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Bloodstream Infection clinical trials

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NCT ID: NCT06271031 Not yet recruiting - Sepsis Clinical Trials

Process Mapping and Data Collection to Inform a Computer Simulation Model of Hospitalised Patients With Bloodstream Infection, Sepsis and Systemic Infection

CSM-BSI
Start date: March 1, 2024
Phase:
Study type: Observational

The goal of this study is to create a computer simulation of patients with bloodstream infection to understand how changes in healthcare policies and resources affect patient treatment. This simulation will help doctors and health-care decision makers make better choices in treating these patients and avoid overusing antibiotics that can lead to antibiotic resistance. Antibiotic resistance is when bacteria can't be killed by antibiotics anymore. Participants will not receive treatments as this is an observational study, but the study will involve: - Interviews with healthcare staff to understand patient care pathways. - Analysis of historical data on bacteria causing infections and antibiotic treatments. - A 30-day observational study to observe patient treatment for bloodstream infections.

NCT ID: NCT06160115 Not yet recruiting - Clinical trials for Acute Lymphoblastic Leukemia

The Role of NK Cells to Detect Blood Infection in ALL.

Start date: February 1, 2024
Phase:
Study type: Observational

1. Assess possibility of prediction of blood stream infections in ALL patients by profiling of NK cells using flow cytometry. 2. Assess the role of NK cells in development of drug resistance post chemotherapy.

NCT ID: NCT05361135 Not yet recruiting - Sepsis Clinical Trials

18-fluorodeoxyglucose Positron Emission Tomography/Computed Tomography in S. Aureus Bacteraemia

PET-SAB
Start date: September 2023
Phase: N/A
Study type: Interventional

Having bacteria in the blood can be very dangerous. This is called bacteraemia (or bacteremia) or bloodstream infection. It can lead to problems across the whole body, which is what happens in sepsis. Bacteria called Staphylococcus aureus (S. aureus) cause one kind of bacteraemia. Up to a third of people with this condition die within three months, even with antibiotics. One reason for such severe problems is that the bacteria can spread almost anywhere in the body, and hide in places where they are very hard to find. When people with S. aureus bacteraemia come into hospital and have had antibiotics, doctors sometimes cannot tell if they still have an infection source (called a 'focus') hiding in their body. The focus can be like an abscess and may need removing or the pus draining out. A focus might be obvious, if there is pain or swelling, or it might be hidden and deep. If these 'foci' can be found, then doctors can treat them and this helps to cure patients. To improve survival for patients with these life-threatening infections, it is vital that doctors find the focus of S. aureus bacteraemia as quickly as possible. However, the research team do not know the best way to do this. Most patients with S. aureus bacteraemia have a chest X-ray and a scan of the heart valves. Patients may go to the scanning department lots of times while doctors try to work out where these foci are. This is uncomfortable and takes a lot of time. In about 1 in 5 cases the doctors still cannot find the focus. This is very worrying for patients, their relatives and doctors. This study has been designed by researchers, doctors and patient advocates. It aims to work out if fewer patients may die when a specific type of scan called a 'PET/CT' is done quickly, because it finds more foci. To do this the team plan to do a clinical trial in patients with S. aureus bacteraemia. Half of the patients will receive the usual tests that patients currently get and the other half will receive an extra scan as soon as possible. The patients will be chosen randomly (like the flip of a coin) to go into one of the 2 groups. A year into the trial, an independent committee will check the results to make sure the extra scan is finding more foci. If this is the case, the trial will carry on. At the end of the study, we will share the results globally. The findings are expected to change the way this dangerous condition is managed, so patients do better.

NCT ID: NCT04229511 Not yet recruiting - Clinical trials for Urinary Tract Infections

Development of Risk Score Model and Decision Tree Algorithm for Predicting Infections With CRKp in Colonized Patients

DETERMINE
Start date: April 2020
Phase:
Study type: Observational

DETERMINE trial is a prospective multicenter multinational cohort study. This study will be carried out to predict the risk of bloodstream infections (BSIs) or other types of invasive infection with carbapenem resistant K.pneumoniae in patients being colonized by CRKp. The results of DETERMINE trial would be quite important to prevent unnecessary coverage of carbapenem resistant Klebsiella pneumoniae in empirical treatment of colonized patients. In this study, both risk score model and decision tree algorithm will be constructed and compared with each other in terms of sensitivity, specificity, positive predictive value and negative predictive value.

NCT ID: NCT04229498 Not yet recruiting - Clinical trials for Bloodstream Infection

Comparison of Bloodstream Infections With Carbapenem Hetero-resistant vs Carbapenem Resistant Klebsiella Pneumoniae

COMBAT
Start date: April 2020
Phase:
Study type: Observational

COMBAT trial was contemplated to elucidate unknown clinical relevance of carbapenem heteroresistance among Klebsiella pneumoniae species. Bloodstream infections, type of frequently seen invasive infections that pathogen isolation, identification of antimicrobial resistance mechanisms can be performed efficiently, with carbapenem resistant Klebsiella pneumoniae (CRKp) and carbapenem hetero-resistant Klebsiella pneumoniae will be compared in terms of relevant clinical outcomes such as 30-day mortality rate, 14-day clinical cure rate, 7-day microbiological eradication rate and 90-day relapse/re-infection rate. In addition, underlying molecular resistance mechanisms causing carbapenem hetero-resistance among Klebsiella pneumoniae isolates will be investigated by using whole genome sequences.

NCT ID: NCT03991793 Not yet recruiting - Sepsis Clinical Trials

Granzyme A in Patients With E. Coli Bacteremic Urinary Tract Infections

GABEC
Start date: June 20, 2019
Phase:
Study type: Observational

Background: Survival in Granzyme A gene (gzmA) knocked-out mice was significantly longer than in wild-type mice in a murine peritonitis model (cecal ligation puncture). Hypothesis: GZM A has a pathogenic role in sepsis in humans and gzmA polymorphisms can help to predict the risk of sepsis among patients with systemic infections (E. coli bacteremic urinary tract infections). Objectives: 1. To assess the correlation between GZM A serum levels and systemic inflammatory response in a human model of infection/sepsis (E. coli bacteremic UTI) 2. To characterize gzmA polymorphisms among patients with E. coli bacteremic UTI 3. To determine GZM A serum kinetics among patients with E. coli bacteremic UTI 4. To characterize E. coli strains causing bacteremic UTI: antimicrobial phenotype and virulence factors ("virulome"). Methods: - Design and setting: Prospective nested case-control study - Study population: consecutive adult patients with bacteremic urinary tract infections (UTIs) caused by E. coli - Exclusion criteria: Patients with conditions that significantly compromise immune status or patients exposed to urologic procedures - Estimated sample size: 50 patients with a sepsis/ non sepsis 1:1 ratio. Septic and non septic patients will be matched on gender, age (+/- 10 years), comorbidity (Charlson score +/-1), time symptom onset to blood culture (+/- 24h) - Measurements: GZM A serum levels will be determined on day 0, day 2-3, day 30. GZM A kinetics, gzmA polymorphisms (whole exome sequencing).Whole genome sequencing of E. coli isolates retrieved from blood cultures will be performed. - Analysis: Association between GZM A levels and gzmA polymorphisms and sepsis will be analyzed adjusting for patient, infection and microorganism-related factors (multivariate analysis).