Active clinical trials for "Pneumonia, Viral"

The aim of this study is to assess the epidemiological and clinical features of patients diagnosed with COVID-19 in Kazakhstan at the onset of the pandemic.

The purpose of this study is to determine whether a protein called TREM-1 can be used to differentiate viral and bacterial pneumonias in children who are on ventilator support. We propose that the level of TREM-1 will be significantly elevated in the lung fluid of children with bacterial pneumonia and viral with co-existing bacterial pneumonia than in children with pure viral pneumonia.

This project aims to use artificial intelligence (image discrimination) algorithms, specifically convolutional neural networks (CNNs) for scanning chest radiographs in the emergency department (triage) in patients with suspected respiratory symptoms (fever, cough, myalgia) of coronavirus infection COVID 19. The objective is to create and validate a software solution that discriminates on the basis of the chest x-ray between Covid-19 pneumonitis and influenza

Chest computed tomography of patients having coronavirus disease (COVID-19) will be analyzed with regards to vascular abnormalities (pulmonary embolism and vascular thickening), and their association with lung inflammation. The prevalence, severity, distribution, and prognostic value of chest CT findings will be assessed. Patients with vascular abnormalities will be compared to patients without, which is supposed to provide insights into the prognostic role of such abnormalities, and the potential impact on treatment strategy.

Severe Acute Respiratory Infection (SARI) is defined by the World Health Organization (WHO) as acute respiratory infection with a history of fever ≥38°C and cough for less than 10 days duration that requires hospital admission. SARI-PREP is a multi-center consortium funded by the CDC Foundation being assembled with the goal of providing the infrastructure to rapidly collect prospective data on clinical risks and outcomes, hospital-level stress, and biologic specimens that will aid in the rapid development of diagnostic and treatment approaches. A current example of a form of SARI to be targeted by SARI-PREP is COVID-19 the acute respiratory infectious disease caused by SARS-CoV-2 infection. COVID-19 has a broad set of manifestations and severity with a subset of affected patients developing severe disease leading to respiratory failure and other forms of organ dysfunction. As with many outbreaks of novel viral pathogens causing SARI there was no efficacious therapeutic intervention at the beginning of the COVID-19 pandemic. Furthermore, while there is emerging knowledge of clinical risks for severe COVID-19, there remains a paucity of information about the viral dynamics and host responses that might indicate a patient is at high risk for poor outcomes. The COVID-19 pandemic will be the initial target of the SARI-PREP consortium with the overall goal of developing a multi-institutional collaborative network of Acute Care Hospitals that will rapidly enroll, sample, and follow patients admitted with severe COVID-19 and to develop research protocols to rapidly determine demographic, clinical, host molecular, virologic, and institutional correlates of outcome. Overall, the information gained from this effort will help to rapidly inform and improve clinical management of epidemic/pandemic SARI patients.

The aim of this study is to estimate the burden of disease due to pneumococci, other bacteria and viruses in the African meningitis belt prior to pneumococcal conjugate vaccine introduction and to estimate the population impact of the vaccine after its implementation in 2014. In a defined population of a sanitary district in northern Togo, during the period 2010 to 2017, investigators enroll patients of all ages with suspected pneumonia requiring hospitalization or suspected bacterial meningitis. Patients are evaluated by bacteriology and molecular biology techniques on blood, cerebro-spinal fluid, nasal aspirates and by chest X-ray.

To build simple and reliable predictive scores for intensive care admissions and deaths in COVID19 patients. These scores adhere to the TRIPOD (transparent reporting of a multivariable prediction model for individual prognosis or diagnosis) reporting guidelines. The outcomes of the study are (i) admission in the Intensive Care Unit admission and (ii) death. All patients admitted in the Emergency Department with a positive reverse transcription-polymerase chain reaction SARS-COV2 test were included in the study. Routine clinical and laboratory data were collected at their admission and during their stay. Chest X-Rays and CT-Scans were performed and analyzed by a senior radiologist. Generalized Linear Models using a binomial distribution with a logit link function (R software version X) were used to develop predictive scores for (i) admission to ICU among emergency ward patients; (ii) death among ICU patients. A first panel of Number Models with the highest AIC (BIC) was preselected. Ten-fold cross-validation was then used to estimate the out-of-sample prediction error among these preselected models. The one with the smallest prediction error was in the end singled out .

Currently there is a great need for an accurately and rapid assessment of patients suspected for Covid-19. Like CT, Lung Ultrasound (LUS) examination can potentially help with the initial triage of patients but also help track the evolution of the disease. LUS can be used in every setting, including settings with limited infrastructure, allowing the reduction of disparities in trials participation. LUS is also a practical approach that can be used by obstetricians/gynecologists, who are the primary care givers in the labour and delivery room. The International Lung UltraSound Analysis (ILUSA) Study is an international multicenter prospective explorative observational study to assess the predictive value of LUS in Covid-19 suspected and diagnosed pregnant patients.

Due to the outbreak of 2019 Novel Coronavirus Pneumonia in Wuhan, Hubei province, medical staff and residents are facing great psychological pressure, the investigator plan to use electronic questionnaire to carry out investigation research.