View clinical trials related to Infection.
Filter by:This is a retrospective observational study drawing on data from the Brigham and Women's Home Hospital database. Sociodemographic and clinic data from a training cohort were used to train a machine learning algorithm to predict patient deterioration throughout a patient's admission. This algorithm was then validated in a validation cohort.
Controlled, prospective, open-label trial with a total duration of 2 weeks to assess the clearance of inflammatory interleukins by different membranes in haemodialysis patients with COVID-19.
EC CORONACOLCHI is a multicenter, double-blind and randomized clinical trial with two branches. Patients who meet all the inclusion criteria and none of the exclusion criteria will be randomized 1: 1 to be included in one of the following groups: - Experimental group: colchicine for 2 weeks orally at the doses described, added to the standard treatment of COVID-19. - Control group: placebo for 2 weeks orally added to standard COVID-19 treatment.
The alternatives to the combination of Fluoroquinolone and Rifampicin in prosthetic joint infections (PJI) caused by staphylococcus are currently unclear. Clindamycin is prescribed as dual therapy in this indication, and provides many advantages. We conducted a multicenter retrospective observational study evaluating the efficacy and safety of Clindamycin in prosthetic joint infections due to staphylococcus between January 2013 and December 2019.
This clinical trial studies the clinical effectiveness of S53P4 bioactive glass (BAG) as a bacterial growth inhibiting bone graft substitute in a one-stage or two-stage surgical procedure for treatment of chronic long bone osteomyelitis.
This is a retrospective non-randomized clinical study of 60 patients total to assess the effects of SARS-CoV-2 infection and the SARS-CoV-2 vaccination. This study will have 2 arms evaluating the epigenomes of patients pre and post-exposure to one of the interventions. The first arm of the study will analyze 40 patients' epigenomes whose DNA methylation was examined pre and post SARS-CoV-2 infection. The second arm of this study is analyzing 20 patients' epigenomes whose DNA methylation was examined pre and post-injection of the SARS-CoV-2 vaccine.
This is a study to evaluate the diagnostic performance of the investigational Cytovale System & IntelliSep Test as a diagnostic marker of sepsis in a population of patients presenting to the emergency department with signs or suspicion of infection compared to retrospective physician adjudication, per the sepsis 3 definition, of those patients.
Although many studies investigated the prevalence and manifestations of HPV-B19 infection in patients with sickle cell anemia (SCA), thalassemia, and hereditary spherocytosis (HS) separately, there is limited information about the extent to which HPV-B19 infection leads to severe complications and chronic infection.
It has been reported in several research studies that men are almost twice as likely to progress to severe COVID 19 disease and die than women. Some researchers have suggested this is due to the activity of estrogen which is produced by the ovaries in pre-menopausal women. Men and post-menopausal women produce very low levels of estrogen. This study will look whether E4, a natural estrogen, can help men and post-menopausal women that are hospitalized with COVID 19 infection but for whom help breathing is not yet needed. The study has 2 parts. In Part A, 162 patients will be randomized (81 patients in the E4 treatment arm and 81 patients in the placebo treatment arm). The data collected from patients in Part A will address the primary and secondary objectives of the study. Once all patients in Part A have been randomized and Part A analysis is complete, assuming positive data, recruitment and double-blind randomization of patients will continue into Part B, unchanged, on 1:1 basis to E4 and placebo.
This is a retrospective observational study drawing on data from the Brigham and Women's Home Hospital database. Sociodemographic and clinic data from a training cohort were used to train a machine learning algorithm to predict length of stay throughout a patient's admission. This algorithm was then validated in a validation cohort.