View clinical trials related to Infection, Bacterial.
Filter by:Respiratory infections such as colds, flu and pneumonia affect millions of people around the world every year. Most cases are mild, but some people become very unwell. Influenza ('flu') is one of the most common causes of lung infection. Seasonal flu affects between 10% and 46% of the population each year and causes around 12 deaths in every 100,000 people infected. In addition, both influenza and coronaviruses have caused pandemics in recent years, leading to severe disease in many people. Although flu vaccines are available, these need to change every year to overcome rapid changes in the virus and are not completely protective. This study aims to find and develop predictive tests to better understand how and when flu-like illness progresses to more severe disease. This may help to decide which people need to be admitted to hospital, and how their treatment needs to be increased or decreased during infection. The aim is to recruit 100 patients admitted to hospital due to a respiratory infection. It is voluntary to take part and participants can choose to withdraw at any time. The study will involve some blood and nose samples. This will be done on Day 0, Day 2 and Discharge from hospital, and an out-patient follow-up visit on Day 28. The data will be used to develop novel diagnostic tools to assist in rational treatment decisions that will benefit both individual patients and resource allocation. It will also establish research preparedness for upcoming pandemics.
This multi-center observational case-control study in Intensive Care Unit (ICU) patients is to identify novel biomarkers allowing to recognize severe community acquired pneumonia (sCAP) -associated sepsis at an earlier stage and predict sepsis-related mortality. Patients with sCAP (cases) will be profoundly characterized over time regarding the development of sepsis and compared with control patients. The mechanisms and influencing factors on the clinical course will be explored with most modern -omics technologies allowing a detailed characterisation. These data will be analysed using machine learning algorithms and multi-dimensional mathematical models.
Bone and joint infections (BJI) is a public health issue in industrialized countries. Implant-associated BJI, are complex hospital-acquired infections and eradication of the pathogen is challenging in such patients. A prolonged antimicrobial therapy is usually required from 6 weeks to 3 months, but some patients are eligible to several years of treatment and most of patients report gastrointestinal troubles, such as nausea and mild to severe diarrhea (but very few developed C. difficile diarrhea). Moreover, the host gut microbiota is probably largely affected in abundance, richness and diversity. Indeed, it is known, that few days of antibiotics are sufficient to induce significant alterations of the gut microbiota, also called dysbiosis. Severe dysbiosis, which is potentially irreversible and associated with a definitive shift in the gut microbiota metabolism and host homeostasis, may lead to and/or promote a large panel of severe diseases such as Clostridium difficile infection, diabetes mellitus, obesity, inflammatory bowel disease (IBD), cirrhosis, neurological disorders and cancer. It may also be associated with BJI recurrence and then impact global health costs. The main objective of this study is to constitute biobanking of stools and perform DNA sequencing of the gut microbiota in patients with acute or sub-acute implant-related Bone and Joint Infection (BJI), caused by Staphylococcus aureus.
The mortality effect of kangaroo mother care in stable newborns <2000g is well established but mortality effect in unstable newborns is not conclusively known. This pragmatic clinical trial aims to investigate the mortality and clinical effects of early continuous Kangaroo Mother Care (KMC) compared to standard care in mild-moderately unstable neonates <2000g in a resource limited hospital setting.