Aims. This study aimed to identify the effect of anatomical tibial component (ATC) design on load distribution in the periprosthetic tibial bone of Koreans using finite element analysis (FEA). Methods. 3D finite element models of 30 tibiae in Korean women were created. A symmetric tibial component (STC, NexGen LPS-Flex) and an ATC (Persona) were used in surgical simulation. We compared the FEA measurements (von Mises stress and principal strains) around the stem tip and in the medial half of the proximal tibial bone, as well as the distance from the distal stem tip to the shortest anteromedial cortical bone. Correlations between this distance and FEA measurements were then analyzed. Results. The distance from the distal stem tip to the shortest cortical bone showed no statistically significant difference between implants. However, the peak von Mises stress around the distal stem tip was higher with STC than with ATC. In the medial half of the proximal tibial bone: 1) the mean von Mises stress, maximum principal strain, and minimum principal strain were higher with ATC; 2) ATC showed a positive correlation between the distance and mean von Mises stress; 3) ATC showed a negative correlation between the distance and mean minimum principal strain; and 4) STC showed no correlation between the distance and mean measurements. Conclusion. Implant design affects the load distribution on the periprosthetic tibial bone, and ATC can be more advantageous in preventing stress-shielding than STC. However, under certain circumstances with short distances, the advantage of ATC may be offset. Cite this article: Bone Joint Res 2022;11(5):252–259

Aims. To devise a method to quantify and optimize tightness when inserting cortical screws, based on bone characterization and screw geometry. Methods. Cortical human cadaveric diaphyseal tibiae screw holes (n = 20) underwent destructive testing to firstly establish the relationship between cortical thickness and experimental stripping torque (T. str. ), and secondly to calibrate an equation to predict T. str. Using the equation’s predictions, 3.5 mm screws were inserted (n = 66) to targeted torques representing 40% to 100% of T. str. , with recording of compression generated during tightening. Once the target torque had been achieved, immediate pullout testing was performed. Results. Cortical thickness predicted T. str. (R. 2. = 0.862; p < 0.001) as did an equation based on tensile yield stress, bone-screw friction coefficient, and screw geometries (R. 2. = 0.894; p < 0.001). Compression increased with screw tightness up to 80% of the maximum (R. 2. = 0.495; p < 0.001). Beyond 80%, further tightening generated no increase in compression. Pullout force did not change with variations in submaximal tightness beyond 40% of T. str. (R. 2. = 0.014; p = 0.175). Conclusion. Screw tightening between 70% and 80% of the predicted maximum generated optimum compression and pullout forces. Further tightening did not considerably increase compression, made no difference to pullout, and increased the risk of the screw holes being stripped. While further work is needed for development of intraoperative methods for accurate and reliable prediction of the maximum tightness for a screw, this work justifies insertion torque being considerably below the maximum. Cite this article: Bone Joint Res 2020;9(8):493–500