Ralf Kellner

Distal femoral torsional osteotomy increases the contact pressure of the medial patellofemoral joint in biomechanical analysis

PurposeTorsional osteotomy of the distal femur allows anatomic treatment of patellofemoral instability and patellofemoral pain syndrome in cases of increased femoral antetorsion. The purpose of this study was to investigate the effects of distal femoral torsional osteotomy on pressure distribution of the medial and lateral patellar facet.MethodsNine fresh frozen human knee specimens were embedded in custom-made 3D-printed casts and tested with a robotic arm. Torsional osteotomy could be simulated ranging from increased femoral antetorsion of 25° with a corresponding lateralization of the patella to an overcorrected value of 5° of femoral antetorsion. The peak and mean lateral and medial compartment pressure was measured in 0°, 15°, 30°, 45°, 60° and 90° flexion beginning with neutral anatomic muscle rotation.ResultsThe medial aspect of the patella showed a significant influence of femoral torsion with an increase of mean and peak pressure in all flexion angles with progressive derotation from 15° external rotation to 5° internal rotation (p = 0.004). The overall pressure difference was highest in near extension and stayed on a constant level with further flexion. On the lateral facet, the derotation resulted in decrease of pressure in near extension; however, it had no significant influence on the mean and peak pressure through the different torsion angles (n.s.). Unlike on the medial facet, a significant consistent increase of peak pressure from 0° to 90° flexion could be shown (p = 0.022) on the lateral patella aspect.ConclusionDistal femoral torsional osteotomy to correct pathological femoral antetorsion leads to a redistribution of retropatellar pressure. External derotation leads to an increased peak pressure on the medial patellar facet and can impair simultaneous cartilage repair. However, as the lateral patellofemoral load decreases, it has a potential in preventing patellofemoral osteoarthritis.

Systematic Effects among Loss Given Defaults and their Implications on Downturn Estimation

Banks are obliged to provide downturn estimates for loss given defaults (LGDs) in the internal ratings-based approach. While downturn conditions are characterized by systematically higher LGDs, it is unclear which factors may best capture these conditions. As LGDs depend on recovery payments which are collected during varying economic conditions in the resolution process, it is challenging to identify suitable economic variables. Using a Bayesian Finite Mixture Model, we adapt random effects to measure economic conditions and to generate downturn estimates. We find that systematic effects vary among regions, i.e., the US and Europe, and strongly deviate from the economic cycle. Our approach offers straightforward supportive tools for decision makers. Risk managers are enabled to select their individual margin of conservatism based on their portfolios, while regulators might set a lower bound to guarantee conservatism. In comparison to other approaches, our proposal appears to be conservative enough during downturn conditions and inhibits over-conservatism.

The Role of Model Risk in Extreme Value Theory for Capital Adequacy

In the recent literature, methods from extreme value theory (EVT) have frequently been applied to the estimation of tail risk measures. While previous analyses show that EVT methods often lead to accurate estimates for risk measures, a potential drawback lies in large standard errors of the point estimates in these methods, as only a fraction of the data set is used. Thus, we comprehensively study the impact of model risk on EVT methods when determining the value-at-risk and expected shortfall. We distinguish between first-order effects of model risk, which consist of misspecification and estimation risk, and second-order effects of model risk, which refer to the dispersion of risk measure estimates, and show that EVT methods are less prone to first-order effects. However, they show a greater sensitivity toward second order effects. We find that this can lead to severe value-at-risk and expected shortfall underestimations and should be reflected in regulatory capital models.