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Sections: Correlations,
Clinical Trials, and HPO
Navigate: Clinical Trials and HPO
| Name (Synonyms) | Correlation | |
|---|---|---|
| drug4482 | Transpulmonary thermodilution Wiki | 0.38 |
| drug3379 | Preventive information Wiki | 0.38 |
| drug195 | Abivertinib Wiki | 0.38 |
| Name (Synonyms) | Correlation | |
|---|---|---|
| drug4444 | Toraymyxin PMX-20R (PMX Cartridge) Wiki | 0.38 |
| drug944 | Cerebral compliance and hemodynamics monitoring Wiki | 0.38 |
| drug392 | Assessment of coagulopathy, Platelets activation and Platelets-Neutrophils interplay Wiki | 0.38 |
| drug4503 | Treatment group: will receive a combination of Nitazoxanide, Ribavirin and Ivermectin for a duration of seven days : Wiki | 0.38 |
| drug946 | Certified cloth face mask plus preventive information Wiki | 0.38 |
| drug2024 | ICU treatment Wiki | 0.27 |
| drug4698 | Vitamin Super B-Complex Wiki | 0.22 |
| drug1446 | Echocardiography Wiki | 0.22 |
| drug2804 | Nitazoxanide Wiki | 0.10 |
| drug4102 | Standard of Care Wiki | 0.06 |
| drug3195 | Placebo Wiki | 0.02 |
| Name (Synonyms) | Correlation | |
|---|---|---|
| D012772 | Shock, Septic NIH | 0.44 |
| D012770 | Shock, Cardiogenic NIH | 0.38 |
| D019446 | Endotoxemia NIH | 0.38 |
| Name (Synonyms) | Correlation | |
|---|---|---|
| D019586 | Intracranial Hypertension NIH | 0.38 |
| D018754 | Ventricular Dysfunction NIH | 0.19 |
| D018487 | Ventricular Dysfunction, Left NIH | 0.19 |
| D004211 | Disseminated Intravascular Coagulation NIH | 0.17 |
| D018805 | Sepsis NIH | 0.12 |
| D020141 | Hemostatic Disorders NIH | 0.09 |
| D001778 | Blood Coagulation Disorders NIH | 0.09 |
| D000860 | Hypoxia NIH | 0.07 |
| D012128 | Respiratory Distress Syndrome, Adult NIH | 0.05 |
| D016638 | Critical Illness NIH | 0.05 |
| D012127 | Respiratory Distress Syndrome, Newborn NIH | 0.03 |
| D055371 | Acute Lung Injury NIH | 0.03 |
| D045169 | Severe Acute Respiratory Syndrome NIH | 0.02 |
| D018352 | Coronavirus Infections NIH | 0.01 |
| Name (Synonyms) | Correlation | |
|---|---|---|
| HP:0030149 | Cardiogenic shock HPO | 0.38 |
| HP:0002516 | Increased intracranial pressure HPO | 0.38 |
| HP:0005521 | Disseminated intravascular coagulation HPO | 0.17 |
| Name (Synonyms) | Correlation | |
|---|---|---|
| HP:0100806 | Sepsis HPO | 0.12 |
| HP:0001928 | Abnormality of coagulation HPO | 0.09 |
| HP:0012418 | Hypoxemia HPO | 0.07 |
Navigate: Correlations HPO
There are 7 clinical trials
Knowing the dramatic increase in thrombin generation during sepsis, our research hypothesis is that AMPK-induced ACC phosphorylation in platelets is increased and that this might modulate platelets metabolism and more particularly platelets inflammatory mediators content, coming from AA and lipids.
Description: ACC phosphorylation on Ser79 (phosphoACC) in platelets of patients will be assessed using western blotting. Results will be expressed in arbitrary units (A.U). A signal above 0.5 A.U. has already been shown to be above 2 standard deviation in a healthy population.
Measure: Platelets Acetyl-CoA Carboxylase phosphorylation rate Time: At the time of inclusionDescription: Sepsis severity will be assessed using the SOFA score (Sepsis-related Organ Failure Assessment). Range from 0( less severe) to 24 (more severe).
Measure: Sepsis severity Time: At the time of inclusionDescription: Sepsis severity will be assessed using the APACHE II score) Acute Physiology And Chronic Health Evaluation) Range 0 (less severe) to 299 (more severe).
Measure: Sepsis severity Time: At the time of inclusionDescription: Platelet function will be assessed using platelets aggregometry. The Aggregation (in AU), the maximum height of the curve during the measurement period will be assessed.
Measure: Platelet function assessment Time: At the time of inclusionDescription: Platelet function will be assessed using platelets aggregometry. Area Under the aggregation Curve (AUC) will be assessed and recorded as Units or U.
Measure: Platelet function assessment Time: At the time of inclusionDescription: Platelet function will be assessed using platelets aggregometry. Velocity (in AU/min), the maximum slope of the curve will be assessed.
Measure: Platelet function assessment Time: At the time of inclusionDescription: D-Dimers (ng/ml)
Measure: Thrombin generation marker rate Time: At the time of inclusionDescription: Urinary Thrombin-antithrombin complex (ng/mL)
Measure: Thrombin generation marker rate Time: At the time of inclusionDescription: Tubulin acetylation will be assessed using western blotting. Results will be expressed in arbitrary units (A.U).
Measure: Tubulin acetylation rate Time: At the time of inclusionDescription: Total platelets lipid content and composition will be assessed using metabolomics approach by Mass Spectrometry. Fold-change estimates and corresponding P values were derived from regression models for each lipid species and each predictor. To control for multiple testing, all P values will be further adjusted for Benjamini-Hochberg false discovery rate (FDR), with a FDR <0.05 considered statistically significant
Measure: Total platelets lipid content and composition Time: At the time of inclusionDescription: Myeloperoxidase MPO (ng/mL)
Measure: Neutrophils extracellular trap formation Time: At the time of inclusionDescription: Citrulinated Histon 3 H3-Cit (ng/mL)
Measure: Neutrophils extracellular trap formation Time: At the time of inclusionDescription: Soluble CD62P (ng/mL)
Measure: Platelets activation Time: At the time of inclusionDescription: PaO2/FiO2
Measure: Respiratory failure Time: At the time of inclusion and through study completion up to day 30The outbreak of coronavirus disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has been declared a public health emergency of international concern. Hospitalized COVID-19-positive patients requiring ICU care is increasing along with the course of epidemic. A large number of these patients developed acute respiratory distress syndrome (ARDS) according to current data. However, the related hemodynamic characteristic has so far been rarely described.
Description: Body temperature(°C)
Measure: Body temperature Time: Through study completion, an estimation of 6 monthsDescription: Blood pressure in mmHg
Measure: Blood pressure Time: Through study completion, an estimation of 6 monthsDescription: Pulse (heart rate) in times/minute
Measure: Pulse (heart rate) Time: Through study completion, an estimation of 6 monthsDescription: Respiratory rate in times/minute
Measure: Respiratory rate Time: Through study completion, an estimation of 6 monthsDescription: Cardiac index (L/min/m2)
Measure: Data provided by transpulmonary thermodilution-CI Time: Through study completion, an estimation of 6 monthsDescription: Global end-diastolic volume(mL/m2)
Measure: Data provided by transpulmonary thermodilution-GEDV Time: Through study completion, an estimation of 6 monthsDescription: Extravascular lung water (mL/kg)
Measure: Data provided by transpulmonary thermodilution-EVLW Time: Through study completion, an estimation of 6 monthsDescription: Pulmonary vascular permeability index
Measure: Data provided by transpulmonary thermodilution-PVPI Time: Through study completion, an estimation of 6 monthsDescription: Left ventricle ejection fraction, Segmental left ventricle contractility, Speckle tracking data of the left and right ventricles, Dimensions of right and left cavities and Diastolic function of left ventricle
Measure: Incidence of new-onset or reversible systolic left ventricular dysfunction Time: Through study completion, an estimation of 6 monthsDescription: The worst extravascular lung water
Measure: Changes of extravascular lung water measured by transpulmonary thermodilution Time: Change from baseline extravascular lung water at 6 monthsDescription: The worst pulmonary vascular permeability index
Measure: Changes of pulmonary vascular permeability index measured by transpulmonary thermodilution Time: Change from baseline extravascular lung water at 6 monthsProspective, observational, clinical investigation of PMX cartridge use in COVID 19 patients with septic shock
The Risk stratification in COVID-19 patients in the ICU (RISC-19-ICU) registry was founded during the emerging SARS-CoV-2 pandemic. COVID-19 is a novel disease caused by infection with the SARS-CoV-2 virus that was first described in December 2019. The disease has spread exponentially in many countries and has reached global pandemic status within three months. According to first experience, hospitalization was required in approximately 20 % of cases and severe, life-threatening illness resulted in approximately 10 %. In some countries, health care systems were overwhelmed by the rapid increase in critically ill patients that far exceeded their capacity. It is thus of utmost importance to gain knowledge about the characteristics and course of critically ill patients with COVID-19 and to stratify these patients according to their risk for further deterioration. A key part of fighting this pandemic is to exchange scientific information and advance our understanding of the disease. The Risk stratification in COVID-19 patients in the ICU (RISC-19-ICU) registry aims to collect an anonymized dataset to characterize patients that develop life-threatening critical illness due to COVID-19 and make it accessible to collaborative analysis. The data collected may be composed of a core dataset and/or an extended dataset. The core dataset consists of a basic set of parameters, of which many are commonly generated during treatment of critically ill patients with COVID-19 in an intensive care unit (the individual parameters are marked yellow in the attached case report forms, and are clearly marked on the electronic case report forms during data entry). The extended dataset consists of parameters that may be measured during treatment of critically ill patients with COVID-19 in an intensive care unit, depending on clinical practice, indication and availability of the measurement method. The data accumulating in the registry as the pandemic or subsequent waves develop are made available to the collaborators to support an optimal response to the pandemic threat. The information gained on the initial characteristics and disease course via the RISC-19-ICU registry may contribute to a better understanding of the risk factors for developing critical illness due to COVID-19 and for an unfavorable disease course, and thus support informed patient triage and management decisions. Initial research questions are (I) to perform risk stratification of critically ill patients with COVID-19 to find predictors associated with the development of critical illness due to COVID-19: characterization of the study population, which are critically ill patients with COVID-19: inflammation, oxygenation, circulatory function, among other parameters collected in the registry, and (II) to perform risk stratification of critically ill patients with COVID-19 to predict outcome after ICU admission (ICU mortality, ICU length of stay): characterization of patients grouped by disease course in the ICU, based on inflammation, oxygenation, circulatory function, and other parameters collected in the registry.
In the last 10 years, severe acute respiratory infection (SARI) was responsible of multiple outbreaks putting a strain on the public health worldwide. Indeed, SARI had a relevant role in the development of pandemic and epidemic with terrible consequences such as the 2009 H1N1 pandemic which led to more than 200.000 respiratory deaths globally. In late December 2019, in Wuhan, Hubei, China, a new respiratory syndrome emerged with clinical signs of viral pneumonia and person-to-person transmission. Tests showed the appearance of a novel coronavirus, namely the 2019 novel coronavirus (COVID-19). Two other strains, the severe acute respiratory syndrome coronavirus (SARS-CoV) and Middle East respiratory syndrome coronavirus (MERS-CoV) have caused severe respiratory illnesses, sometimes fatal. In particular, the mortality rate associated with SARS-CoV and MERS-CoV, was of 10% and 37% respectively. Even though COVID-19 appeared from the first time in China, quickly it spread worldwide and cases have been described in other countries such as Thailand, Japan, South Korea, Germany, Italy, France, Iran, USA and many other countries. An early paper reported 41 patients with laboratory-confirmed COVID-19 infection in Wuhan. The median age of the patients was 49 years and mostly men (73%). Among those, 32% were admitted to the ICU because of the severe hypoxemia. The most associated comorbidities were diabetes (20%), hypertension (15%), and cardiovascular diseases (15%). On admission, 98% of the patients had bilateral multiple lobular and sub-segmental areas of consolidation. Importantly, acute respiratory distress syndrome (ARDS) developed in 29% of the patients, while acute cardiac injury in 12%, and secondary infection in 10%. Invasive mechanical ventilation was required in 10% of those patients, and two of these patients (5%) had refractory hypoxemia and received extracorporeal membrane oxygenation (ECMO). In a later retrospective report by Wang and collaborators, clinical characteristics of 138 patients with COVID-19 infection were described. ICU admission was required in 26.1% of the patients for acute respiratory distress syndrome (61.1%), arrhythmia (44.4%), and shock (30.6%). ECMO support was needed in 11% of the patients admitted to the ICU. During the period of follow-up, overall mortality was 4.3%. The use of ECMO in COVID-19 infection is increasing due to the high transmission rate of the infection and the respiratory-related mortality. Therefore, the investigators believe that ECMO in case of severe interstitial pneumonia caused by COVID could represent a valid solution in order to avoid lung injuries related to prolonged treatment with non-invasive and invasive mechanical ventilation. In addition, ECMO could have a role for the systemic complications such as septic and cardiogenic shock as well myocarditis scenarios. Potential clinical effects and outcomes of the ECMO support in the novel coronavirus pandemic will be recorded and analyzed in our project. The researchers hypothesize that a significant percentage of patients with COVID-19 infection will require the utilize of ECMO for refactory hypoxemia, cardiogenic shock or septic shock. This study seeks to prove this hypothesis by conducting an observational retrospective/prospective study of patients in the ICU who underwent ECMO support and describe clinical features, severity of pulmonary dysfunction and risk factors of COVID-patients who need ECMO support, the incidence of ECMO use, ECMO technical characteristics, duration of ECMO, complications and outcomes of COVID-patients requiring ECMO support.
Description: age in years
Measure: Age Time: at baselineDescription: male/female
Measure: Gender Time: at baselineDescription: in kilograms
Measure: Weight Time: at baselineDescription: in meters
Measure: Height Time: at baselineDescription: weight and height combined to calculate BMI in kg/m^2
Measure: BMI Time: at baselineDescription: Asthma y/n, cystic fibrosis y/n, chronic obstructive pulmonary disease y/n, pulmonary hypertension y/n, pulmonary fibrosis y/n, chronic restrictive lung disease y/n
Measure: Pre-existing pulmonary disease y/n Time: at baselineDescription: diabetes mellitus y/n, chronic renal failure y/n, ischemic heart disease y/n, heart failure y/n, chronic liver failure y/n, neurological impairment y/n
Measure: Main co-morbidities y/n Time: at baselineDescription: in dd-mm-yyyy or mm-dd-yyyy
Measure: Date of signs of COVID-19 infection Time: at baseline or date of occurenceDescription: in dd-mm-yyyy or mm-dd-yyyy
Measure: Date of positive swab Time: at baseline or date of occurenceDescription: in days
Measure: Pre-ECMO length of hospital stay Time: at or during ECMO-implantDescription: in days
Measure: Pre-ECMO length of ICU stay Time: at or during ECMO-implantDescription: in days
Measure: Pre-ECMO length of mechanical ventilation days Time: at or during ECMO-implantDescription: y/n, what kind
Measure: Use of antibiotics Time: up to 6 monthsDescription: y/n, what kind
Measure: Use of anti-viral treatment Time: up to 6 monthsDescription: y/n, what kind (eg prone-position, recruitment manoeuvers, neuromuscular blockade etc)
Measure: Use of second line treatment Time: up to 6 monthsDescription: respiratory or cardiac
Measure: Indications for ECMO-implant Time: at ECMO-implantDescription: veno-venous, veno-arterial or veno-venoarterial
Measure: Type of ECMO-implant Time: at ECMO-implantDescription: peripheral or central
Measure: Type of access Time: at ECMO-implantDescription: in dd-mm-yyyy or mm-dd-yyyy
Measure: Date of ECMO implant Time: at ECMO-implantDescription: l/min
Measure: ECMO blood flow rate Time: from day of ECMO-implant for every 24 hours until date of weaning or death, up to 6 monthsDescription: l/min
Measure: ECMO gas flow rate Time: from day of ECMO-implant for every 24 hours until date of weaning or death, up to 6 monthsDescription: y/n
Measure: ECMO configuration change Time: up to 6 monthsDescription: in dd-mm-yyyy or mm-dd-yyyy
Measure: Date of ECMO configuration change Time: up to 6 monthsDescription: veno-venous, veno-arterial, veno-venoarterial, other
Measure: New ECMO configuration Time: up to 6 monthsDescription: right ventricular failure, left ventricular failure, refractory hypoxemia
Measure: Indications for ECMO configuration change Time: up to 6 monthsDescription: settings of ventilator
Measure: Ventilator setting on ECMO Time: from day of ECMO-implant for every 24 hours until date of weaning or death, up to 6 monthsDescription: heparin, bivalirudin, nothing
Measure: Anticoagulation during ECMO Time: from day of ECMO-implant for every 24 hours until date of weaning or death, up to 6 monthsDescription: amount of ECMO circuit changes (1, 2, 3 etc.)
Measure: Frequency of ECMO circuit change Time: up to 6 monthsDescription: Hemorrhagic, infection, other complications
Measure: ECMO complications Time: up to 6 monthsDescription: y/n
Measure: ECMO Weaning Time: from day of ECMO-implant for every 24 hours until date of weaning or death, up to 6 monthsDescription: y/n, date
Measure: ICU discharge Time: from day of ICU-admission for every 24 hours until date of discharge or death, up to 6 monthsDescription: Ward, another ICU, rehabilitation center, home
Measure: Type of discharge Time: up to 6 monthsSeveral recent studies point to the possibility of the new coronavirus (SARS-Cov2), which currently causes pandemic COVID-19, to infiltrate the central nervous system (CNS) and cause primary damage to neural tissues, increasing the morbidity and mortality of these patients. A pathophysiological hypothesis for insulting the CNS would be the impairment of cerebral compliance (CC), because elevation of intracranial pressure (ICP), but due to the invasive nature of the methods available for ICP evaluation, this hypothesis has so far not been verified. Recently, a noninvasive technique was developed to evaluate CC (B4C sensor), making it possible to analyse CC in patients outside the neurosurgical environment. Therefore, the main objective of this study was to assess the presence of CC impairment in patients with COVID-19, and observe potential influences of this syndrome on cerebral hemodynamics.
Description: Observe alteration in cerebral compliance due to potential intracranial hypertension during severe COVID-19. This situation is indicated when the relation P2/P1 given by the B4C sensor is >1.
Measure: Detection of cerebral compliance impairment by the B4C sensor Time: During critical care, around 15 days/patientDescription: Observe disturbances in cerebral circulation during severe COVID-19, given by blood flow velocities in middle cerebral arteries (with normal range 40-70 cm/s) and the pulsatility index (normal <1.2) calculated by transcranial Doppler.
Measure: Detection of cerebral hemodynamics impairment by transcranial Doppler Time: During critical care, around 15 days/patientDescription: Observe whether disturbances in cerebral compliance and hemodynamics assessed in this population is significantly associated with higher mortality.
Measure: Calculate mortality in this population Time: 3 monthsThe study will follow COVID-19 patients who required intensive care after 3-6 months and one year after discharge from the ICU with functional level as well as organ function to assess recovery after COVID-19. Blood and urine will be collected for biobanking.
Description: Death
Measure: Mortality Time: Within 90 days after admission to ICU.Description: Death
Measure: Mortality Time: Within 1 year after admission to ICU.Description: Return of renal function measured as CKD stage.
Measure: Renal recovery Time: At follow-up three to six months after ICU discharge.Description: Return of renal function measured as CKD stage.
Measure: Renal recovery Time: At follow-up one year after ICU discharge.Description: Respiratory function as assessed by a clinician
Measure: Respiratory recovery Time: Three to six months from discharge from ICUDescription: 6 min walk test
Measure: Working capacity Time: Three to six months from discharge from ICUDescription: Quality of Life assessed using the 36-item short form survey by RAND.
Measure: Quality of life score Time: Three to six months from discharge from ICUDescription: Cognitive screening using the Montreal Cognitive Assessment.
Measure: Cognitive recovery Time: Three to six months from discharge from ICUDescription: Screening for frailty using the Clinical Frailty Scale-9.
Measure: Frailty Time: Three to six months from discharge from ICUDescription: Screening of functional level for Activities of Daily Life using the 5-level EQ-5D.
Measure: Activities of Daily Life Time: Three to six months from discharge from ICUDescription: Screening for anxiety using the Generalised Anxiety Disorder 7-item scale.
Measure: Anxiety Time: Three to six months from discharge from ICUDescription: Screening for depression using the Patient Health Questionnaire 9.
Measure: Depression Time: Three to six months from discharge from ICUDescription: Neurological function as assessed by a clinician
Measure: Neurological recovery Time: Three to six months from discharge from ICUAlphabetical listing of all HPO terms. Navigate: Correlations Clinical Trials
Data processed on December 13, 2020.
An HTML report was created for each of the unique drugs, MeSH, and HPO terms associated with COVID-19 clinical trials. Each report contains a list of either the drug, the MeSH terms, or the HPO terms. All of the terms in a category are displayed on the left-hand side of the report to enable easy navigation, and the reports contain a list of correlated drugs, MeSH, and HPO terms. Further, all reports contain the details of the clinical trials in which the term is referenced. Every clinical trial report shows the mapped HPO and MeSH terms, which are also hyperlinked. Related HPO terms, with their associated genes, protein mutations, and SNPs are also referenced in the report.
Drug Reports MeSH Reports HPO Reports