Juan Diego Hernández

Optimal cutoff for the evaluation of insulin resistance through triglyceride-glucose index: A cross-sectional study in a Venezuelan population

Background: Insulin resistance (IR) evaluation is a fundamental goal in clinical and epidemiological research. However, the most widely used methods are difficult to apply to populations with low incomes. The triglyceride-glucose index (TGI) emerges as an alternative to use in daily clinical practice. Therefore the objective of this study was to determine an optimal cutoff point for the TGI in an adult population from Maracaibo, Venezuela. Methods: This is a sub-study of Maracaibo City Metabolic Syndrome Prevalence Study, a descriptive, cross-sectional study with random and multi-stage sampling. For this analysis, 2004 individuals of both genders ≥18 years old with basal insulin determination and triglycerides < 500 mg/dl were evaluated.. A reference population was selected according to clinical and metabolic criteria to plot ROC Curves specific for gender and age groups to determine the optimal cutoff point according to sensitivity and specificity.The TGI was calculated according to the equation: ln [Fasting triglyceride (mg / dl) x Fasting glucose (mg / dl)] / 2. Results: The TGI in the general population was 4.6±0.3 (male: 4.66±0.34 vs. female: 4.56±0.33, p=8.93x10 -10). The optimal cutoff point was 4.49, with a sensitivity of 82.6% and specificity of 82.1% (AUC=0.889, 95% CI: 0.854-0.924). There were no significant differences in the predictive capacity of the index when evaluated according to gender and age groups. Those individuals with TGI≥4.5 had higher HOMA2-IR averages than those with TGI <4.5 (2.48 vs 1.74, respectively, p<0.001). Conclusions: The TGI is a measure of interest to identify IR in the general population. We propose a single cutoff point of 4.5 to classify individuals with IR. Future studies should evaluate the predictive capacity of this index to determine atypical metabolic phenotypes, type 2 diabetes mellitus and even cardiovascular risk in our population.

Metabolic Syndrome and Subclinical Hypothyroidism: A Type 2 Diabetes-Dependent Association

Introduction Subclinical hypothyroidism (ScH) is an endocrine alteration that is related to cardiovascular risk factors, including those categorized as components of the Metabolic Syndrome (MS). However, findings in prior reports regarding an association between these alterations are inconsistent. The purpose of this study was to determine the relationship between both entities in adult subjects from Maracaibo City, Venezuela. Materials and Methods The Maracaibo City Metabolic Syndrome Prevalence Study is a descriptive, cross-sectional study with random and multistage sampling. In this substudy, 391 individuals of both genders were selected and TSH, free T3, and free T4 tests were performed as well as a complete lipid profile, fasting glycaemia, and insulin blood values. ScH was defined according to the National Health and Nutrition Examination Survey (NHANES) criteria: high TSH (≥4.12mUI/L) and normal free T4 (0.9-1,9u2009ng/dL) in subjects without personal history of thyroid disease. MS components were defined according to IDF/AHA/NHLBI/WHF/IAS/IASO-2009 criteria. A multiple logistic regression analysis was used to assess the relationship between MS components and ScH diagnosis. Results Of the evaluated population, 10.5% (n=41) was diagnosed with ScH, with a higher prevalence in women (female: 13.6% versus male: 7.7%; χ2=3.56, p=0.05). Likewise, 56.1% (n=23) of the subjects with ScH were diagnosed with MS (χ2=4.85; p=0.03), being hyperglycemia the main associated criterion (χ2=11.7; p=0.001). In multivariable analysis, it was observed that the relationship was exclusive with the presence of type 2 diabetes mellitus (T2DM) OR: 3.22 (1.14-9.14); p=0.03. Conclusion The relationship between ScH and MS in our population is dependent on the presence of hyperglycemia, specifically T2DM diagnosis, findings that vary from those previously reported in Latin American subjects.

Biochemical and clinical characterization of metabolic phenotypes: a cross-sectional study from Maracaibo city, Venezuela

In 1980, Reuben Andresen observed that in certain Background: individuals, obesity did not increase mortality, introducing an atypical phenotype called “healthy obese”. Other studies reported that 10-15 % of lean individuals presented insulin resistance, hyperglycemia and dyslipidemia. The objective of this study was to evaluate biochemical and clinical characteristics of metabolic phenotypes in Maracaibo city. A descriptive, cross-sectional sub-analysis of The Maracaibo Methods: City Metabolic Syndrome Prevalence Study, with a randomized multistage sampling was performed including 1226 non diabetic individuals from both sexes. For phenotype definition, the subjects were first classified according to their BMI into Normal-Weight, Overweight and Obese; then divided in metabolically healthy and unhealthy using a two-step analysis cluster being predictive variables: HOMA2-IR, HOMA2-βcell, triglycerides. To evaluate the relationship with coronary risk, a multiple logistic regression model was performed. In the studied population, 43.9% (n=538) were healthy normal Results: weight, 5.2% (n=64) unhealthy normal weight, 17.4% (n=217) healthy obese and 33.5% (n=411) unhealthy obese subjects. Atypical phenotypes, Metabolically Unhealthy Normal-Weight (MUNW) was more frequent in males (56.3%), whereas Metabolically Unhealthy Obese (MUO) was more frequent in females (51.3%). This phenotypes had a higher coronary event risk, especially for obese individuals (MHO: OR=1.85 CI95%: 1.11-3.09; p=0.02 and MUO: OR=2.09 CI95%: 1.34-3.28; p<0.01). Individuals with atypical metabolic phenotypes are common in Conclusion: Maracaibo city. Related factors may include insulin resistance, basal glucose, and triglycerides levels. Lastly, obese subjects show a higher 1,2 2,3 2 2 2 2 4 2 1 1 1 1 1 1

Computational assessment of stomach tumor volume from multi-slice computerized tomography images in presence of type 2 cancer

Background: The multi-slice computerized tomography (MSCT) is a medical imaging modality that has been used to determine the size and location of the stomach cancer. Additionally, MSCT is considered the best modality for the staging of gastric cancer. One way to assess the type 2 cancer of stomach is by detecting the pathological structure with an image segmentation approach. The tumor segmentation of MSCT gastric cancer images enables the diagnosis of the disease condition, for a given patient, without using an invasive method as surgical intervention. Methods: This approach consists of three stages. The initial stage, an image enhancement, consists of a method for correcting non homogeneities present in the background of MSCT images. Then, a segmentation stage using a clustering method allows to obtain the adenocarcinoma morphology. In the third stage, the pathology region is reconstructed and then visualized with a three-dimensional (3-D) computer graphics procedure based on marching cubes algorithm. In order to validate the segmentations, the Dice score is used as a metric function useful for comparing the segmentations obtained using the proposed method with respect to ground truth volumes traced by a clinician. Results: A total of 8 datasets available for patients diagnosed, from the cancer data collection of the project, Cancer Genome Atlas Stomach Adenocarcinoma (TCGASTAD) is considered in this research. The volume of the type 2 stomach tumor is estimated from the 3-D shape computationally segmented from the each dataset. These 3-D shapes are computationally reconstructed and then used to assess the morphopathology macroscopic features of this cancer. Conclusions: The segmentations obtained are useful for assessing qualitatively and quantitatively the stomach type 2 cancer. In addition, this type of segmentation allows the development of computational models that allow the planning of virtual surgical processes related to type 2 cancer.

Insulin resistance indices and coronary risk in adults from Maracaibo city, Venezuela: A cross sectional study

Background: Insulin resistance (IR) is a metabolic disorder related to atherosclerosis. Its measurement is of great importance not only as a marker of diabetes but also for cardiovascular disease. The aim of this research study was to evaluate the relationship between various IR indices and coronary risk in an adult population from Maracaibo city, Venezuela. Methods: The Maracaibo City Metabolic Syndrome Prevalence Study is a descriptive, cross-sectional study with random and multi-stage sampling. In this sub study, 1272 individuals of both genders were selected with the measurement of basal insulin and coronary risk according to the Framingham-Wilson formula calibrated for our population. The insulin resistance indices evaluated were HOMA2-IR, triglycerides and glucose index (TyG) and triglycerides/HDL ratio (TG/HDL). The predictive capacity and association between each index and the coronary risk event in 10 years were determined. Results: Of the evaluated population, 55.2% were female, 34.8% had a coronary risk ≥5% in 10 years, with the TG/HDL and TyG indices showing the highest AUC 0.712 (0.681-0.743) and 0.707 (0.675-0.739), respectively; compared to HOMA2-IR. Both were also the indices most associated with increased coronary risk, especially TG/HDL ≥3 with a higher association [OR = 2.83 (1.74-4.61); p<0.01] after multivariable adjustment. Conclusions: TyG (≥4.5) and TG/HDL (≥3) indices showed a great predictive capacity of higher coronary risk, with being TG/HDL more associated even after adjusting for abdominal obesity and hs-CRP. Therefore, these represent useful tools for determining IR.