CARAMEL: COVID-19, Aging, and Cardiometabolic Risk Factors Study

Sponsor

Indonesia University (Other)

Overall Status

Active, not recruiting

CT.gov ID

NCT04802044

Collaborator

Leiden University Medical Center (Other)

440

Enrollment

Locations

36.7

Anticipated Duration (Months)

220

Patients Per Site

Patients Per Site Per Month

Study Details

Study Description

Brief Summary

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.

Condition or Disease	Intervention/Treatment	Phase
Covid19 Obesity Diabetes Mellitus Aging Cardiometabolic Syndrome Immune System Disorder

Detailed Description

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.

Study Design

Study Type:

Observational

Actual Enrollment :

440 participants

Observational Model:

Cohort

Time Perspective:

Prospective

Official Title:

COVID-19, Aging, and Cardiometabolic Risk Factors (CARAMEL) Study: Integrating Aging, Cardiovascular, Metabolic, and Immunological Studies to Unravel COVID-19 Pathophysiology

Actual Study Start Date :

Dec 8, 2020

Anticipated Primary Completion Date :

Dec 31, 2022

Anticipated Study Completion Date :

Dec 31, 2023

Outcome Measures

Primary Outcome Measures

Correlation of Body Mass Index with Clinical Disease Severity [Baseline]
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
Correlation of Visceral Fat with Clinical Disease Severity [Baseline]
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
Correlation of Blood Glucose Levels with Clinical Disease Severity [Baseline]
To compare the random blood glucose levels during admission in groups of COVID-19 patients with various disease severity based on WHO criteria
Correlation of HbA1c with Clinical Disease Severity [Baseline]
To compare the HbA1c levels during admission in groups of COVID-19 patients with various disease severity based on WHO criteria

Secondary Outcome Measures

Changes of Insulin Resistance Levels in COVID-19 Patients Overtime [Baseline, 6, and 12 month]
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
Changes of Leptin/Adiponectin Ratio in COVID-19 Patients Overtime [Baseline, 6, and 12 month]
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
Systemic Immune Profiles in Diabetic COVID-19 Patients [Baseline]
To compare the systemic immune profiles using mass cytometry between diabetic/COVID-19, non-diabetic/COVID-19, and healthy control subjects
Nasal Mucosal Immune Profiles in Diabetic COVID-19 Patients [Baseline]
To compare the nasal-mucosal immune profiles using mass cytometry between diabetic/COVID-19, non-diabetic/COVID-19, and healthy control subjects
Aging Parameter (ACE-2 gene expression) in COVID-19 Patients [Baseline]
To compare the nasal epithelial ACE-2 gene expression in groups of COVID-19 patients with various disease severity based on WHO criteria
Aging Parameter (Telomere Length) in COVID-19 Patients [Baseline]
To compare the aging parameter using telomere length in groups of COVID-19 patients with various disease severity based on WHO criteria
Immune Cells Exhaustion in COVID-19 Patients [Baseline]
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
Changes of Pro-Inflammatory Cytokine (IL-6) in COVID-19 Patients [Baseline, 1, 3, and 6 months]
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
Changes of Anti-Inflammatory Cytokine (IL-10) in COVID-19 Patients [Baseline, 1, 3, and 6 months]
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
Antibody Kinetics in COVID-19 Patients [Baseline, 1, 3, and 6 months]
To compare the changes of antibody titers in groups of patients with various clinical disease severity based on WHO criteria
Proportion of Long COVID Syndrome [3, 6, and 12 months]
Percentage of COVID-19 patients still present with symptoms compared to whole study subjects

Eligibility Criteria

Criteria

Ages Eligible for Study:

18 Years and Older

Sexes Eligible for Study:

All

Accepts Healthy Volunteers:

Yes

Inclusion Criteria:

Patients newly diagnosed with COVID-19 at hospital setting or community screening, confirmed with biological proof (RT-PCR)

Exclusion Criteria:

Subjects opposed to the use of their data
Minors, adults under guardianship, protected persons
History of malignancy
History of autoimmune disease
Pregnancy

Contacts and Locations

Locations

	Site	City	State	Country	Postal Code
1	Dr. Cipto Mangunkusumo National General Hospital	Jakarta Pusat	DKI Jakarta	Indonesia	10430
2	Metabolic Disorder, Cardiovascular, and Aging Research Cluster IMERI-FKUI, Research Tower, 5th Floor	Jakarta Pusat	DKI Jakarta	Indonesia	10430