CovidResearchTrials by Shray Alag


CovidResearchTrials Covid 19 Research using Clinical Trials (Home Page)


Report for D060085: Coinfection NIH

(Synonyms: Coinfection)

Developed by Shray Alag
Clinical Trial MeSH HPO Drug Gene SNP Protein Mutation


Correlated Drug Terms (4)


Name (Synonyms) Correlation
drug1217 Sampling (EDTA blood, pharyngeal and nose swabs, bronchoalveolar lavage ,urine) Wiki 0.71
drug518 FilmArray Pneumonia Wiki 0.71
drug438 Dornase Alfa Wiki 0.71
drug439 Dornase Alfa Inhalation Solution Wiki 0.71

Correlated MeSH Terms (2)


Name (Synonyms) Correlation
D045169 Severe Acute Respiratory Syndrome NIH 0.04
D018352 Coronavirus Infections NIH 0.03

Correlated HPO Terms (0)


Name (Synonyms) Correlation

There are 2 clinical trials

Clinical Trials


1 Co-infections in COVID-19 Critically Ill and Antibiotic Management

International guidelines suggest the administration of empirical broad-spectrum antibiotics for suspected bacterial co-infection in COVID-19 critically ill. However, data on associated respiratory infections is rare and antimicrobial stewardship interventions promoting antibiotic savings are non-existent in this context. The main objectives of the trial are: to evaluate the rate of co-infections among COVID-19 critically ill to evaluate the added value of a a rapid molecular diagnostic tool (FA-PNEU) to detect the presence of co-infecting pathogens in order to rapidly tailor the patient's antibiotic treatment

NCT04382092 COVID-19 Diagnostic Test: FilmArray Pneumonia
MeSH:Coinfection

Primary Outcomes

Description: COVID-19 infections with additional bacteria/viruses identified through FA-PNEU testing

Measure: % of COVID-19 co-infections

Time: through study completion, an average of 1 month

Secondary Outcomes

Description: The rapid FA results could allow a fast modification of the empirical antibiotherapy. This percentage will be measured.

Measure: % of antibiotic switches following FA results

Time: through study completion, an average of 1 month

2 Microbiota in COVID-19 Patients for Future Therapeutic and Preventive Approaches

In light of the rapidly emerging pandemic of SARS-CoV-2 infections, the global population and health care systems are facing unprecedented challenges through the combination of transmission and the potential for severe disease. Acute respiratory distress syndrome (ARDS) has been found with unusual clinical features dominated by substantial alveolar fluid load. It is unknown whether this is primarily caused by endothelial dysfunction leading to capillary leakage or direct virus induced damage. This knowledge gap is significant because the initial balance between fluid management and circulatory support appear to be decisive. On progression of the disease, bacterial superinfection facilitated by inflammation and virus related damage, has been identified as the main factor for patient outcome, but the role of the host versus the environment microbiome remains unclear. The overarching aim of the present research proposal is to improve therapeutic strategies in critically ill patients with ARDS due to SARS-CoV-2 infection by advancing the pathophysiological understanding of this novel disease. This research thus focuses on inflammation, microcirculatory dysfunction and superinfection, aiming to elucidate risk factors (RF) for the development of severe ARDS in SARS-CoV-2 infected patients and contribute to the rationale for therapeutic strategies. The hypotheses are that (I) the primary damage to the lung in SARS-CoV-2 ARDS is mediated through an exaggerated pro-inflammatory response causing primary endothelial dysfunction, and subsequently acting two-fold on the degradation of the lung parenchyma - through the primary cytokine response, and through recruitment of the inflammatory-monocyte-lymphocyte-neutrophil axis. The pronounced inflammation and primary damage to the lung disrupts the pulmonary microbiome, leading secondarily to pulmonary superinfections. (II) Pulmonary bacterial superinfections are a significant cause of morbidity and mortality in COVID-19 patients. Pathogen colonization main Risk Factor for lower respiratory tract infections. To establish colonization, pathogens have to interact with the local microbiota (a.k.a. microbiome) and certain microbiome profiles will be more resistant to pathogen invasion. Finally, (III) Handheld devices used in clinical routine are a potential reservoir and carrier of both, SARS-CoV-2, as well as bacteria causing nosocomial pneumonia.

NCT04410263 Corona Virus Infection ARDS Coinfection Diagnostic Test: Sampling (EDTA blood, pharyngeal and nose swabs, bronchoalveolar lavage ,urine)
MeSH:Coinfection Coronavirus Infections Severe Acute Respiratory Syndrome

Primary Outcomes

Description: Daily recorded Vitals and Inflammatory Response will be analyzed by means of multivariable mixed effect models analysis and generalized linear models, with corrections for time and randomness. To account for the different units of measure we will standardize all values to an absolute measure by means of the z-score. The following variables will be considered: Respiratory values, Vital signs, Haemodynamic monitoring, Microcirculation, Inflammatory values, Hematology: T-cells CD3, 4 and 6 Chemistry: Inflammatory Cytokines and Biomarkers:CRP, PCT, MR-ProADM, IFN-1, IFN-γ, TNF-α/β, IL-1β, IL-2, IL-4, IL-6, IL-8, IL-10, IL-12, MIG, RANTES, MCP-1, IP-10, PD1, PD-L1 Lipid-pannel3: LDL, HDL, Cholesterol, Triglyceride Other: HLA DR/DQ TBS, Swabs, sublingual nonnvasive microscopy

Measure: Change of pro-inflammatory response over the ICU stay as a causative for primary endothelial dysfunction

Time: Admission, on day 0, day 1, day 2 , day 3, day 5, every 5 days up to 1 year

Description: COX proportional hazards model and generalized mixed effect models assessing the effect of positive bacterial infection on mortality. Correction for time and randomness (multiple sampling). Super infection will be defined as a positive bacterial/ fungal sample (Bood cultures, BAL, TBS, Swabs, Urine)

Measure: Time-to-event "pulmonary bacterial superinfection or death"

Time: Through study completion, an average of 30 days

Description: Mobile devices will be swabed for bacterial and viral contamination, simultaneously adherence of the user to disinfection protocols will be assessed.

Measure: Positive bacteria and/ or SARS-CoV-2 cultures on handheld devices used in clinical routine and correlation to the adherence to disinfection protocols

Time: Through study completion, an average of 30 days

Secondary Outcomes

Description: SF 36 questionnaire

Measure: Life Quality after COVID-19 Infection

Time: follow up 30 + 90 days and 1 year after discharge


HPO Nodes