Insulin Resistance Clinical Trial
— DICAMANOOfficial title:
Discovering Carbohydrate Metabolism Alterations in Normoglycemic Obese Patients Study
Verified date | February 2018 |
Source | Clinica Universidad de Navarra, Universidad de Navarra |
Contact | n/a |
Is FDA regulated | No |
Health authority | |
Study type | Observational |
This is a large and comprehensively phenotyped cohort with fasting glycaemia where the predictive value of body composition and anthropometric measures of total and central fat distribution for postprandial carbohydrate intolerance are studied.
Status | Completed |
Enrollment | 853 |
Est. completion date | January 28, 2016 |
Est. primary completion date | August 28, 2014 |
Accepts healthy volunteers | |
Gender | All |
Age group | 18 Years to 70 Years |
Eligibility |
Inclusion Criteria: - Fasting glucose level = 5.5 mmol l-1 - BMI = 25 Exclusion Criteria: - Type 2 diabetes mellitus - Severe renal, liver or thyroid dysfunction |
Country | Name | City | State |
---|---|---|---|
n/a |
Lead Sponsor | Collaborator |
---|---|
Clinica Universidad de Navarra, Universidad de Navarra | Instituto de Salud Carlos III |
Type | Measure | Description | Time frame | Safety issue |
---|---|---|---|---|
Primary | Body fat percentage and carbohydrate intolerance | Investigate whether body fat percentage estimated by air-displacement plethysmography (Bod-Pod®, Life Measurements, Concord, CA, USA) predicts postprandial carbohydrate intolerance early on in the metabolic dysregulation process. Body fat percentage (BF%) is calculated from body density by means of the Siri equation. |
Baseline | |
Primary | Neck circumference as screening tool | Examine the predictive value of neck circumference as screening tool for the selection of patients who are most likely to benefit from an oral glucose tolerance test (OGTT) | Baseline | |
Secondary | Waist-to-hip ratio as screening tool | Examine the predictive value of waist-to-hip ratio as screening tool for the selection of patients who are most likely to benefit from an oral glucose tolerance test (OGTT). Waist-to-hip ratio was calculated as waist circumference divided by hip circumference. Waist circumference was measured at the midpoint between the iliac crest and the rib cage on the mid-axillary line, and hip circumference at the level of the greater trochanters was measured to the nearest millimetre using a flexible tape. | Baseline | |
Secondary | Waist-to-height ratio as screening tool | Examine the predictive value of waist-to-height ratio as screening tool for the selection of patients who are most likely to benefit from an oral glucose tolerance test (OGTT). Waist-to-height ratio was calculated as waist circumference divided by height. | Baseline | |
Secondary | BMI as screening tool | Examine the predictive value of body adiposity index (BMI) as screening tool for the selection of patients who are most likely to benefit from an oral glucose tolerance test (OGTT). BMI was calculated as weight in kilograms divided by height in meters squared. | Baseline | |
Secondary | Body adiposity index as screening tool | Examine the predictive value of body adiposity index (BAI) ([hip circumference/height1.5]-18) as screening tool for the selection of patients who are most likely to benefit from an oral glucose tolerance test (OGTT). | Baseline | |
Secondary | Central fat depot and carbohydrate intolerance | Investigate whether central fat depot predicts postprandial carbohydrate intolerance early on in the metabolic dysregulation process. Visceral and abdominal adiposity was quantified by the use of the abdominal bioelectrical impedance analysis device ViScan (Tanita AB-140, Tanita Corp., Tokyo, Japan). | Baseline | |
Secondary | Central fat depot and cardiometabolic risk | Investigate whether a higher central fat depot is able to identify those individuals with higher inflammatory parameters (c-reactive protein, homocysteine and uric acid) and cardiovascular risk (higher rate of hypercholesterolemia, hypertension and/or obstructive sleep apnea). Body fat percentage (BF%) is calculated from body density by means of the Siri equation. |
Baseline | |
Secondary | Body fat percentage and cardiometabolic risk | Investigate whether a higher body fat percentage is able to identify those individuals with higher inflammatory parameters (c-reactive protein, homocysteine and uric acid) and cardiovascular risk (higher rate of hypercholesterolemia, hypertension and/or obstructive sleep apnea). Body fat percentage (BF%) is calculated from body density by means of the Siri equation. |
Baseline | |
Secondary | Prevalence of postprandial carbohydrate intolerance | Assess the prevalence of postprandial carbohydrate intolerance in individuals with normal fasting glycaemia | Baseline | |
Secondary | Oral glucose tolerance test parameters and cardiometabolic profile | Verification of the utility of the two-hour OGTT glucose value to select those individuals with higher cardiometabolic risk (higher rate of hypercholesterolemia, hypertension and/or obstructive sleep apnea). | Baseline | |
Secondary | Non-alcoholic fatty liver disease (NAFLD) and glucose dysregulation | Analyse the association between NAFLD and OGTT-based ß-cell function and insulin resistance in non-diabetic subjects. | Baseline | |
Secondary | OGTT-based indices as screening tool of NAFLD | Examine whether OGTT-based ß-cell function and insulin resistance indices could be used as screening tools for the selection of patients who are most likely to benefit from a NAFLD-study. | Baseline | |
Secondary | OGTT-derived glucose curve as screening tool of NAFLD | Examine whether the glucose response curve could be used as screening tool for the selection of patients who are most likely to benefit from a NAFLD-study. | Baseline |
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