View clinical trials related to Severe Sepsis.
Filter by:1. To research the current situation of severe infection in children in China, and to investigate the incidence, prognosis and disease burden of severe infection in children in different regions of China. 2. Establish the risk prediction model and diagnosi model of severe infection in children, and verify the accuracy of the model in multi-center; 3. To study the effectiveness and safety of different treatments in real diagnosis and treatment, and to evaluate the efficacy of subgroups under different ages and high risk factors.
This is a single arm, pilot study. Patients in the LHSC adult ICU (Critical Care Trauma Centre) (1200 patients/annum) are screened daily for severe sepsis by the Clinical Research Assistants. Severe sepsis is defined as infection, systemic inflammation and sepsis-induced dysfunction of at least one organ system. Study consent is obtained from the patient or substitute decision maker. Our objective in this pilot study is to determine the feasibility of delivering a regular passive exercise intervention, and collecting relevant outcome data early in the course of severe sepsis in critically ill patients. We hypothesize that early passive exercise in septic patients will reduce inflammation, endothelial cell injury, microvascular hypoperfusion and mortality. Our goal is to provide the evidence from comprehensive analysis of biochemical, physiologic and patient outcomes to develop a definitive multi-centre clinical trial.
The purpose of this study is to demonstrate that addition of the Monocyte Width Distribution (MDW) parameter to current standard of care improves a clinician's ability to recognize sepsis in the Emergency Department, resulting in earlier decision to administer antibiotics from time of ED presentation for sepsis patients (simulated primary endpoint), with concomitant reductions in length of stay and in-hospital mortality for those patients (secondary endpoints).
The purpose of this study is to demonstrate that addition of the Monocyte Width Distribution (MDW) parameter to current standard of care improves a clinician's ability to recognize sepsis in the Emergency Department, resulting in earlier decision to administer antibiotics from time of ED presentation for sepsis patients (simulated primary endpoint), with concomitant reductions in length of stay and in-hospital mortality for those patients (secondary endpoints).
The purpose of this study is to demonstrate that addition of the Monocyte Width Distribution (MDW) parameter to current standard of care improves a clinician's ability to recognize sepsis in the Emergency Department, resulting in earlier decision to administer antibiotics from time of ED presentation for sepsis patients (simulated primary endpoint), with concomitant reductions in length of stay and in-hospital mortality for those patients (secondary endpoints).
The purpose of this study is to demonstrate that addition of the Monocyte Width Distribution (MDW) parameter to current standard of care improves a clinician's ability to recognize sepsis in the Emergency Department, resulting in earlier decision to administer antibiotics from time of ED presentation for sepsis patients (simulated primary endpoint), with concomitant reductions in length of stay and in-hospital mortality for those patients (secondary endpoints).
The benefits of fever treatment in critically ill patients remains unclear. The aim of the prospective, randomized clinical trial was to verify the hypothesis that the administration of ibuprofen in order to decrease the fever in septic patients without limited cardiorespiratory reserve leads to decreasing their prognosis.
This study is a multicenter randomized controlled trial. The purpose of this study is to assess the efficacy of the combination of PCR and CRISPR/Cas12a in alveolar lavage fluid for early targeted anti-infective therapy for patients with severe pneumonia. Hosted by the Department of Critical Care Medicine, Affiliated Drum Tower Hospital of Nanjing University Medical College, 5 adult ICU units participate in 3 hospitals. All patients are randomly assigned to the experimental group and the control group. For experimental group, the combined detection of PCR and CRISPR/Cas12a in the alveolar lavage fluid was carried out in the early stage, and the antibiotic scheme is changed base on the results of PCR-CRISPR/Cas12a.The patients in the control group were adjusted according to the traditional microbial detection methods. The types of early antibiotics, the proportion of target antibiotics, the duration of anti-infective treatment, the length of hospital stay in ICU, the mortality rate, the secondary antibiotic-associated diarrhea, and the incidence of new multidrug-resistant infections were recorded.
Machine learning is a powerful method to create clinical decision support (CDS) tools, when training labels reflect the desired alert behavior. In our Phase I work for this project, we developed HindSight, an encoding software that was designed to examine discharged patients' electronic health records (EHRs), identify clinicians' sepsis treatment decisions and patient outcomes, and pass those labeled outcomes and treatment decisions to an online algorithm for retraining of our machine-learning-based CDS tool for real-time sepsis alert notification, InSight. HindSight improved the performance of InSight sepsis alerts in retrospective work. In this study, we propose to assess the clinical utility of HindSight by conducting a multicenter prospective randomized controlled trial (RCT) for more accurate sepsis alerts.
In patients diagnosed as sepsis on PICU admission, early and accurate identification of patients who will develop organ dysfunction (severe sepsis) is critical for effective management and positive outcome. A multiple marker approach would improve clinical utility compared with use of a single marker. The primary goal of this part of study is to define a combination of multiple markers, derived from novel biomarkers (nCD-64, IL-27, sTREM, HLA-DR, IL-10), metabolomics and routine clinical parameters, which could predict severe sepsis and determine the severity of disease.