Predictors of cut-out after cephalomedullary nail fixation of pertrochanteric fractures: a retrospective study of 813 patients

Cut-out is the most common mechanical complication of the osteosynthesis of pertrochanteric fractures. This complication determines a significant increase in morbidity in elderly patient. Cut-out is defined as the varus collapse of the femoral head-neck fragment with the extrusion of the cephalic screw. Surgical treatment of cut-out might lead to further complications, longer rehabilitation, increased social burden and healthcare system costs. The aim of the study is to identify the predictors of cut-out to prevent its occurrence. Study population included all patients affected by extracapsular fracture of the proximal femur who were admitted and treated with short cephalomedullary nailing at the Cattinara Hospital-ASUITS of Trieste between 2009 and 2014. A retrospective analysis of clinical and radiographic data was carried out and cut-out cases recorded. The data collected on the study population were analyzed to find an eventual correlation with the occurrence of cut-out. The independent variables were age, gender, side of the fracture, ASA class, Evans classification, nailing system, quality of reduction, TAD, CalTAD, and Parker ratio. The study population counted 813 cases, with an F:M ratio of 4:1 and a mean age of 84.7 years. The cut-out was recorded in 18 cases (2.2%). There was no statistically significant association between cut-out and age, sex, side of fracture, ASA class, and nailing system. The Evans classification, the quality of reduction, the TAD, the CalTAD, and the Parker's ratio demonstrated a significant correlation at univariate analysis with cut-out. The results of multivariate analysis confirmed that TAD, Parker AP, and quality of reduction were independently significantly correlated to cut-out. The results of the present study demonstrate that good quality of reduction and correct position of the lag screw are likely to decrease the risk of cut-out complication. A nomogram for cut-out prediction is proposed for clinical validation.