Comparison Between Phenylephrine and Dopamine in Maintaining Cerebral Oxygen Saturation in Thoracic Surgery: A Randomized Controlled Trial

Fluid is usually restricted during thoracic surgery, and vasoactive agents are often administered to maintain blood pressure. One-lung ventilation (OLV) decreases arterial oxygenation; thus oxygen delivery to the brain can be decreased. In this study, we compared phenylephrine and dopamine with respect to maintaining cerebral oxygenation during OLV in major thoracic surgery.Sixty-three patients undergoing lobectomies were randomly assigned to the dopamine (D) or phenylephrine (P) group. The patients’ mean arterial pressure was maintained within 20% of baseline by a continuous infusion of dopamine or phenylephrine. Maintenance fluid was kept at 5 mL/kg/h. The depth of anesthesia was maintained with desflurane 1MAC and remifentanil infusion under bispectral index guidance. Regional cerebral oxygen saturation (rScO₂) and hemodynamic variables were recorded using near-infrared spectroscopy and esophageal cardiac Doppler.The rScO₂ was higher in the D group than the P group during OLV (OLV 60 min: 71 ± 6% vs 63 ± 12%; P = 0.03). The number of patients whose rScO₂ dropped more than 20% from baseline was 0 and 6 in the D and P groups, respectively (P = 0.02). The D group showed higher cardiac output, but lower mean arterial pressure than the P group (4.7 ± 1.0 vs 3.9 ± 1.2 L/min; 76.7 ± 8.1 vs 84.5 ± 7.5 mm Hg; P = 0.02, P = 0.02). Among the variables, age, hemoglobin concentration, and cardiac output were associated with rScO₂ by correlation analysis.Dopamine was superior to phenylephrine in maintaining cerebral oxygenation during OLV in thoracic surgery.     

Assessment of toxicity using dehydrogenases activity and mathematical modeling

Dehydrogenase activity is frequently used to assess the general condition of microorganisms in soil and activated sludge. Many studies have investigated the inhibition of dehydrogenase activity by various compounds, including heavy metal ions. However, the time after which the measurements are carried out is often chosen arbitrarily. Thus, it can be difficult to estimate how the toxic effects of compounds vary during the reaction and when the maximum of the effect would be reached. Hence, the aim of this study was to create simple and useful mathematical model describing changes in dehydrogenase activity during exposure to substances that inactivate enzymes. Our model is based on the Lagergrens pseudo-first-order equation, the rate of chemical reactions, enzyme activity, and inactivation and was created to describe short-term changes in dehydrogenase activity. The main assumption of our model is that toxic substances cause irreversible inactivation of enzyme units. The model is able to predict the maximum direct toxic effect (MDTE) and the time to reach this maximum (T_MDTE). In order to validate our model, we present two examples: inactivation of dehydrogenase in microorganisms in soil and activated sludge. The model was applied successfully for cadmium and copper ions. Our results indicate that the predicted MDTE and T_MDTE are more appropriate than EC₅₀ and IC₅₀ for toxicity assessments, except for long exposure times.     

Use of a Checklist During Observation of a Simulated Cardiac Arrest Scenario Does Not Improve Time to CPR and Defibrillation Over Observation Alone for Subsequent Scenarios

Theory: Immersive simulation is a common mode of education for medical students. Observation of clinical simulations prior to participation is believed to be beneficial, though this is often a passive process. Active observation may be more beneficial. Hypotheses: The hypothesis tested in this study was that the active use of a simple checklist during observation of an immersive simulation would result in better participant performance in a subsequent scenario compared with passive observation alone. Methods: Medical students were randomized to either passive or active (with checklist) observation of an immersive simulation involving cardiac arrest prior to participating in their own simulation. Performance measures included time to cardiopulmonary resuscitation (CPR) and time to defibrillation and were compared between first and second scenarios as well as between passive and active observers. Results: Seventy-nine simulations involving 232 students were conducted. Mean time to CPR was 18 seconds (SD = 11.6) for those using the checklist and 24 seconds (SD = 15.8) for those who observed passively (M difference = 6 seconds), t(35) = 1.46, p =.153. Time to defibrillation was 94 seconds (SD = 26.4) for those using the checklist and 92 seconds (SD = 23.8) for those who observed passively (M difference = –2 seconds), t(38) =.21, p =.837. Time to CPR was 24 seconds (SD = 15.8) for passive observers and 31 seconds (SD = 21.0; M difference = 7 seconds), t(35) = 1.13, p =.265, for their first scenario counterparts. Time to CPR was 18 seconds (SD = 11.6) for active observers and 36 seconds (SD = 26.2; M difference = 18 seconds), t(24) = 2.81, p =.010, for their first scenario counterparts. Time to defibrillation was 92 seconds (SD = 23.8) for passive observers and 125 seconds (SD = 32.2; M difference = 33 seconds), t(33) = 3.63, p =.001, for their first scenario counterparts. Time to defibrillation was 94 seconds (SD = 26.4) for the active observers and 132 seconds (SD = 52.9; M difference = 38 seconds), t(28) =.46, p =.008, for their first scenario counterparts. Conclusions: Observation alone leads to improved performance in the management of a simulated cardiac arrest. The active use of a simple skills-based checklist during observation did not appear to improve performance over passive observation alone.     

Genetic Approaches to Hypothalamic-Pituitary-Adrenal Axis Regulation

The normal function of the hypothalamic-pituitary-adrenal (HPA) axis, and resultant glucocorticoid (GC) secretion, is essential for human health. Disruption of GC regulation is associated with pathologic, psychological, and physiological disease states such as depression, post-traumatic stress disorder, hypertension, diabetes, and osteopenia, among others. As such, understanding the mechanisms by which HPA output is tightly regulated in its responses to environmental stressors and circadian cues has been an active area of investigation for decades. Over the last 20 years, however, advances in gene targeting and genome modification in rodent models have allowed the detailed dissection of roles for key molecular mediators and brain regions responsible for this control in vivo to emerge. Here, we summarize work done to elucidate the function of critical neuropeptide systems, GC-signaling targets, and inflammation-associated pathways in HPA axis regulation and behavior, and highlight areas for future investigation.