Evaluation of a combination of alfaxalone and methadone, with or without midazolam, for premedication in healthy dogs

Introduction: The study objective was to evaluate sedative and physiologic effects of midazolam associated with a combination of methadone and alfaxalone for IM premedication in dogs. Methods: Sixteen healthy dogs of various breeds, weighing 5–12 kg, classified ASA status I-II, randomly received a combination of 0.5 mg kg−1 of methadone and 1 mg kg−1 of alfaxalone with (MMA) or without (MA) 0.5 mg kg−1 of midazolam by IM injection. Quality of sedation was assessed at 10, 15, 20 and 25 minutes post-injection, by an observer blinded to treatment. Cardiovascular, respiratory variables and additional intravenous alfaxalone required for endotracheal intubation were recorded. Data were analyzed with mixed-effect linear model on rank or Mann-Whitney rank-sum test (p≤0.05). Results: There was no significant difference over time in heart rate, respiratory rate, systolic blood pressure, SpO2 and temperature between MA and MMA premedication. Sedation increased over time (p < 0.01), however dogs premedicated with MMA appeared significantly less sedated than dogs premedicated with MA at 15 (p=0.02), 20 (p=0.02) and 25 minutes (p=0.01) post-injection. This was substantiated by the fact that dogs premedicated with MMA were almost four times more likely to show delirium than those premedicated with MA (OR 3.95, CI 0.69-7.21, p=0.02). The amount of alfaxalone needed for intubation did not differ between treatments (p=0.92). Conclusion: Results suggest that adding midazolam to an IM combination of methadone and alfaxalone does not improve sedation scores or amount of agent needed for intubation in healthy dogs

Derivative pricing for a multi-curve extension of the Gaussian, exponentially quadratic short rate model

The recent financial crisis has led to so-called multi-curve models for the term structure. Here we study a multi-curve extension of short rate models where, in addition to the short rate itself, we introduce short rate spreads. In particular, we consider a Gaussian factor model where the short rate and the spreads are second order polynomials of Gaussian factor processes. This leads to an exponentially quadratic model class that is less well known than the exponentially affine class. In the latter class the factors enter linearly and for positivity one considers square root factor processes. While the square root factors in the affine class have more involved distributions, in the quadratic class the factors remain Gaussian and this leads to various advantages, in particular for derivative pricing. After some preliminaries on martingale modeling in the multi-curve setup, we concentrate on pricing of linear and optional derivatives. For linear derivatives, we exhibit an adjustment factor that allows one to pass from pre-crisis single curve values to the corresponding post-crisis multi-curve values

Forecasting Bond Risk Premia Using Technical Analysis

This paper is selected as one of the Top Ten Paper in Forecasting in SSRN