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Introduction Suboptimal outcomes were observed in cases of unstable pertrochanteric fractures, even when bone healing occurs without complications. This raises the question of whether factors beyond bone health integrity, such as the frailty of muscles, contribute to these less favorable results. Muscles, particularly the gluteal muscles, not only influence functional ability but also serve as a cushion that provides physical protection against external forces during falls. When gluteal muscles are thin or weak, their ability to absorb the impact from a fall diminishes, potentially leading to unstable fractures. In this study, we compared gluteal muscle-related indices, including cross-sectional area (CSA) and muscle density, between stable and unstable pertrochanteric fractures. The aim of this study was to employ a retrospective approach to investigate the causes of unstable fractures, with a focus on potential muscular pathology. It was hypothesized that reduced CSA and lower density of the gluteal muscles would be associated with unstable fractures. Material and methods Geriatric patients aged 70 years or older with pertrochanteric fractures requiring surgical intervention were retrospectively identified from databases. These fractures classified as stable (A1) or unstable (A2) based on the Revised Arbeitsgemeinschaft für Osteosynthesefragen (AO)/Orthopaedic Trauma Association (OTA) Classification were compared based on demographic variables (age, height, body mass index (BMI), and fracture laterality) as well as muscle-related indices. A multivariate logistic regression model was employed to identify predictors of unstable fractures. Independent variables included age at the time of surgery, height, BMI, and muscular metrics CSA and density of the gluteus maximus and gluteus medius. Results Out of 220 patients identified from the database, 111 patients with an average age of 88 years (ranging from 71 to 103 years) were included. This cohort consisted of 40 patients with stable fractures (A1) and 71 patients with unstable fractures (A2). Among the demographical data, only fracture laterality demonstrated a significant difference between the groups (p < 0.05). Regarding gluteal muscle data, the CSA/BMI of both the gluteus maximus and medius, as well as the density of the gluteus medius, did not show significant differences between the two groups. The only exception was the density of the gluteus maximus, which was significantly lower in the unstable group (p < 0.01). A binary logistic regression analysis was conducted to identify risk factors for unstable fractures. The analysis found that the density of the gluteus maximus was a statistically significant predictor, with an odds ratio of 0.959 (95% CI, 0.923 to 0.997; p = 0.03). To determine an optimal cut-off value, receiver operating characteristic (ROC) analysis was performed for the density of the gluteus maximus. The Youden index identified a cut-off value of 20.8 HU for the gluteus maximus density as the optimal threshold (area under the curve (AUC): 0.625; 95% CI: 0.520-0.730). Conclusion This retrospective study investigated whether unstable pertrochanteric fractures in elderly female patients were linked to weakened gluteal muscles, compared to stable fractures, and suggested this muscle weakness may contribute to poor functional outcomes. Our binary regression analysis indicated that decreased muscle density in the gluteus maximus increases the risk of unstable fractures., Competing Interests: Human subjects: Consent for treatment and open access publication was obtained or waived by all participants in this study. Nishi Hospital Ethics Committee, and Himeji Central Hospital Ethics Committee issued approval 2021-1, 2024-43. The study was approved by the Ethics Committees of both hospitals: Nishi Hospital Ethics Committee (approval number 2021-1) and Himeji Central Hospital Ethics Committee (approval number 2024-43). Animal subjects: All authors have confirmed that this study did not involve animal subjects or tissue. Conflicts of interest: In compliance with the ICMJE uniform disclosure form, all authors declare the following: Payment/services info: All authors have declared that no financial support was received from any organization for the submitted work. Financial relationships: All authors have declared that they have no financial relationships at present or within the previous three years with any organizations that might have an interest in the submitted work. Other relationships: All authors have declared that there are no other relationships or activities that could appear to have influenced the submitted work., (Copyright © 2024, Noda et al.)

The thumb function is complex, and accurate evaluation through images or videos is difficult. Pose estimation, a technology that uses artificial intelligence (AI) to estimate skeletal detection of the body, is gaining popularity. In this study, we combined the pose estimation library MediaPipe-Hands and five machine learning (ML) models to predict the radial abduction angle of the thumb. Radial abduction movements of 20 hands from 10 healthy volunteers were captured on video and processed into 5,000 images. Angle measurements by goniometer were used as true values to evaluate the angle reliability of the MediaPipe-Hands and the angle reliability of the MediaPipe-Hands combined with ML. The correlation coefficient (CC) between the angle measured by goniometry and the angle calculated by MediaPipe-Hands was 0.84. In contrast, applying ML to MediaPipe-Hands resulted in models with improved accuracy, and all models showed high CCs (0.94-099) with angle measurements taken by goniometry. The ML model also predicted the abduction angles when the camera was taken from three different angles. In visualizing the features that the AI deemed important, the ML model predicted the abduction angle by focusing on the tip distance between the thumb and index finger along with the angle of the metacarpophalangeal joint between the thumb and middle finger. These results enable angle estimation even without frontal imaging with a camera, and expansion of this system may lead to real-time functional assessment in telemedicine and rehabilitation without the need for physical contact., Competing Interests: Human subjects: Consent was obtained or waived by all participants in this study. The Ethics Committee at Kobe University Graduate School of Medicine issued approval B210009. Informed consent was obtained from all participants. The approved title of this study is “Biomechanical Study of the Elbow and Wrist Joints,” which is in line with a series of previously reported studies. . Animal subjects: All authors have confirmed that this study did not involve animal subjects or tissue. Conflicts of interest: In compliance with the ICMJE uniform disclosure form, all authors declare the following: Payment/services info: All authors have declared that no financial support was received from any organization for the submitted work. Financial relationships: All authors have declared that they have no financial relationships at present or within the previous three years with any organizations that might have an interest in the submitted work. Other relationships: All authors have declared that there are no other relationships or activities that could appear to have influenced the submitted work., (Copyright © 2024, Shinohara et al.)

Introduction Amid an increasing number of patients with pertrochanteric fractures, early prediction of postoperative gait potential could reduce unnecessary rehabilitation and hospitalization. The relationship between preoperative gluteal muscle condition and postoperative gait outcomes remains unclear. The gluteal muscles are crucial for mobility, and their cross-sectional area (CSA) and fatty infiltration are indicators of physical function. Preoperative computed tomography (CT) provides quantitative data on muscle CSA and density, measured in Hounsfield Units (HU). This study aimed to identify which preoperative muscle index, CSA, BMI-adjusted CSA, or muscle density, best predicts postoperative gait ability. We hypothesized that a higher adjusted CSA and muscle density in the gluteus muscles would be associated with superior gait performance. Materials and methods Preoperative assessments included radiographs and CT scans. Patients under 75, with less than four weeks of follow-up, prior contralateral hip surgery, prefracture immobility, male patients, high-energy trauma, or conditions impairing physical performance were excluded. Gait performance was evaluated four weeks postoperatively, classifying patients into two groups: the 'parallel bar group,' requiring parallel bars, and the 'walker group,' walking independently. Patients underwent CM nailing. Preoperative CT scans measured the CSA and muscle density of the gluteus maximus and medius. Measurements were taken from the non-injured side to avoid interference from the fracture. Muscle borders were manually traced, and the CSA and muscle density in HU were calculated. Results Out of 81 patients, 49 met the inclusion criteria (mean age: 87). The patients were divided into the 'parallel bar group' (n=19) and the 'walker group' (n=30) based on postoperative gait performance. No significant differences in age, weight, height, or fracture laterality were observed between groups. The mean (and standard deviation (SD)) of CSA for the gluteus maximus in the 'parallel bar group'/in the 'walker group' was 2211.8 ± 469.8 mm²/2440.0 ± 586.2 mm², respectively (p=0.15), and for the gluteus medius, it was 1751.7 ± 415.2mm²/1869.1 ± 448.3mm², respectively (p=0.36). The mean (and SD) muscle density for the gluteus maximus in the 'parallel bar group'/in the 'walker group' was 13.6 ± 12.7 HU / 20.6 ± 13.0 HU (p=0.07), and for the gluteus medius, it was 25.2 ± 8.4 HU/31.8 ± 10.1 HU, respectively (p=0.02). The ROC curve identified a 30.9 HU cut-off for gluteus medius density, with sensitivity and specificity of 60.7% and 78.9%. The mean (and SD) of BMI-adjusted CSA for the gluteus maximus in the 'parallel bar group'/ in the 'walker group' was 116.4 ± 26.8 m²/10 6 kg/124.3 ± 29.2 m²/10 6 kg, respectively (p=0.35), and for the gluteus medius, it was 93.3 ± 27.2 m²/10 6 kg/95.4 ± 21.3m²/10 6 kg, respectively (p=0.78). Conclusion This study analyzed preoperative CT images of women aged 75 and older with pertrochanteric fractures, comparing gluteal muscle CSA and density with postoperative walking ability. The gluteus medius density was significantly higher in the superior gait group, with a cut-off value of 30.9 HU. However, no significant differences were found in the gluteus maximus density, CSA, or BMI-adjusted CSA. These findings partially support the hypothesis, emphasizing the importance of muscle evaluation in predicting postoperative gait performance., Competing Interests: Human subjects: Consent was obtained or waived by all participants in this study. The Nishi Hospital Ethics Committee issued approval 2021-1. Animal subjects: All authors have confirmed that this study did not involve animal subjects or tissue. Conflicts of interest: In compliance with the ICMJE uniform disclosure form, all authors declare the following: Payment/services info: All authors have declared that no financial support was received from any organization for the submitted work. Financial relationships: All authors have declared that they have no financial relationships at present or within the previous three years with any organizations that might have an interest in the submitted work. Other relationships: All authors have declared that there are no other relationships or activities that could appear to have influenced the submitted work., (Copyright © 2024, Noda et al.)

MediaPipe Hand (MediaPipe) is an artificial intelligence (AI)-based pose estimation library. In this study, MediaPipe was combined with four machine learning (ML) models to estimate the rotation angle of the thumb. Videos of the right hands of 15 healthy volunteers were recorded and processed into 9000 images. The rotation angle of the thumb (defined as angle θ from the palmar plane, which is defined as 0°) was measured using an angle measuring device, expressed in a radian system. Angle θ was then estimated by the ML model by using parameters calculated from the hand coordinates detected by MediaPipe. The linear regression model showed a root mean square error (RMSE) of 12.23, a mean absolute error (MAE) of 9.9, and a correlation coefficient of 0.91. The ElasticNet model showed an RMSE of 12.23, an MAE of 9.95, and a correlation coefficient of 0.91; the support vector machine (SVM) model showed an RMSE of 4.7, an MAE of 2.5, and a correlation coefficient of 0.99. The LightGBM model achieved high values: an RMSE of 4.58, an MAE of 2.62, and a correlation coefficient of 0.99. Based on these findings, we concluded that the thumb rotation angle can be estimated with high accuracy by combining MediaPipe and ML., Competing Interests: The authors have declared that no competing interests exist., (Copyright © 2024, Ehara et al.)

Introduction We introduced a novel numerical index known as posterior protrusion measures (PPM), derived from lateral plain radiograph images, which effectively serves to distinguish stable from unstable pertrochanteric fractures. The present study aims to scrutinize PPM values among two classified fracture patterns, stable and unstable, within the three-dimensional (3D) CT classification system, establishing a numeric threshold for PPM to differentiate between these groups; explore the potential relationship between the PPM index and unclassified categories; investigate how groups divided by the PPM threshold value can predict fracture stability based on 3D CT. Materials and methods In this study, three observers were tasked with measuring PPM on a single occasion. The chi-square test assessed the association between each demographic parameter on a categorical scale and stable/unstable groups. Continuous variables were also subject to examination. Receiver operating characteristic (ROC) analysis was employed to determine optimal cut-off points of PPM for predicting the presence of stable versus unstable groups. Additionally, the chi-square test examined the linear relation between separated groups based on the defined threshold PPM value and the stable/unstable groups. Results A total of 106 pertrochanteric fractures were identified using CT scan images and plain radiographs in the 3D CT classification system, revealing the stable group of 35 patients and the unstable group of 71 patients. The PPM values for stable/unstable fractures were, on average (± standard deviation), 0.34±0.25/0.50±0.29 for observer 1, 0.31±0.23/0.57±0.31 for observer 2, and 0.41±0.29/0.57±0.26 for observer 3, respectively (p<0.01). We established 0.3 as the cut-off value for PPM. The average PPM value among three observers represented each patient to assess fracture stability. The group with PPM <0.3 included 27 patients (16 stable and 11 unstable), and the group with PPM ≥0.3 group comprised 79 patients (19 stable and 60 unstable; p<0.005). Conclusion The present study revealed a significant difference in PPM values among stable and unstable 3D CT classification groups. Additionally, a threshold PPM value of 0.3 suggests a pivotal point for differentiating fracture stability. This innovative methodology makes a substantial contribution to clinical endeavors, potentially circumventing the necessity for 3D CT scanning., Competing Interests: The authors have declared that no competing interests exist., (Copyright © 2023, Noda et al.)