View clinical trials related to Severe Sepsis.
Filter by:The purpose of this study is to assess whether implementation of an ED Sepsis Tracking Sheet effects the percentage of goal-directed sepsis criteria met in a tertiary care academic Emergency Department.
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.
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.
In this clinical outcomes analysis, the effect of a machine learning algorithm for severe sepsis prediction on in-hospital mortality, hospital length of stay, and 30-day readmission was evaluated.
The purpose of this study is to study the implementation and impact of an early warning system to detect and treat sepsis in the emergency room. We are observing the implementation of a Sepsis Machine Learning Model on all Adult patients. All data (observations field notes, interview recording & transcripts, and survey responses) will be stored on HIPAA-compliant Duke servers behind the Duke firewall, and requiring password-protected user authentication to access. The risk to patients is minimal. The two risks to interviewed clinical staff we have identified involve loss of work time and anonymity.