based on analysis of video-clip data of cardiopulmonary resuscitation (CPR) for out-of hospital cardiac arrest (OHCA) in emergency department. Aim of study is to evaluate effect of the factors relating endotracheal intubation (ETI) on the outcome of OHCA patients.
The study aims to increase proportions of bystander defibrillation during out-of-hospital cardiac arrest (hereof referred to as cardiac arrest) in residential areas with a high density of cardiac arrests. The intervention consists of Automated External Defibrillators (AEDs) and residents' involvement in resuscitation through training and enrollment as citizen responders.
A controlled clinical trial will be performed. School children from the age of 10 to 11 will be selected to learn basic life support (BLS) in a primary school of Zaragoza. One of the groups will learn BLS in two consecutive years and the other group will learn BLS only the first year. The investigators think that the knowledge will be better in the group that receives two interventions.
Out-of-hospital cardiac arrest (OHCA) is a leading cause of sudden death in Europe and the United States. Mortality is currently close to 40% among those patients who had been successfully resuscitated after OHCA associated with ventricular fibrillation or pulseless ventricular tachycardia . Coronary artery disease is observed in up to 70% of patients with OHCA and immediate coronary angiography . Current European and American guidelines recommend immediate coronary angiography with primary angioplasty in OHCA patients with ST-segment elevation on ECG after successful resuscitation . Furthermore, the identification of the culprit lesion by coronary angiography among patients with an acute coronary syndrome (ACS) and no OHCA is challenging. In a recent cardiac magnetic resonance study, Heitner et al. found that in almost half of the patients with non-ST segment elevation ACS, the culprit lesion was not properly detected or identified by coronary angiography. In the Coronary Angiography after cardiac arrest (COACT) trial, a randomized controlled trial comparing immediate versus delayed coronary angiography after OHCA in patients without ST segment elevation on ECG, some degree of coronary artery disease was found in 64.5% of the patients in the immediate angiography group and an unstable coronary lesion was identified in only 13.6% of the patients. However, in survivors of OHCA without ST segment elevation on ECG, the use of intra coronary optical computerized tomography (OCT) led to identification of plaque rupture (27%), plaque erosion (36%) and coronary thrombosis (59%) undetected on angiography. There is hence a clear need to improve causality diagnosis among patients resuscitated after OHCA and without ST segment elevation on ECG, and, in the case of coronary artery disease detection, to better identify the culprit vessel/lesion ultimately leading to a targeted treatment. These are the reasons why we have designed a prospective, multi-centre, single cohort, diagnostic accuracy study: to better explore the incidence of a true ACS among OHCA survivors and to evaluate the accuracy of angiography to detect the culprit lesion when compared to OCT.
The PERSEUS protocol is a new approach to the resuscitation of highly monitored patients with cardiac arrest. It aims at the optimization of all the available physiological parameters and the full exploitation of both the "cardiac pump" and "thoracic pump'. This protocol will help to titrate chest compressions, ventilation, and vasopressor dosing to physiological parameters, increasing survival after cardiac arrest with favorable neurological outcome