Examination of bone fractures in women exposed to domestic violence (Tokat-Turkey).

BACKGROUND: Fractures are an important symptom of physical violence that will negatively affect the woman's quality of life in the coming years. However, there is limited information in the literature about fractures in women exposed to domestic violence (DV). The aim of this study was to compare fracture development rates and age distributions in women exposed to DV and intimate partner violence (IPV), a component of DV, and women exposed to other physical violence (OV), to determine the incidence of DV cases with and without fractures, and to determine fracture locations in DV cases and to identify diagnostic lesions accompanying fractures. METHODS: A retrospective review was made of patients injured as a result of IPV, other domestic violence (ODV) and OV. The data of cases with fracture were analyzed in terms of age groups of the victims and according to location and types of fractures. RESULTS: Of the 854 female patients aged >18 years who were admitted to the hospital due to violence, 55.2% were exposed to DV. Most DV victims (87.9%) were assaulted by intimate partners. The incidence of fractures in IPV cases (7.2%), was nearly twice that of ODV and OV cases. The mean age of IPV cases with fractures (42.1 ± 12.1 years) was significantly higher than that of IPV cases without fractures (33.1 ± 11.8 years) (p < 0.05). Most IPV cases (61.8%) were aged <35 years. Most DV cases with fractures (75%) were aged <50 years. Facial/neck injuries (41.5%) and facial fractures (52.6%) were prominent in DV cases. CONCLUSION: The results of this study of the presence of facial fractures, especially in women aged <50 years, is an important finding that can alert doctors to potential cases of domestic violence.

Sex Estimation From Measurements of the Mastoid Triangle and Volume of the Mastoid Air Cell System Using Classical and Machine Learning Methods: A Comparative Analysis.

ABSTRACT: Previous studies on the sexual dimorphism of the mastoid triangle have typically focused on linear and area measurements. No studies in the literature have used mastoid air cell system volume measurements for direct anthropological or forensic sex determination. The aims of this study were to investigate the applicability of mastoid air cell system volume measurements and mastoid triangle measurements separately and combined for sex estimation, and to determine the accuracy of sex estimation rates using machine learning algorithms and discriminant function analysis of these data. On 200 computed tomography images, the distances constituting the edges of the mastoid triangle were measured, and the area was calculated using these measurements. A region-growing algorithm was used to determine the volume of the mastoid air cell system. The univariate sex determination accuracy was calculated for all parameters. Stepwise discriminant function analysis was performed for sex estimation. Multiple machine learning methods have also been used. All measurements of the mastoid triangle and volumes of the mastoid air cell system were higher in males than in females. The accurate sex estimation rate was determined to be 79.5% using stepwise discriminant function analysis and 88.5% using machine learning methods.

Sex Estimation From the Paranasal Sinus Volumes Using Semiautomatic Segmentation, Discriminant Analyses, and Machine Learning Algorithms.

ABSTRACT: The aims of this study were to determine whether paranasal sinus volumetric measurements differ according to sex, age group, and right-left side and to determine the rate of sexual dimorphism using discriminant function analysis and machine learning algorithms. The study included paranasal computed tomography images of 100 live individuals of known sex and age. The paranasal sinuses were marked using semiautomatic segmentation and their volumes and densities were measured. Sex determination using discriminant analyses and machine learning algorithms was performed. Males had higher mean volumes of all paranasal sinuses than females ( P < 0.05); however, there were no statistically significant differences between age groups or sides ( P > 0.05). The paranasal sinus volumes of females were more dysmorphic during sex determination. The frontal sinus volume had the highest accuracy, whereas the sphenoid sinus volume was the least dysmorphic. In this study, although there was moderate sexual dimorphism in paranasal sinus volumes, the use of machine learning methods increased the accuracy of sex estimation. We believe that sex estimation rates will be significantly higher in future studies that combine linear measurements, volumetric measurements, and machine-learning algorithms.

An investigation of the effect of the COVID-19 (SARS-CoV-2) pandemic on occupational accidents (Tokat-Turkey).

The aims of this study were to compare the incidence of occupational accidents during one-year periods of the COVID-19 Pandemic and before the COVID-19 Pandemic, and to determine in which sectors occupational accidents occurred and what types of injuries were sustained in the population of Tokat, Turkey. A retrospective review was made of the records of Tokat State Hospital of patients injured in occupational accidents between 12.03.2019 and 11.03.2021. The patients injured in occupational accidents were classified according to age, gender, sector, accident type, trauma localization and type, time of the accident, and outcome of the injuries. Of 608 patients injured in occupational accidents, 384 (63.2%) were injured in the period before the pandemic and 224 (36.8%) were injured in the period during the pandemic (p < 0.001). Most work-related injuries occurred in the industry sector (n = 287; 47.2%; p < 0.001). Occupational accidents increased in the service sector (p < 0.001), but decreased in other sectors. The increase in occupational accidents in the health sector (p < 0.001) and transportation sector (p < 0.05) within the service sector caused a general increase despite the decrease in other service sectors (p > 0.05). In current study, the increase in the number of injuries in the transportation sector due to the increase of motor courier accidents, in health sector, and in pandemic quarantines were remarkable. It was evaluated that this narrow-scoped study pioneered comprehensive studies on the measures that can be taken to prevent occupational accidents in such pandemics in the future.

Sex estimation using foramen magnum measurements, discriminant analyses and artificial neural networks on an eastern Turkish population sample.

BACKGROUND: Although many studies have been conducted using the foramen magnum for sex estimation, recent findings have indicated that the discriminant and regression models obtained from the foramen magnum may not be reliable. Artificial Neural Networks, was used as a classification technique in sex estimation studies on some other bones, did not used in sex estimation studies on the foramen magnum until now. The aim of this study was sex estimation on an Eastern Turkish population sample using foramen magnum measurements, discriminant analyses and Artificial Neural Networks. METHODOLOGY: The study was performed on the CT images of a total of 720 cases, comprising 360 males and 360 females. For sex estimation, discriminant analysis and Artificial Neural Networks were used. RESULTS: The accuracy rate was 86.7% with discriminant analysis and when sex estimation accuracy was determined according to cases with posterior probabilities above 95%, the accuracy ranged from 0% to 33.3%. With the use of the discriminant formulas of 2 other studies, obtained from different Turkish samples, sex could be determined at a rate of 84.6%. Some formulas were found to be unsuccessful in sex estimation. Sex estimation accuracy of 88.2% was achieved with Artificial Neural Networks. CONCLUSION: In this study, it was found that sex could be determined to some extent with discriminant formulas from other samples from the same population, although some formulas were unsuccessful. With the use of image processing techniques and machine learning algorithms, better results can be obtained in sex estimation.

Sex estimation from the clavicle using 3D reconstruction, discriminant analyses, and neural networks in an Eastern Turkish population.

Sex estimation of skeletal remains is an important aspect of forensic anthropology. The clavicle is a bone with relatively high accuracy in sex determination. In this study, 7 clavicular parameters were obtained using the CT images and 3D reconstruction of 360 cases equally distributed as 180 males and 180 females. Sex determination was made using univariate, linear, and stepwise discriminant analyses, and multilayer perceptron neural networks. Maximum sex determination accuracy of 85.3% was achieved with univariate analysis, 89.4% with linear discriminant analysis, 90.0% with stepwise discriminant analysis, and 91.4% with multilayer perceptron neural networks. Significant changes were observed in the MLC, APMD-R and CDC parameters according to age, and these were determined to affect the accuracy of sex determination in different age groups. In forensic anthropological studies, more reliable results can be obtained by considering the confounding factors during sampling. Although high accuracy rates can be achieved with neural networks, the results should be approached with caution.

Sex estimation from sacrum and coccyx with discriminant analyses and neural networks in an equally distributed population by age and sex.

Sex estimation is an essential step in the process of the identification of the skeletal remains in forensic anthropology since it reduces the number of possible matches by half. In this study, sex estimation with 21 sacral and coccygeal metric parameters obtained from Computerized Tomography images of a Turkish population which consists of 480 patients that are equalized according to their sexes and ages, is performed. Univariate discriminant analysis, linear discriminant function analysis, stepwise discriminant function analysis, and multilayer perceptron neural networks are used in this study. A maximum of 67.1% accuracy for univariate discriminant analysis, 82.5% for linear discriminant function analysis, 78.8% for stepwise discriminant function analysis, and 86.3% for multilayer perceptron neural networks, were achieved. Although it does not reach an acceptable accuracy rate of 95% or more for sacrum and coccyx, sex estimation with neural networks is a promising field of research in corpses where identification is otherwise not possible, and further studies with other bones and with new techniques might give useful information.

The effect of altitude and climate on the suicide rates in Turkey.

Suicide is one of the most important public health problems. There was an association between suicide and several factors such as psychiatric diseases and psychological characteristics, somatic illness, cultural, socioeconomic, familial, occupational and individual risk factors. Also, high altitude and climatic factors including high temperature, cloudiness, more sunshine and low rainfalls were defined as some of these risk factors in the literature. In this study, we aimed to investigate correlation between suicide rates and altitudes of all cities in Turkey and between suicide rates and climatic factors including Rainfall Activity Index, Winter Mean Temperatures, Summer Mean Temperatures and Temperature Difference between January and July previously defined by several authors in the broad series in Turkey. In Turkey, 29865 suicidal deaths occurred in 10 years period between 2006 and 2015. Of them, 21020 (70.4%) were males and 8845 (29.6%) were females. In this study, we found that high altitude above 1500 m, winter median temperature lower than -10 °C and hard temperature changes above 25 °C between winter and summer of settlements were important factors that affected on female suicide rates appropriate to knowledge which defined in previous studies. In conclusion, we suggested that the associations among suicide rates with altitudes and climate should be studied in wider series obtained from different countries for reaching more reliable results.

The effects of gender and age on forensic personal identification from frontal sinus in a Turkish population.

OBJECTIVES: To define the dimensions of the frontal sinus in groups standardized for age and gender and to discuss the reasons and the effects of the variations. Methods: Frontal sinus measurements were obtained from paranasal CTscans of 180 males and 180 females in the Radiology Department of Dursun Odabas Medical Center of Yuzuncu Yil University, Van, which is located in Eastern Turkey, between February and March 2016. The width and height of sinuses were measured on a coronal plane, and the anteroposterior length was measured on an axial plane. Volumes were calculated using the Hospital Information Management Systems and Image Archiving and Management Systemprogram. The Statistical Package of the Social Science version 13 was used for statistical analyses.  Results: We determined differences in the frontal sinus measurements of different age groups in a Turkish adult population. Frontal sinus dimensions were usually higher in females and lower in males after 40-49 years of age than their younger counterparts, but the measurements were lower in females and higher in males in 70≤ years of age group than 60-69 years of age. Left frontal sinus was dominant in young age groups but right frontal sinus was dominant in groups 40-49 years of age or older.  Conclusion: We observed crossing of the measurements between the different age groups, which we could not find clear explanations. The results of such studies may affect forensic identification from frontal sinus measurements.