Trauma is a condition that affects the body's structure and results from outside factors. After heart disease and cancer, it is the most common cause of death across all age categories. For a variety of causes, people are routinely exposed to traumatic vertebral, thoracic pathologies and rib fractures. Ribs can be harmed by simple falls, impacts, and blunt injuries as well as broken due to car accidents and falling from a height. Magnetic resonance imaging or computed tomography are used to diagnose these fractures. In this study, non-linear complex methods were used to categorize gender and age by utilizing thoracic pathologies, fractures or cracks in the body as a result of traffic accidents or falling from a height, which have the feature of being a case in forensic issues. Variables were selected to identify the most important data. MARS (Multivariate Adaptive Regression Spline) method of variable selection. Although autopsy should be utilized in these situations, complex regression methods is intended to have an impact on quick and accurate decision-making about events in order to speed up or direct the process in the field of forensic medicine. As a result, the effectiveness of the experts' subsequent predictions will be increased by the preliminary findings produced by real-world data and artificial intelligence algorithms or complex non-linear regression problems.
Objective In this study, patients were divided into two groups. Patients with polycystic ovary syndrome (PCOS) and patients with polycystic ovary syndrome + Hashimoto's Thyroid (PCOS + HT). The effect of insulin resistance on ovarian volume in patients divided into two groups and the change in ovarian volume with the addition of HT to PCOS will be investigated. Material and methods 46 PCOS patients and 46 PCOS patients diagnosed with HT were included in this study. A detailed medical history was taken from all participants. Polycystic ovary image was evaluated as below or above 10 ml and antral follicles were counted by transvaginal ultrasound. Insulin resistance of the patients was evaluated according to the fasting insulin (HOMA) index. Results Insulin resistance was found to be associated with fasting insulin, HOMA index, body mass index and right ovarian volume in patients diagnosed with PCOS. Among the patients diagnosed with PCOS + HT, insulin resistance was found to be significantly correlated with fasting insulin, HOMA index, (BMI), (SHBG) and left ovarian volume. An increase in right ovarian volume was found in 37.5% of patients with PCOS without insulin resistance and in 76.3% of patients with insulin resistance. An increase in left ovarian volume was found in 35.7% of patients without insulin resistance diagnosed with PCOS + HT and in 68.8% of patients with insulin resistance. Conclusions This study shows that ovarian volume should be evaluated in every PCOS patient in order to predict insulin resistance, which causes long-term metabolic diseases, and that all PCOS patients with increased ovarian volume should be investigated for insulin resistance. In addition, it has been observed that insulin resistance affects left ovarian volume in patients with PCOS + HT, whereas insulin resistance affects the volume of the right ovary more in patients with PCOS. At least one ovary has been found to be affected by long-term metabolic diseases. While there was a greater increase in ovarian volume with the addition of insulin resistance, no significant change was observed in the number of patients with increased ovarian volume (PCOS-58, PCOS + HT-57) with the addition of HT finding.
Objective: In this study, our aim was to divide the patients diagnosed with polycystic ovary syndrome (PCOS) and Hashimoto's thyroiditis (HT) into subgroups according to different clinical and laboratory findings. It is to investigate whether it will exacerbate it. Material and Methods: 46 PCOS patients and 46 PCOS patients diagnosed with HT were included in this study. A detailed medical history was taken from all participants. Polycystic ovary image was evaluated as below or above 10 ml and antral follicles were counted by transvaginal ultrasound. Insulin resistance of the patients was evaluated according to the fasting insulin (HOMA) index. Results: Insulin resistance was found to be associated with fasting insulin, HOMA index, body mass index and right ovarian volume in patients diagnosed with PCOS. Among the patients diagnosed with PCOS+HT, insulin resistance was found to be significantly correlated with fasting insulin, HOMA index, (BMI), (SHBG) and left ovarian volume. An increase in right ovarian volume was found in 37.5% of patients with PCOS without insulin resistance and in 76.3% of patients with insulin resistance. An increase in left ovarian volume was found in 35.7% of patients without insulin resistance diagnosed with PCOS+HT and in 68.8% of patients with insulin resistance. Conclusions: This study shows that in order to predict insulin resistance that causes long-term metabolic diseases, ovarian volume should be evaluated in every PCOS patient and all PCOS patients with increased ovarian volume should be investigated for insulin resistance. In addition, it has been observed that insulin resistance affects left ovarian volume in patients with PCOS+HT, while insulin resistance affects the volume of the right ovary more in patients with PCOS. At least one ovary has been found to be affected by long-term metabolic diseases.
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