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Background: The injury of femoral head varies among femoral head fractures (FHFs). In addition, the injury degree of the femoral head is a significant predictor of femoral neck fracture (FNF) incidence in patients with FHFs. However, the exact measurement methods have yet been clearly defined based on injury models of FHFs. This study aimed to design a new measurement for the injury degree of the femoral head on 2D and 3D models with computed tomography (CT) images and investigate its association with FHFs with FNF.Methods: A consecutive series of 209 patients with FHFs was assessed regarding patient characteristics, CT images, and rate of FNF. New parameters for injury degree of femoral head, including percentage of maximum defect length (PMDL) in the 2D CT model and percentage of fracture area (PFA) in the 3D CT-reconstruction model, were respectively measured. Four 2D parameters included PMDLs in the coronal, cross-sectional and sagittal plane and average PMDL across all three planes. Reliability tests for all parameters were evaluated in 100 randomly selected patients. The PMDL with better reliability and areas under curves (AUCs) was finally defined as the 2D parameter. Factors associated with FNF were determined by binary logistic regression analysis. The sensitivity, specificity, likelihood ratios, and positive and negative predictive values for different cut-off values of the 2D and 3D parameters were employed to test the diagnostic accuracy for FNF prediction.Results: Intra- and inter-class coefficients for all parameters were ≥0.887. AUCs of all parameters ranged from 0.719 to 0.929 (p < 0.05). The average PMDL across all three planes was defined as the 2D parameter. The results of logistic regression analysis showed that average PMDL across all three planes and PFA were the significant predictors of FNF (p < 0.05). The cutoff values of the average PMDL across all three planes and PFA were 91.65% and 29.68%. The sensitivity, specificity, positive likelihood ratio, negative likelihood ratio, predictive positive value and negative predictive value of 2D (3D) parameters were 91.7% (83.3%), 93.4% (58.4%), 13.8 (2.0), 0.09 (0.29), 45.83% (10.87%), and 99.46% (98.29%).Conclusion: The new measurement on 2D and 3D injury models with CT has been established to assess the fracture risk of femoral neck in patients with FHFs in the clinic practice. 2D and 3D parameters in FHFs were a feasible adjunctive diagnostic tool in identifying FNFs. In addition, this finding might also provide a theoretic basis for the investigation of the convenient digital-model in complex injury analysis.

PurposeThe aim of the current study is to investigate the impact of Baduanjin, a traditional Chinese exercise, on quality of life and sleep quality in breast cancer survivors receiving aromatase inhibitor (AI) therapy.MethodsA total of 72 breast cancer survivors who had received AI treatment for more3 than 6 months were enrolled in the current study using non-probability consecutive sampling procedure. Participants were randomly assigned in a 1:1 ratio to a 12-week Baduanjin exercise program or to a wait-list control group. The Baduanjin exercise group performed two 90-min supervised sessions per week. The primary outcomes were changes in quality of life measured by the European Organization for Research and Treatment of Cancer Quality-of-Life Questionnaire Core 30 (EORTC QLQ-C30) and in sleep quality evaluated using the Pittsburgh Sleep Quality Index (PSQI).ResultsA total of 68 participants completed the trial (Baduanjin exercise group: n = 33; control group: n = 35). Baseline values for quality of life did not differ between groups. Both global quality of life and physical functioning scores increased significantly by 12.39 (P < 0.001) and 8.48 (P < 0.001) in the Baduanjin exercise group compared with those in the control. Overall PSQI score also decreased by 4.85 (P < 0.001) in the Baduanjin exercise group, whereas it increased by 0.34 in the control group.ConclusionBaduanjin exercise training led to improvement in the quality of life and sleep quality of breast cancer patients undergoing AI therapy.

BackgroundA detailed depiction of nutrient foramina is useful for defining guidelines and minimising iatrogenic damage during hip surgery. Therefore, this study aimed to define the location and frequency of nutrient foramina in the proximal femur using mapping techniques.MethodsOne hundred dry human cadaveric proximal femurs, comprising 56 left and 44 right femurs, were scanned using a three-dimensional scanner, with scanning distance 200 mm, precision 0.01 mm, and measuring point 0.04 mm. The image resolution of 1,310,000 pixels was obtained. Digital imaging models were acquired from the proximal femur surface. All the nutrient foramina in each model were identified and marked. The nutrient foramina models were superimposed on one another and oriented to fit a standard template of the femur’s proximal aspect. Three-dimensional mapping in the proximal femur’s nutrient foramina was performed.ResultsThe nutrient foramina’s location and dense zones were identified. The dense zones were distributed along the vascular course and gaps between the muscle attachment sites. Eighteen dense zones were identified and found to be location-dependent. They were located in the central part of the fovea capitis femoris, subcapital and basicervical areas of the femoral neck, and muscle attachment gaps of the femoral trochanter.ConclusionsThe terminal branch of the nutrient vessels entering the nutrient foramina is at risk for iatrogenic damage during hip surgeries, especially in cases of close bone exposures. There are 18 dense zones that need to be considered for a safer approach to the proximal femur. To minimise iatrogenic damage to the nutrient vessels entering the nutrient foramina, the dense areas should be avoided when technically possible.