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In response to letter to the editor: calcar fracture gapping: a reliable predictor of anteromedial cortical support failure after cephalomedullary nailing for pertrochanteric femur fractures

We appreciate the interest by Drs. Hagiyama and coauthors in our work entitled “Calcar fracture gapping: a reliable predictor of anteromedial cortical support failure after cephalomedullary nailing for pertrochanteric femur fractures”. They discussed several pertinent points and it is our pleasure t...

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Detalles Bibliográficos
Autores principales: Chang, Shi-Min, Mao, Wei, Li, Shi-Jie, Song, Hui
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9331109/
https://www.ncbi.nlm.nih.gov/pubmed/35902901
http://dx.doi.org/10.1186/s12891-022-05689-9
Descripción
Sumario:We appreciate the interest by Drs. Hagiyama and coauthors in our work entitled “Calcar fracture gapping: a reliable predictor of anteromedial cortical support failure after cephalomedullary nailing for pertrochanteric femur fractures”. They discussed several pertinent points and it is our pleasure to respond their concerns in order. Firstly, we agree that calcar fracture gap and anteromedial cortical support are different concepts, though both of them were used to evaluate the displacement of fracture reduction quality. Secondly, our primary outcome parameter was the threshold distance of calcar fracture gapping in anteroposterior and lateral fluoroscopies, which was calculated based on sensitivity and specificity by receiver operating characteristic curves. Thirdly, we took immediate post-operative fluoroscopic images in 3 views to describe the initial reduction quality as baseline to compare and calculate the changes with three-dimensional computed tomography, which was taken about one week after operation for confirming secondary stability after head-neck sliding and impaction. Lastly, the parameters selected in multivariable analysis. Future work with better study-design is needed to improve the prediction of patient outcomes.