Name (Synonyms) | Correlation | |
---|---|---|
drug1261 | Sputum and blood sampling Wiki | 0.45 |
drug443 | Drug Isotretinoin (13 cis retinoic acid ) capsules+standard treatment Wiki | 0.45 |
drug1514 | allogeneic human dental pulp stem cells (BSH BTC & Utooth BTC) Wiki | 0.45 |
drug707 | Intravenous saline injection (Placebo) Wiki | 0.45 |
drug171 | Best Practice Wiki | 0.45 |
drug713 | Isotretinoin(Aerosolized 13 cis retinoic acid) +standard treatment Wiki | 0.45 |
drug1242 | Serology for Covid-19 Wiki | 0.45 |
drug1302 | Standard treatment Wiki | 0.26 |
drug360 | Convalescent Plasma Wiki | 0.13 |
drug1402 | Tocilizumab Wiki | 0.10 |
Name (Synonyms) | Correlation | |
---|---|---|
D008173 | Lung Diseases, Obstructive NIH | 0.91 |
D029424 | Pulmonary Disease, Chronic Obstructive NIH | 0.67 |
D018410 | Pneumonia, Bacterial NIH | 0.45 |
D008171 | Lung Diseases, NIH | 0.34 |
D003139 | Common Cold NIH | 0.32 |
D007676 | Kidney Failure, Chronic NIH | 0.26 |
D003324 | Coronary Artery Disease NIH | 0.26 |
D020521 | Stroke NIH | 0.20 |
D012120 | Respiration Disorders NIH | 0.16 |
D012140 | Respiratory Tract Diseases NIH | 0.13 |
D009369 | Neoplasms, NIH | 0.13 |
D011024 | Pneumonia, Viral NIH | 0.13 |
D002318 | Cardiovascular Diseases NIH | 0.11 |
D012141 | Respiratory Tract Infections NIH | 0.10 |
D011014 | Pneumonia NIH | 0.06 |
D007239 | Infection NIH | 0.06 |
D045169 | Severe Acute Respiratory Syndrome NIH | 0.05 |
D003141 | Communicable Diseases NIH | 0.04 |
D018352 | Coronavirus Infections NIH | 0.04 |
Name (Synonyms) | Correlation | |
---|---|---|
HP:0006510 | Chronic obstructive pulmonary disease HPO | 0.77 |
HP:0002088 | Abnormal lung morphology HPO | 0.37 |
HP:0001677 | Coronary artery atherosclerosis HPO | 0.26 |
HP:0001297 | Stroke HPO | 0.22 |
HP:0002664 | Neoplasm HPO | 0.13 |
HP:0001626 | Abnormality of the cardiovascular system HPO | 0.12 |
HP:0011947 | Respiratory tract infection HPO | 0.10 |
HP:0002090 | Pneumonia HPO | 0.07 |
There are 5 clinical trials
Since the infectious aetiology of AECOPD has been suggested to vary according to geographical region, the primary purpose of this study (which will be conducted in several countries in Asia Pacific) is to evaluate the occurrence of bacterial and viral pathogens in the sputum of stable COPD patients and at the time of AECOPD. Given the increasing and projected burden of COPD in the Asia Pacific region, this study will also evaluate the frequency, severity and duration of AECOPD, as well as the impact of AECOPD on health-related quality of life (HRQOL), healthcare utilisation and lung function.
Description: Bacterial pathogens, as identified by bacteriological methods, including (but not necessarily limited to) Haemophilus influenzae, Moraxella catarrhalis, Streptococcus pneumoniae, Staphylococcus aureus, Pseudomonas aeruginosa, Klebsiella pneumoniae and Acinetobacter baumannii.
Measure: Occurrence of potential bacterial in sputum of stable COPD patients. Time: Over the course of 1 yearDescription: Bacterial pathogens, as identified by bacteriological methods, including (but not necessarily limited to) Haemophilus influenzae, Moraxella catarrhalis, Streptococcus pneumoniae, Staphylococcus aureus, Pseudomonas aeruginosa, Klebsiella pneumoniae and Acinetobacter baumannii.
Measure: Occurrence of potential bacterial in sputum during AECOPD. Time: Over the course of 1 yearDescription: Viral pathogens, as identified by PCR, including (but not necessarily limited to) Respiratory syncytial virus (RSV), parainfluenza virus, enterovirus/ rhinovirus, metapneumovirus, influenza virus, adenovirus, bocavirus and coronavirus and by rhinovirus quantitative RT-PCR.
Measure: Occurrence of viral pathogens in sputum of stable COPD patients. Time: Over the course of 1 yearDescription: Viral pathogens, as identified by PCR, including (but not necessarily limited to) Respiratory syncytial virus (RSV), parainfluenza virus, enterovirus/ rhinovirus, metapneumovirus, influenza virus, adenovirus, bocavirus and coronavirus and by rhinovirus quantitative RT-PCR.
Measure: Occurrence of viral pathogens in sputum during AECOPD. Time: Over the course of 1 yearDescription: Including (but not necessarily limited to) H. influenzae, M. catarrhalis, S. pneumoniae, S. aureus and P. aeruginosa. The proportion of sputum samples obtained at each confirmed stable/AECOPD visit and positive for specific bacterial pathogens by PCR will be computed with 95% confidence intervals.
Measure: Occurrence of potential bacterial pathogens in sputum of stable COPD patients and during AECOPD, as measured by real-time qualitative PCR/ quantitative PCR and compared to data from bacteriological methods. Time: Over the course of 1 yearDescription: The proportion of sputum samples obtained at each AECOPD visit and positive for specific bacterial/viral pathogens by bacteriological methods and PCR, respectively (overall and by bacterial/viral species) will be computed with 95% confidence intervals by any severity (mild, moderate and severe).
Measure: Occurrence of potential bacterial and viral pathogens (overall and by species) in sputum during AECOPD by severity of AECOPD. Time: Over the course of 1 yearDescription: The proportion of sputum samples obtained at each confirmed stable visit and positive for bacterial/viral pathogens by bacteriological methods and PCR, respectively (overall and by bacterial / viral species) will be computed with 95% confidence intervals by Gold grade at enrolment.
Measure: Occurrence of potential bacterial and viral pathogens (overall and by species) in sputum of stable COPD patients by GOLD grade. Time: Over the course of 1 yearDescription: The following incidence rates will be computed, with 95% confidence intervals (CI): All-cause AECOPD. AECOPD having sputum containing bacterial pathogens found by PCR or by bacteriological methods or by both methods (overall and by, but not limited to, the following bacterial species: H. influenzae, M. catarrhalis, S. pneumoniae, S. aureus, and P. aeruginosa). The 95% CI of the incidence rate will be computed using a model which accounts for repeated events. The incidence rates described above will also be computed for mild, moderate severe AECOPD and by GOLD grade at enrolment.
Measure: Incident rate (per subject per year) of any AECOPD overall and by GOLD grade. Time: Over the course of 1 yearDescription: Classification of severity according to the intensity of medical intervention required: mild: controlled with an increase in dosage of regular medications; moderate: requires treatment with systemic corticosteroids and/ or antibiotics; severe: requires hospitalisation.
Measure: Number of mild, moderate or severe AECOPD overall and by GOLD grade. Time: Over the course of 1 yearDescription: Descriptive statistics (median, mean, range, standard deviation, first and third quartiles) on the number of days of AECOPD episodes will be presented.
Measure: Number of days of AECOPD episodes overall and by AECOPD severity. Time: Over the course of 1 yearDescription: Descriptive statistics (median, mean, range, standard deviation, first and third quartiles) on the CAT scores will be tabulated at each respective visit.
Measure: COPD assessment test (CAT) score in stable COPD patients and during AECOPD. Time: Over the course of 1 yearDescription: Descriptive statistics (median, mean, range, standard deviation, first and third quartiles) on the SGRQ-C scores will be tabulated at each respective visit.
Measure: St. George's Respiratory Questionnaire (SGRQ-C) score in stable COPD patients. Time: Over the course of 1 yearDescription: The spirometric classification of airflow limitation in COPD patients is based on post-bronchodilator FEV1. Summary statistics (mean, median, standard deviation, maximum and minimum) on post bronchodilator FEV1% of predicted normal value will be tabulated at each respective visit.
Measure: Forced expiratory volume in 1 second (FEV1%) of predicted normal value in stable COPD patients. Time: At Pre-Month 0 and Month 12Description: Healthcare use for each COPD patient will be obtained through review of the subject's medical record (aided by subject self-reporting). Healthcare utilisation includes all unscheduled visits to a physician office, visits to urgent care, visits to emergency department, and hospitalizations.
Measure: Assessment of the Healthcare utilization. Time: Over the course of 1 yearIt has been reported that nearly half of the patients who are hospitalized for Covid-19 pneumonia have on admission old age or comorbidities. In particular, hypertension was present in 30% of the cases, diabetes in 19%, coronary heart disease in 8% and chronic obstructive lung disease in 3% of the patients. Amazingly, in the two major studies published in the Lancet (Zhou F et al Lancet 2020) and in the New England Journal of Medicine (Guan W et al 2020), the weight of the subjects as well their body mass index (BMI) were omitted. However, obesity, alone or in association with diabetes, can be a major predisposition factor for Covid-19 infection. The primary end-point of our prospective, observational study is to assess the recovery rate in patients with diagnosis of Covid-19 pneumonia. Among the other secondary end-points, we intend to find the predictors of the time to clinical improvement or hospital discharge in patients affected by Covid-19 pneumonia.
Description: mean rate of recovery in patients with diagnosis of Covid-19 pneumonia, who present with complications at the time of hospital admission (such as diabetes, obesity, cardiovascular disease, hypertension or respiratory failure), with the mean recovery rate in patients without any of the above-mentioned complications.
Measure: rate of recovery Time: 3 weeksDescription: comparison of the survival curves (times to improvement) in the two groups (patients with and without complications) and among patients presenting with different types of complications
Measure: time to improvement Time: 3 weeksDescription: the efficacy of different pharmaceutical treatment against Covid-19
Measure: efficacy of treatments Time: 3 weeksDescription: liver, kidney or multiorgan failure, cardiac failure
Measure: organ failure Time: 3 weeksAn open access study that will define and collect digital measures of coughing in multiple populations and public spaces using various means of audio data collection.
Description: Size of collected audio dataset measured as number of collected cough sounds, targeting ≥10,000 identified coughs.
Measure: Dataset size Time: 14 daysDescription: Identification of cough sounds by the existing mathematical model with ≥ 99% specificity and ≥ 60% sensitivity
Measure: Cough sound identification Time: 14 daysDescription: Increase in the sensitivity of the mathematical model to cough sounds to ≥ 70% while retaining the specificity of ≥ 99%
Measure: Improvement of the existing model Time: 14 daysDescription: Determination of the level of acceptance and satisfaction of the solution by patients by means of a Standard Usability Questionnaire to provide feedback. The score ranges from 10 to 50, higher score indicating a better usability.
Measure: Evaluate the usability of the application Time: 14 daysThis phase III trial compares the effect of adding tocilizumab to standard of care versus standard of care alone in treating cytokine release syndrome (CRS) in patients with SARS-CoV-2 infection. CRS is a potentially serious disorder caused by the release of an excessive amount of substance that is made by cells of the immune system (cytokines) as a response to viral infection. Tocilizumab is used to decrease the body's immune response. Adding tocilizumab to standard of care may work better in treating CRS in patients with SARS-CoV-2 infection compared to standard of care alone.
Description: The 7-day length of invasive MV for each arm will be estimated with 95% confidence intervals (CIs) using the exact binomial distribution. Their difference by the arms will be tested by Cochran-Mantel-Haenszel (CMH) test stratified by the age group and Sequential Organ Failure Assessment (SOFA) score at significance level of 0.05.
Measure: 7-day length of invasive mechanical ventilation (MV) Time: Up to 7 daysDescription: Defined as death within 30-day after randomization. The 30-day mortality rate for each arm will be estimated with 95% CIs using the exact binomial distribution. Their difference by the arms will be tested CMH test stratified by the age group and SOFA score at significance level of 0.05.
Measure: 30-day mortality rate Time: Up to 30-day after randomizationDescription: The rate of ICU transfer for each arm will be estimated with 95% CIs using the exact binomial distribution. Their difference by the arms will be tested CMH test stratified by the age group and SOFA score at significance level of 0.05.
Measure: Rate of intensive care (ICU) transfer Time: Up to 2 yearsDescription: The rate of invasive mechanical ventilation for each arm will be estimated with 95% CIs using the exact binomial distribution. Their difference by the arms will be tested CMH test stratified by the age group and SOFA score at significance level of 0.05.
Measure: Rate of invasive mechanical ventilation Time: Up to 2 yearsDescription: The rate of tracheostomy for each arm will be estimated with 95% CIs using the exact binomial distribution. Their difference by the arms will be tested CMH test stratified by the age group and SOFA score at significance level of 0.05.
Measure: Rate of tracheostomy Time: Up to 2 yearsDescription: Will first be described by median and inter-quartile, and then compared between two arms by Wilcoxon Sum-Rank test
Measure: Length of ICU stay Time: Up to 2 yearsMolecular testing (e.g PCR) of respiratory tract samples is the recommended method for the identification and laboratory confirmation of COVID-19 cases. Recent evidence reported that the diagnostic accuracy of many of the available RT-PCR tests for detecting SARS-CoV2 may be lower than optimal. Of course, the economical and clinical implications of diagnostic errors are of foremost significance and in case of infectious outbreaks, namely pandemics, the repercussions are amplified. False positives and false-negative results may jeopardize the health of a single patient and may affect the efficacy of containment of the outbreak and of public health policies. In particular, false-negative results contribute to the ongoing of the infection causing further spread of the virus within the community, masking also other potentially infected people.
Description: assess if inpatients who presented with pneumonia but had a negative test for Covid-19 are positive at the serology for SARS-CoV-2.
Measure: Serology Time: 3 weeksDescription: to find if the combination of CT scan and serology could help us in the identification of those patients who were initially negative at laboratory testing alone.
Measure: Efficacy of CT scan and Serology Time: 3 weeksDescription: the efficacy of different pharmaceutical treatments against Covid-19
Measure: Efficacy of different pharmaceutical treatments Time: 3 weeks