View clinical trials related to Emergencies.
Filter by:Introduction: Early and rapid diagnosis of etiology is often an important part of saving the lives of patients in emergency department. Chest CT is an important examination method for emergency diagnosis because of its fast examination speed and accurate localization. Traditional medical imaging diagnosis relies on radiologists to report in a qualitative and subjective manner. Through the interdisciplinary combination of clinical, imaging and artificial intelligence, the integration of multi-omics data, the construction of large-scale language models, and the construction of the auxiliary diagnosis support system of "one check for multiple diseases" provide new ideas and means for the rapid and accurate screening of emergency critical diseases. Method： Study design Investigators retrospectively collected cardiovascular, respiratory, digestive, and neurological CT images, demographic data, medical history and laboratory date of emergency department patients during the period from 1 January 2018 and 30 December 2024. Regularly carry out standardized follow-up work, and complete the collection and database establishment of clinical-imaging multi-omics data of patients attending emergency department.The inclusion criteria are:1. adult emergency patients with cardiovascular, respiratory, digestive, and nervous system diseases; 2. These patients had CT images. Patients with incomplete clinical or radiographic data were excluded from the analysis. Regularly carry out standardized follow-up work, and complete the collection and database establishment of clinical-imaging multi-omics data of patients attending emergency department. Based on the collected medical text data, an artificial intelligence large-scale language model algorithm framework is built. After the structure annotation of chest CT images is performed by doctors above the intermediate level of imaging, the Transformer deep neural network is trained for CT image segmentation, and a series of tasks such as structural structure segmentation, damage detection, disease classification and automatic report generation are developed based on Vision Transformer self-attention architecture mechanism. A multi-disease diagnosis and treatment decision-making system based on chest CT images, clinical text and examination multimodal data was constructed and validated. Disscusion Emergency medicine deals mainly with unpredictable critical and sudden illnesses. Patients who come to the emergency department for medical treatment often have acute onset, hidden condition, rapid progress, many complications, high mortality and disability rate. Assisted diagnosis systems developed by combining clinical text, images and artificial intelligence can greatly improve the ability of emergency department doctors to accurately diagnose diseases. This study fills the blank of CT artificial intelligence aided diagnosis system for emergency patients, and provides a rapid diagnosis scheme for multi-system and multi-disease. Finally, the results will be transformed into clinical application software and used and promoted in clinical work to improve the diagnosis and treatment level.
The goal of this clinical trial is to learn about the reduction of pain and anxiety during a minor procedure in the emergency department on adult patients through the visualisation of atmospheric projection as a distraction mean. The main question it aims to answer is : Can the atmospheric projection of a video reduce pain and anxiety in adult patients receiving painful procedures in the emergency department ? Participants will look at an atmospheric projection (projection of a media on the walls and roof around the patient) while receiving their planned care procedures. Researchers will compare an active group watching a video with a control group watching a simple colored light to see if the visualisation of an atmospheric projected video reduces pain and anxiety more than the visualisation of a colored light does.
The purpose of the study is to study changes in sedentary behavior following a behavioral intervention (sit-and-stand desk, and cycloergometer)
A Multicentre, Randomized, Double-blind, Parallel Design Phase III Study to Evaluate the efficacy and safety of QLG2071 Versus Cleviprex® in the Treatment of Hypertensive Emergency and Sub-emergency
Aortic dissection is an uncommon and serious pathology. Its diagnosis is difficult because of the varied and silent clinical presentations. The development of ultrasound in emergency medicine is an asset in certain pathologies. The aim of this study is therefore to study the feasibility of a protocol integrating clinical ultrasound in the suspicion of acute aortic dissection in the hospital setting. This study is a single-center prospective interventional study. In which the investigators perform ultrasound in patients with suspected acute aortic dissection in the emergency department. If the protocol is feasible and if it allows a saving of time in the diagnosis or an increase in diagnoses, the investigators will be able to evoke a profitability to the systematic realization of this examination.
Surgeons experience higher levels of work stress, even under normal circumstances. Many can suffer from substantial levels of mental health issues, especially when faced with severe complications. However, due to a variety of reasons, many surgeons are reluctant to disclose mental health issues or seek psychological help. Patients in need of emergency surgery are usually characterized by critical conditions and high surgical risks. Emergency surgeons always do not have enough time to clearly explain the ins and outs of the disease to the family members of the patients, only tell the key issues and risks that need to be paid attention to during the operation. The tone of the explanation maybe direct and blunt, which also could cause the incomprehension and dissatisfaction of the patients and their families. Due to the lack of communication, although the patient is in critical condition, the family members always think that the disease should be cured after arriving at the hospital. Therefore, once severe complications occur after the operation, the family members often find it difficult to accept the reality. This is also one of the important reasons for medical disputes in emergency surgery. In addition to delaying patients' recovery courses, severe complications also place enormous pressure on chief surgeons who performed the operations. Such pressures may bring great risks of psychological distress. Surgeons are also the victims when they encounter severe complications following emergency surgery. Their mental distress should not be minimized. Until now, little has been known about the effects of surgical complications on surgeons. In the current study, based on a large-scale questionnaire survey in China, the investigators aimed to investigate incidences of surgeons' mental distress following severe complications after emergency surgery. The investigators also aimed to identify independent risk factors which could help develop strategies to improve the mental well-being of these surgeons after such incidences.
Vaso-occlusive crisis (VOC) is the most common complaint in patients with sickle cell disease presenting to the emergency room. VOC is most commonly treated with opioids and NSAIDs. However, new research is demonstrating that opioids in addition to virtual reality (VR) is more effective at reducing the experience of pain and pain nerve signals compared to opioids alone. Numerous research studies have demonstrated that VR reduces the experience of pain during painful medical procedures in children, such as venipuncture and burn wound dressing changes. The study aims to add VR to standard of care medical treatment for pediatric patients with sickle cell disease who present to the pediatric emergency department in VOC. Investigators will conduct a retrospective chart review of patients aged 6 to 21 years with sickle cell disease who present to the pediatric emergency department with VOC for the historical control arm. Investigators will also conduct a prospective convenient sampling of patient who receive VR plus standard medical care in patients aged 6 to 21years with sickle cell disease who present to the emergency department with VOC. Investigators hypothesize that VR, in addition to standard medical care, will reduce the experience of pain and hospital admissions compared to the historical control group (standard medical treatment).
This study seeks to utilise retrospective patient data to train machine learning algorithms to predict the short term mortality and morbidity after an emergency laparotomy. Data will be collected via the Electronic Health records system at the Queen Mary Hospital Hong Kong. Machine learning models will be compared and the best-performing one will be explored for further optimization and deployment. Upon completion, we hope that this platform will aid clinicians to identify high risk patients and aid clinical decisions and peri-operative planning, with the aim to reduce mortality and morbidity in this high risk procedure.
The proposed study will be the first randomized clinical trial to evaluate a comprehensive Emergency Department (ED)-based intervention for moderate to severe Alcohol Use Disorder (AUD) combining Screening, Brief Intervention and Referral to Treatment (SBIRT) with ED-initiated medications for treatment of alcohol use disorder (MAUD). The primary objective of this phase 3 study is to evaluate for differences in treatment engagement 30 days after ED visit between emergency department patients with moderate to severe alcohol use disorder (AUD) who are randomized to initiate medications for the treatment for AUD in the ED in addition to receiving a brief intervention and referral to ongoing treatment, which all participants will receive. The secondary objective of this study is to evaluate the difference in reduction of heavy drinking days between the two ED treatment models during the 30 days post ED visit.
The aim of the study is to examine the effect of animal-assisted practice on fear in children admitted to the emergency room.