Vitamin D deficiency is associated with cardiometabolic risk factors (eg, hypertension, insulin resistance, type 2 diabetes mellitus, obesity, and dyslipidemia). We studied 50 obese patients (body mass index [BMI]: 43.5 ± 9.2 kg/m ² ) and 36 normal weight participants (BMI: 22.6 ± 1.9 kg/m ² ). The prevalence of vitamin D deficiency (25-hydroxyvitamin D, 25(OH)D < 50 nmol/L) was 88% among obese patients and 31% among nonobese individuals; 25(OH)D levels were lower in the obese group (27.3 ± 13.7 vs 64.6 ± 21.3 nmol/L; P < .001). There was a negative correlation between vitamin D level and anthropometric indicators of obesity: BMI ( r = −0.64; P < .001), waist circumference ( r = −0.59; P < .001), and body fat percentage ( r = −0.64; P < .001) as well as with fasting plasma insulin ( r = −0.35; P < .001) and homeostasis model assessment of insulin resistance ( r = −0.35; P < .001). In conclusion, we observed a higher prevalence of vitamin D deficiency among obese participants and this was associated with a proatherogenic cardiometabolic risk profile.

Vitamin D deficiency and dysfunctional adipose tissue are involved in the development of cardiometabolic disturbances (eg, hypertension, insulin resistance, type 2 diabetes mellitus, obesity, and dyslipidemia). We evaluated the relation between vitamin D and adipocytokines derived from adipose tissue. We studied 50 obese individuals who were classified into different subgroups according to medians of observed anthropometric parameters (body mass index, body fat percentage, waist circumference, and trunk fat mass). There was a negative correlation between vitamin D level and leptin and resistin (r = −.61, P < .01), while a positive association with adiponectin concentrations was found (r = .7, P < .001). Trend estimation showed that increase in vitamin D level is accompanied by intensive increase in adiponectin concentrations (growth coefficient: 12.13). In conclusion, a positive trend was established between vitamin D and the protective adipocytokine adiponectin. The clinical relevance of this relationship needs to be investigated in larger studies.

A common problem when working with medical records is that some measurements are missing. The simplest and the most common solution, especially in machine learning domain, is to exclude records with incomplete data. This approach produces datasets with reduced statistical power and can even lead to biased or erroneous final results. There are, however, many proposed imputing methods for missing data. Although some of them, such as multiple imputation, are mature and well researched, they can be prone to misuse and are not always suitable for building complex frameworks. This paper explores neural networks as a potential tool for imputing univariate missing laboratory data during cardiometabolic risk assessment, comparing it to other simple methods that could be easily set up and used further in building predictive models. We have found that neural networks outperform other algorithms for diverse fraction of missing data and different mechanisms causing their missingness.

Introduction. Lingual thyroid gland is a rare anomaly of thyroid gland development, occurring more frequently in females. If it causes local symptomatology such as dysphagia, dysphonia or dyspnea it is diagnosed in childhood, however, if it is asymptomatic it is usually diagnosed in adulthood. Case Outline. We present a 23-year-old female patient in whom we diagnosed lingual thyroid gland coincidentally during diagnostic procedures of a concomitant disease. The application of 131I scintigraphy showed an oval field of intensive accumulation of radio markers in the zone of medial face line, around tongue base, with the absence of thyroid gland in its physiological position. Functional testing proved primary hypothyroidism and we started the application of substitution therapy. The application of levothyroxine resulted in reaching euthyroid state and the reduction of thyroid gland size. Conclusion. We present a very rare anomaly of the thyroid gland, and so far there have been no clear attitudes about further treatment. The general condition of the patient, age, the size of ectopic thyroid gland and the existence of local symptomatology or complications represent the factors that have influence on the choice of treatment method.