Characteristics and Treatment Strategies for Basicervical and Transcervical Shear Fractures of the Femoral Neck.
Hiroaki KijimaShin YamadaTetsuya KawanoMotoharu KomatsuYosuke IwamotoNatsuo KonishiHitoshi KubotaHiroshi TazawaTakayuki TaniNorio SuzukiKeiji KamoKen SasakiMasashi FujiiItsuki NagahataTakanori MiuraShun IgarashiNaohisa MiyakoshiPublished in: Journal of clinical medicine (2023)
This study aimed to define basicervical and transcervical shear fractures using area classification and to determine the optimal osteosynthesis implants for them. The clinical outcomes of 1042 proximal femur fractures were investigated. A model of the proximal femur of a healthy adult was created from computed tomography images, and basicervical and transcervical shear fractures were established in the model. Osteosynthesis models were created using a short femoral nail with a single lag screw or two lag screws and a long femoral nail with a single lag screw or two lag screws. The minimum principal strains of the fracture surfaces were compared when the maximum loads during walking were applied to these models using finite element analysis software. Basicervical fractures accounted for 0.96% of all proximal femur fractures, 67% of which were treated with osteosynthesis; the failure rate was 0%. Transcervical shear fractures accounted for 9.6% of all proximal femur fractures, 24% of which were treated with osteosynthesis; the failure rate was 13%. Finite element analysis showed that transcervical shear fracture has high instability. To perform osteosynthesis, multiple screw insertions into the femoral head and careful postoperative management are required; joint replacement should be considered to achieve early mobility.
Keyphrases
- finite element analysis
- computed tomography
- bone mineral density
- deep learning
- machine learning
- escherichia coli
- young adults
- body composition
- cystic fibrosis
- positron emission tomography
- staphylococcus aureus
- finite element
- pseudomonas aeruginosa
- postmenopausal women
- soft tissue
- data analysis
- single molecule
- childhood cancer