Age-specific waist circumference cutoff-points for abdominal obesity diagnosis: a personalized strategy for a large Venezuelan population.

BACKGROUND: Evidence shows that the ageing process is a determining factor in fat distribution, composition, and functionality. The goal of this research was to determine cut-off points for waist circumference according to age in the adult population from Maracaibo city, Venezuela. METHODOLOGY: The Metabolic Syndrome Prevalence Study is a descriptive, cross-sectional study with multi-stage randomized sampling. In this post-hoc analysis 1902 individuals ≥18 years and from both sexes were evaluated. Waist circumference ROC curves were built for each age group and sex, using metabolic phenotypes for classification. RESULTS: 52.2% (n = 992) were women, and the mean age was 38.7 ± 2. Cut-off points obtained for the <30 years age group were: 91 cm for women (Sensitivity: 96,8%, Specificity: 97,7%) and 94 cm for men (Sensitivity:100%, Specificity: 99,2%); for 30-49 years: women 94 cm (Sensitivity: 93.7%, Specificity: 97.1%) and men 95 cm (Sensitivity: 97.3%, Specificity: 100%); for ≥50 years: women 94 cm (Sensitivity: 91.8%, Specificity: 86.7%) and men 101 cm (Sensitivity: 100%, Specificity: 100%). CONCLUSION: The use of specific cut-off points according to age groups is proposed to determine abdominal obesity in Maracaibo city due to the underestimation seen in young people and the overestimation observed in older people when using a unique cut-off point.

Association between +45T>G adiponectin polymorphism gene and type 2 diabetes mellitus and metabolic syndrome in a Venezuelan population.

Background: Adiponectin (ADIPOQ) is a hormone primarily synthesized by adipocytes and encoded by the ADIPOQ gene, which exerts anti-inflammatory, antiatheratogenic and insulin sensitizing functions. It has been shown that its plasma concentrations are decreased in individuals with metabolic syndrome (MS) and type 2 diabetes mellitus (DM2), which could be due to variations in the gene coding for this protein. The aim of this study was to detect the +45 T>G polymorphism of the ADIPOQ gene in subjects with DM2 and MS in Maracaibo municipality, Zulia state, Venezuela. Methods: A total of 90 subjects who attended the Center for Metabolic Endocrine Research "Dr. Félix Gómez" were enrolled for this study, 46 of which had MS-DM2 and 44 of which were healthy control individuals. Genomic DNA was extracted from blood samples and PCR-restriction fragment length polymorphism analysis was carried out for the promoter region of the ADIPOQ gene. Likewise, the +45 T> G polymorphism was identified and correlated with MS and DM2 in the studied population. Results: The most frequent allele in both groups was the T allele, and the predominant genotype was homozygous T/T (79%). Genotypes with heterozygous T/G and G/G homozygous polymorphism were more frequent in the control group than in the MS-DM2 group. Regarding the individuals with T/G and G/G genotypes, statistically significant lower mean values ​​were found for fasting glucose, total cholesterol, triacylglycerides, abdominal circumference, and for the medians of systolic and diastolic blood pressure. Odds ratio were calculated for the presence or absence of MS and DM2. Conclusions: The results suggested that the presence of the G allele exerts a protective effect on the carrier individuals, thus avoiding the appearance of the aforementioned metabolic alterations.

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.