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

Implications of return predictability for consumption dynamics and asset pricing

Two broad classes of consumption dynamics—long-run risks and rare disasters—have proven successful in explaining the equity premium puzzle when used in conjunction with recursive preferences. We show that bounds a-là Gallant, Hansen, and Tauchen that restrict the volatility of the stochastic discount factor by conditioning on a set of return predictors constitute a useful tool to discriminate between these alternative dynamics. In particular, we document that models that rely on rare disasters meet comfortably the bounds independently of the forecasting horizon and the asset returns used to construct the bounds. However, the specific nature of disasters is a relevant characteristic at the 1-year horizon: disasters that unfold over multiple years are more successful in meeting the predictors-based bounds than one-period disasters. Instead, at the 5-year horizon, the sole presence of disasters—even if one-period and permanent—is sufficient for the model to satisfy the bounds. Finally, the bounds point to multiple volatility components in consumption as a promising dimension for long-run risk models

Modelling credit spreads with time volatility, skewness, and kurtosis

This paper seeks to identify the macroeconomic and financial factors that drive credit spreads on bond indices in the US credit market. To overcome the idiosyncratic nature of credit spread data reflected in time varying volatility, skewness and thick tails, it proposes asymmetric GARCH models with alternative probability density functions. The results show that credit spread changes are mainly explained by the interest rate and interest rate volatility, the slope of the yield curve, stock market returns and volatility, the state of liquidity in the corporate bond market and, a heretofore overlooked variable, the foreign exchange rate. They also confirm that the asymmetric GARCH models and Student-t distributions are systematically superior to the conventional GARCH model and the normal distribution in in-sample and out-of-sample testing

Forecasting Bond Risk Premia Using Technical Analysis

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