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Conclusion: In hip fractures with high mortality in the geriatric age group, 90-day mortality can be predicted by GNRI score calculated using albumin, height, and weight values. Results: The study included 1,345 patients with a mean age of 80.27±7.45. The 90-day mortality rate of the patients examined in the study was 10.6%. In addition, when we look at early complications, this rate is 4%. Statistically, although there was no significant relationship between early complications and GNRI (p=0.724), it was found to be significant with mortality (p<0.001). Materials and Methods: Patients over 65 years of age were retrospectively included in this study. Age, gender, height, weight, fracture type, hemogram, and routine biochemical values at the time of admission to the hospital, previous trauma history, and hospitalization within 90 days after surgery were evaluated from the patient's files. Surgical site infection and periprosthetic joint infections that developed in the first 90 days were recorded as early complications. Objective: Malnutrition is a severe cause of increased morbidity and mortality and decreased functionality and quality of life that can be treated and prevented in the geriatric population. The geriatric nutritional risk index is used to determine the nutritional status of the geriatric population. We evaluated the ability of geriatric nutrition risk index (GNRI) values to predict 90-day complications and mortality in elderly patients with hip fractures. Our study hypothesises that low GNRI values can help predict early complications and mortality. [ABSTRACT FROM AUTHOR]

Introduction: Sarcopenia is defined as a progressive loss of muscle mass and function with increased age. The measurement of muscle mass and attenuation on the axial computed tomography (CT) scan has been reported to be a good indicator for sarcopenia in previous literature. This study aimed to compare muscle mass between the intertrochanteric fracture and femoral neck fracture groups by accurately measuring muscle mass around the hip joint using a CT scan. Methods: The cases were matched according to age and gender on a 1-to-1 basis. As a result, a total of 400 patients, 200 patients in each group with the same age and gender characteristics, were included in the study. At the disc of L4-L5 level, the cross-sectional area (CSA) of the psoas muscle was evaluated, and at the disc of L5-S1 level, the CSA of the psoas, iliacus and gluteus medius muscles were evaluated. In addition, attenuation was evaluated using the average Hounsfield Unit (HU) for the specific area. Results: The mean age of 400 patients (262 females, 138 male) included in the study was 78.49 ± 7.67 years. It was observed that the mean HU values of the patients in the femoral neck fracture group were significantly higher than the intertrochanteric fracture group (p < 0.001, p = 0.008; respectively). At the same time, the mean HU values of the gluteus medius muscle were higher in the femoral neck fracture group (p < 0.001), but in contrast with the psoas muscle, the CSA values of gluteus medius muscle were significantly higher in the intertrochanteric fracture group (p = 0.017). Conclusions: Fatty degeneration of the psoas muscle among the muscles around the hip may affect the type of hip fracture. Elderly patients with strong psoas muscles may experience femoral neck fracture due to contraction and torsion during falling. [ABSTRACT FROM AUTHOR]

Objective: Although the incidence of hip fractures before and during the pandemic is similar, the effect of the epidemic on the distribution of hip fractures and its subtypes cannot be clearly explained. We aimed to elucidate the changes by comparing the number of geriatric hip fractures and the distribution of fracture types between one year of the Coronavirus disease-2019 (COVID-19) pandemic and seven years ago. Methods: Hip fracture patients over 65 years of age was analyzed retrospectively. The period between March 11, 2020 and March 10, 2021 was called the pandemic period, and the period between March 11, 2013 and March 10, 2020 was called the pre-pandemic period. Mortality rates and fracture morphology were compared between the pre-pandemic period and the pandemic period. Results: There was no significant difference in the age distribution between pre-covid (80.48±7.38) and Coronavirus period (79.54±7.92) (p=0.163). Likewise, no difference was found between the fracture patterns in both groups (p=0.348). During the pandemic period, femoral neck fractures have become dominant in the younger age group (p=0.038). Conclusion: Despite the restrictions in the COVID-19 pandemic, geriatric hip fracture rates did not change. At the same time, fracture type distribution was similar to the pre-pandemic period. Pandemic restrictions may have affected hip fracture in the younger age geriatric group. However, this finding alone may not impact the management and planning of geriatric hip fractures during the pandemic. [ABSTRACT FROM AUTHOR]

System identification is an important methodology used in control theory and constitutes the first step of control design. It is known that many real systems can be better characterized by fractional-order models. However, it is often quite complex and difficult to apply classical control theory methods analytically for fractional-order models. For this reason, integer-order models are generally considered in classical control theory. In this study, an alternative approximation method is proposed for fractional-order models. The proposed method converts a fractional-order transfer function directly into an integer-order transfer function. The proposed method is based on curve fitting that uses a quadratic system model and Equilibrium Optimizer (EO) algorithm. The curve fitting is implemented based on the unit step response signal. The EO algorithm aims to determine the optimal coefficients of integer-order transfer functions by minimizing the error between general parametric quadratic model and objective data. The objective data are unit step response of fractional-order transfer functions and obtained by using the Grünwald-Letnikov (GL) method in the Fractional-Order Modeling and Control (FOMCON) toolbox. Thus, the coefficients of an integer-order transfer function most properly can be determined. Some examples are provided based on different fractional-order transfer functions to evaluate the performance of the proposed method. The proposed method is compared with studies from the literature in terms of time and frequency responses. It is seen that the proposed method exhibits better model approximation performance and provides a lower order model. [ABSTRACT FROM AUTHOR]