Determination of age and sex specific TSH and FT4 reference limits in overweight and obese individuals in an iodine-replete region: Tehran Thyroid Study (TTS)

Optimizing cardiovascular disease mortality prediction: a super learner approach in the tehran lipid and glucose study

BACKGROUND & AIM

Cardiovascular disease (CVD) is the most important cause of death in the world and has a potential impact on health care costs, this study aimed to evaluate the performance of machine learning survival models and determine the optimum model for predicting CVD-related mortality.

METHOD

In this study, the research population was all participants in Tehran Lipid and Glucose Study (TLGS) aged over 30 years. We used the Gradient Boosting model (GBM), Support Vector Machine (SVM), Super Learner (SL), and Cox proportional hazard (Cox-PH) models to predict the CVD-related mortality using 26 features. The dataset was randomly divided into training (80%) and testing (20%). To evaluate the performance of the methods, we used the Brier Score (BS), Prediction Error (PE), Concordance Index (C-index), and time-dependent Area Under the Curve (TD-AUC) criteria. Four different clinical models were also performed to improve the performance of the methods.

RESULTS

Out of 9258 participants with a mean age of (SD; range) 43.74 (15.51; 20-91), 56.60% were female. The CVD death proportion was 2.5% (228 participants). The death proportion was significantly higher in men (67.98% M, 32.02% F). Based on predefined selection criteria, the SL method has the best performance in predicting CVD-related mortality (TD-AUC > 93.50%). Among the machine learning (ML) methods, The SVM has the worst performance (TD-AUC = 90.13%). According to the relative effect, age, fasting blood sugar, systolic blood pressure, smoking, taking aspirin, diastolic blood pressure, Type 2 diabetes mellitus, hip circumference, body mss index (BMI), and triglyceride were identified as the most influential variables in predicting CVD-related mortality.

CONCLUSION

According to the results of our study, compared to the Cox-PH model, Machine Learning models showed promising and sometimes better performance in predicting CVD-related mortality. This finding is based on the analysis of a large and diverse urban population from Tehran, Iran.

A Systematic Review and Meta-Analysis of Free Triiodothyronine (FT3) Levels in Humans Depending on Seasonal Air Temperature Changes: Is the Variation in FT3 Levels Related to Nonshivering Thermogenesis?

Thyroid hormones play a crucial role in regulating normal development, growth, and metabolic function. However, the controversy surrounding seasonal changes in free triiodothyronine (FT3) levels remains unresolved. Therefore, the aim of this study was to conduct a systematic review and meta-analysis of variations in FT3 levels in relation to seasonal air temperatures in the context of current knowledge about its role in nonshivering thermogenesis. Ten eligible articles with a total of 336,755 participants were included in the meta-analysis. The studies were categorized into two groups based on the air temperature: "Cold winter", where the winter temperature fell below 0 °C, and "Warm winter", where the winter temperature was above 0 °C. The analysis revealed that in cold regions, FT3 levels decreased in winter compared to summer (I2 = 57%, p < 0.001), whereas in warm regions, FT3 levels increased during winter (I2 = 28%, p < 0.001). These findings suggest that seasonal variations in FT3 levels are likely to be influenced by the winter temperature. Considering the important role of the FT3 in the nonshivering thermogenesis process, we assume that this observed pattern is probably related to the differences in use of thyroid hormones in the brown adipose tissue during adaptive thermogenesis, which may depend on intensity of cold exposure.

The Effects of Zinc and Selenium Supplementation on Body Composition and Thyroid Function in Individuals with Overweight or Obesity: A Systematic Review

People with obesity have been found to have lower zinc (Zn) and selenium (Se) circulatory levels and abnormal thyroid function than people with normal weight. Studies about the effects of Zn and Se supplementation on body composition and thyroid function of overweight-obese people showed inconsistent results. A systematic review of randomized controlled trials was conducted to determine the effects of Ζn supplementation, Se supplementation, and their combination on body composition and thyroid function of individuals with overweight or obesity. Databases of PubMed, ScienceDirect, and Cochrane, were searched from inception to February 27, 2022, to identify relevant articles. For the assessment of the methodological quality of the studies, the Jadad scale was used. After screening the articles, thirteen studies were finally included and were analyzed using the strength of the evidence approach. Regarding the effectiveness of Zn supplementation on body composition, moderate evidence was found, while the effects of Se were found to be mixed. Zn supplementation was found to affect the thyroid function of people with overweight or obesity by increasing their free triiodothyronine (FT3) levels. However, this result is based only on one study among hypothyroid patients. At this point, the effectiveness of Zn, Se, and their combination, on the body composition and the thyroid function of people with overweight or obesity cannot safely be determined because of the controversial results, small number, and the limitations of the identified studies. The results of this systematic review must be interpreted with caution due to the limitations detected.

Obesity and Thyroid Axis

Development of obesity is primarily the result of imbalance between energy intake and energy expenditure. Thyroid hormones influence energy expenditure by regulating cellular respiration and thermogenesis and by determining resting metabolic rate. Triiodothyronine influences lipid turnover in adipocytes and impacts appetite regulation through the central nervous system, mainly the hypothalamus. Thyroid-stimulating hormone may also influence thermogenesis, suppress appetite and regulate lipid storage through lipolysis and lipogenesis control. Subclinical hypothyroidism may induce changes in basal metabolic rate with subsequent increase in BMI, but obesity can also affect thyroid function via several mechanisms such as lipotoxicity and changes in adipokines and inflammatory cytokine secretion. The present study investigated the complex and mutual relationships between the thyroid axis and adiposity.