Name (Synonyms) | Correlation | |
---|---|---|
drug92 | Assessment of ventilator-associated pneumonia criteria Wiki | 0.35 |
drug1215 | VC Wiki | 0.35 |
drug1361 | observation Wiki | 0.35 |
drug74 | Anti-coronavirus antibodies (immunoglobulins)obtained with DFPP from convalescent patients Wiki | 0.35 |
drug1091 | Sterile Water for Injection Wiki | 0.35 |
drug1016 | Scanning Chest X-rays and performing AI algorithms on images Wiki | 0.35 |
drug139 | Bacterial species isolated Wiki | 0.35 |
drug1196 | UC-MSCs Wiki | 0.18 |
Name (Synonyms) | Correlation | |
---|---|---|
D000077299 | Healthcare-Associated Pneumonia NIH | 0.35 |
D011014 | Pneumonia NIH | 0.18 |
D017563 | Lung Diseases, Interstitial NIH | 0.16 |
D011024 | Pneumonia, Viral NIH | 0.15 |
D007251 | Influenza, Human NIH | 0.13 |
D045169 | Severe Acute Respiratory Syndrome NIH | 0.04 |
D018352 | Coronavirus Infections NIH | 0.03 |
Name (Synonyms) | Correlation | |
---|---|---|
HP:0002090 | Pneumonia HPO | 0.18 |
HP:0006515 | Interstitial pneumonitis HPO | 0.16 |
There are 8 clinical trials
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
Description: Number of participants with pneumonitis on Chest X-Ray and COVID 19 positive
Measure: COVID-19 positive X-Rays Time: 6 monthsDescription: Number of participants with pneumonitis on Chest X-Ray and COVID 19 negative
Measure: COVID-19 negative X-Rays Time: 6 monthsThe purpose of the study is to determine if the clinical course of pneumonia is more severe when both, bacterial and viral pathogens are find as possible causative agent and how does it affect treatment.
2019 new coronavirus (2019-nCoV) infected pneumonia, namely severe acute respiratory infection (SARI) has caused global concern and emergency. There is a lack of effective targeted antiviral drugs, and symptomatic supportive treatment is still the current main treatment for SARI. Vitamin C is significant to human body and plays a role in reducing inflammatory response and preventing common cold. In addtion, a few studies have shown that vitamin C deficiency is related to the increased risk and severity of influenza infections. We hypothize that Vitamin C infusion can help improve the prognosis of patients with SARI. Therefore, it is necessary to study the clinical efficacy and safety of vitamin C for the clinical management of SARI through randomized controlled trials during the current epidemic of SARI.
Description: days without ventilation support during 28 days after patients' enrollment
Measure: Ventilation-free days Time: on the day 28 after enrollmentDescription: wether the patient survives
Measure: 28-days mortality Time: on the day 28 after enrollmentDescription: days of the patients staying in the ICU
Measure: ICU length of stay Time: on the day 28 after enrollmentDescription: the rate of CPR
Measure: Demand for first aid measuments Time: on the day 28 after enrollmentDescription: days of using vasopressors
Measure: Vasopressor days Time: on the day 28 after enrollmentDescription: P O2/Fi O2 which reflects patients' respiratory function
Measure: Respiratory indexes Time: on the day 10 and 28 after enrollmentDescription: Ecmo or ventilator
Measure: Ventilator parameters Time: on the day 10 and 28 after enrollmentDescription: Acute Physiology and Chronic Health Evaluation
Measure: APACHE II scores Time: on the day 10 after enrollmentDescription: Sepsis-related Organ Failure Assessment
Measure: SOFA scores Time: on the day 10 after enrollmentSerious Pneumonia and Critical Pneumonia caused by the 2019-nCOV infection greatly threats patients' life, UC-MSCs treatment has been proved to play a role in curing multiple diseases. And this study is conducted to find out whether or not it will function in 2019-nCOV infection Pneumonia.
Description: partial arterial oxygen pressure (PaO2) / oxygen concentration (FiO2)
Measure: Oxygenation index Time: on the day 14 after enrollmentDescription: whether the patient survives
Measure: 28 day mortality Time: on the day 28 after enrollmentDescription: days of the patients in hospital
Measure: Hospital stay Time: up to 6 monthsDescription: whether or not the 2019-nCoV nucleic acid test is positive
Measure: 2019-nCoV nucleic acid test Time: on the day 7,14,28 after enrollmentDescription: whether lung imaging examinations show the improvement of the pneumonia
Measure: Improvement of lung imaging examinations Time: on the day 7,14,28 after enrollmentDescription: counts of white blood cell in a litre of blood
Measure: White blood cell count Time: on the day 7,14,28 after enrollmentDescription: counts of lymphocyte in a litre (L) of blood
Measure: Lymphocyte count Time: on the day 7,14,28 after enrollmentDescription: percentage of lymphocyte in white blood cell
Measure: Lymphocyte percentage Time: on the day 7,14,28 after enrollmentDescription: procalcitonin in microgram(ug)/L
Measure: Procalcitonin Time: on the day 7,14,28 after enrollmentDescription: IL-2 in picogram(pg)/millilitre(mL)
Measure: interleukin(IL)-2 Time: on the day 7,14,28 after enrollmentDescription: IL-4 in pg/mL
Measure: IL-4 Time: on the day 7,14,28 after enrollmentDescription: IL-6 in pg/mL
Measure: IL-6 Time: on the day 7,14,28 after enrollmentDescription: IL-8 in pg/mL
Measure: IL-8 Time: on the day 7,14,28 after enrollmentDescription: IL-10 in pg/mL
Measure: IL-10 Time: on the day 7,14,28 after enrollmentDescription: TNF-α in nanogram(ng)/L
Measure: tumor necrosis factor(TNF)-α Time: on the day 7,14,28 after enrollmentDescription: γ-IFN in a thousand unit (KU)/L
Measure: γ-interferon(IFN) Time: on the day 7,14,28 after enrollmentThis 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
Description: Number of participants with pneumonitis on Chest X-Ray and COVID 19 positive
Measure: COVID-19 positive X-Rays Time: 6 monthsDescription: Number of participants with pneumonitis on Chest X-Ray and COVID 19 negative
Measure: COVID-19 negative X-Rays Time: 6 monthsNational multicentric observational retrospective case-control study comparing the relative frequency of the various microorganisms responsible for VAP in patients infected or not by SARS-CoV-2 and their resistance to antibiotics.
The 2019 outbreak of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2 or COVID 19), which originated in Wuhan, China, has become a major concern all over the world. Convalescent plasma or immunoglobulins have been used as a last resort to improve the survival rate of patients with SARS whose condition continued to deteriorate despite any attempted treatment.. Moreover, several studies showed a shorter hospital stay and lower mortality in patients treated with convalescent plasma than those who were not treated with convalescent plasma. Evidence shows that convalescent plasma from patients who have recovered from viral infections can be used effectively as a treatment of patients with active disease. The use of solutions enriched of antiviral antibodies has several important advantages over the convalescent plasma including the high level of neutralizing antibodies supplied. Plasma-exchange is expensive and requires large volumes of substitution fluid. Albumin is better tolerated and less expensive, but exchanges using albumin solutions increase the risk of bleeding because of progressive coagulation factor depletion. With either albumin or fresh frozen plasma, increasing the risk of cardiovascular instability in the plasma donor and in the recipient, which can be detrimental in a critically ill patient with COVID 19 pneumonia. The aforementioned limitations of plasma therapy can be overcome by using selective apheresis methods, such as double-filtration plasmapheresis (DFPP).DFPP is a modality of plasma purification that performs an initial plasma separation from blood, and the subsequent separation of specific molecules, on the basis of their specific molecular weight (cut-off), by using a fractionation filter. The Fractionation Filter 2A20, because of its membrane sieving cut-off, retains larger molecules and returns plasma along with smaller molecules to the circulation, including the major part of the albumin. The selection of the membrane 2A20 is related to the appropriate Sieving Coefficient for IgG that allows to efficiently collect antibodies from patients which are recovered from COVID-19, with negligible fluid losses and limited removal of albumin. The total amount of antibodies obtained during one DFPP session exceeds by three to four times the total amount provided to recipients with one unit of plasma obtained during one plasma-exchange session from one COVID-19 convalescent donor. This should result in more effective viral inhibition and larger benefit for the patient achieved with one unit of enriched immunoglobulin solution obtained with DFPP than with one unit of plasma obtained with plasma exchange. These observations provide the background for a pilot study aimed to explore whether the infusion of antibodies obtained with one single DFPP procedure from voluntary convalescent donors could offer an effective and safe therapeutic option for critically ill patients with severe coronavirus (COVID-19) pneumonia requiring mechanical ventilation.
The aim of this study is to determine the risk factors for development of ventilator-associated pneumonia (VAP) and to identify the prognostic factors of VAP among Coronavirus Disease 2019 (CoViD-19) patients. We hypothesized that CoViD-19 serves as a high risk factor for the development of VAP and it affects clinical outcome measures negatively.