An observational study in Covid19, Obesity and Diabetes Mellitus, sponsored by Indonesia University. Status unknown at 2 sites in Indonesia. Open to participants aged 18 Years and older, including healthy volunteers. Per ClinicalTrials.gov, last updated 2022-04-18.
Sponsored by Indonesia University · Observational
COVID-19 pandemic has made a tremendous impact on Indonesian economic and health care system especially with the double burden of diseases facing by Indonesia as a developing country. The prevalence of non-communicable diseases such as obesity, type diabetes, and cardiovascular diseases is increasing. These diseases along with older age have been known as an established risk factors for higher mortality and severe clinical disease entity in COVID-19 infection. Although, there is still some part of patients with these co-morbidities that only present with mild symptoms when infected with SARS-CoV-2, even for some without any symptoms. Thus, it would be very interesting to evaluate how are these role of aging and cardiometabolic parameters in the clinical disease course of COVID-19 infection, and how are the relationship with the immune system.
Indonesia is a country in transition where the burden of non-communicable diseases is taking over the infectious diseases problem, mostly due to the changes in lifestyle and increase in life expectancy.
However, the unprecedented rising numbers of COVID-19 patients in Indonesia has impacted the Indonesian healthcare system heavily. It has been reported that older age and the presence of cardiometabolic risk factors pose a poor prognostic factor of COVID-19. It is also important to note that in Indonesia, the presence of cardiometabolic risk factors is often observed at a younger age. Thus, this might also contribute to the higher mortality of COVID19 infected patients despite their relatively younger age in comparison to other countries. Nevertheless, specific data on the impact of aging and cardiometabolic risk factors on COVID-19 are fragmentary, justifying the achievement of a dedicated prospective observational study.
The CARAMEL study aims to specifically describe the phenotypic aging and cardiometabolic characteristics of patients with COVID-19 infection, in relation with the changes in the mucosal and systemic immune system. Particular attention will be devoted to obesity, central obesity, prediabetes, diabetes, hypertension, dyslipidemia, as well as anti-diabetic, antihypertensive, and anti-dyslipidemia therapies.
This study will provide answers to researchers, medical professionals, and especially patients, regarding the impact of aging and cardiometabolic risk factors for COVID-19 prognosis. This pilot study will be used for the development of new studies and for the establishment of recommendations for the care of patients with cardiometabolic risk factors and COVID-19.
7,640 studies on the registry are indexed under COVID-19; 488 are open to participants now.
This study's enrollment of 440 is above the median of 261 across 3,136 observational studies indexed under COVID-19.
Browse COVID-19 studies →Indonesia University is the lead sponsor of 448 studies on the registry; 56 are open to participants now.
Of its 6 completed or terminated interventional studies of FDA-regulated products, 1 (17%) have results posted.
Counted across the registry records on this site, refreshed daily.
COVID-19 patients in hospital and community setting
Exclusion Criteria:
Correlation of Body Mass Index with Clinical Disease Severity
To compare the body mass index, which calculated from body height (in meters) and body weight (in kilograms), in groups of COVID-19 patients with various disease severity based on WHO criteria
Time frame: Baseline
Correlation of Visceral Fat with Clinical Disease Severity
To compare the visceral fat that measures using a bio-impedance analyzer, in groups of COVID-19 patients with various disease severity based on WHO criteria
Time frame: Baseline
Correlation of Blood Glucose Levels with Clinical Disease Severity
To compare the random blood glucose levels during admission in groups of COVID-19 patients with various disease severity based on WHO criteria
Time frame: Baseline
Correlation of HbA1c with Clinical Disease Severity
To compare the HbA1c levels during admission in groups of COVID-19 patients with various disease severity based on WHO criteria
Time frame: Baseline
Changes of Insulin Resistance Levels in COVID-19 Patients Overtime
To compare the changes of HOMA-IR, a surrogate marker for whole-body insulin resistance which calculated from fasting blood glucose (IU/mL) and fasting insulin (mg/dL), between COVID-19 patients and healthy control subjects
Time frame: Baseline, 6, and 12 month
Changes of Leptin/Adiponectin Ratio in COVID-19 Patients Overtime
To compare the changes of leptin/adiponectin ratio, which calculated from leptin levels (ng/mL) divided by adiponectin levels (mikrogram/dL), between COVID-19 patients and healthy control subjects
Time frame: Baseline, 6, and 12 month
Systemic Immune Profiles in Diabetic COVID-19 Patients
To compare the systemic immune profiles using mass cytometry between diabetic/COVID-19, non-diabetic/COVID-19, and healthy control subjects
Time frame: Baseline
Nasal Mucosal Immune Profiles in Diabetic COVID-19 Patients
To compare the nasal-mucosal immune profiles using mass cytometry between diabetic/COVID-19, non-diabetic/COVID-19, and healthy control subjects
Time frame: Baseline
Aging Parameter (ACE-2 gene expression) in COVID-19 Patients
To compare the nasal epithelial ACE-2 gene expression in groups of COVID-19 patients with various disease severity based on WHO criteria
Time frame: Baseline
Aging Parameter (Telomere Length) in COVID-19 Patients
To compare the aging parameter using telomere length in groups of COVID-19 patients with various disease severity based on WHO criteria
Time frame: Baseline
Immune Cells Exhaustion in COVID-19 Patients
To compare the immune cells exhaustion marker (T-cell immunoglobulin mucin-3/TIM-3 expressions) in groups of COVID-19 patients with various disease severity based on WHO criteria
Time frame: Baseline
Changes of Pro-Inflammatory Cytokine (IL-6) in COVID-19 Patients
To compare the changes of pro-inflammatory cytokine (IL-6) levels overtime, measured from the supernatant of stimulated PBMC isolation in groups of patients with various clinical disease severity based on WHO criteria
Time frame: Baseline, 1, 3, and 6 months
Changes of Anti-Inflammatory Cytokine (IL-10) in COVID-19 Patients
To compare the changes of anti-inflammatory cytokine (IL-10) levels overtime, measured from the supernatant of stimulated PBMC isolation in groups of patients with various clinical disease severity based on WHO criteria
Time frame: Baseline, 1, 3, and 6 months
Antibody Kinetics in COVID-19 Patients
To compare the changes of antibody titers in groups of patients with various clinical disease severity based on WHO criteria
Time frame: Baseline, 1, 3, and 6 months
Proportion of Long COVID Syndrome
Percentage of COVID-19 patients still present with symptoms compared to whole study subjects
Time frame: 3, 6, and 12 months
This study is status unknown, as verified in Apr 2022. You cannot join it, but the record below documents what was studied.
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Indonesia University