EOY summary 2018.

Clinical monitoring and technology are at the heart of anesthesiology, and new technological developments will help to define how anesthesiology will evolve as a profession. Anesthesia related research published in the JCMC in 2018 mainly pertained to ICU sedation with inhaled agents, anesthesia workstation technology, and monitoring of different aspects of depth of anesthesia.

Mathematical method to build an empirical model for inhaled anesthetic agent wash-in.

BACKGROUND: The wide range of fresh gas flow - vaporizer setting (FGF - FD) combinations used by different anesthesiologists during the wash-in period of inhaled anesthetics indicates that the selection of FGF and FD is based on habit and personal experience. An empirical model could rationalize FGF - FD selection during wash-in. METHODS: During model derivation, 50 ASA PS I-II patients received desflurane in O2 with an ADU® anesthesia machine with a random combination of a fixed FGF - FD setting. The resulting course of the end-expired desflurane concentration (FA) was modeled with Excel Solver, with patient age, height, and weight as covariates; NONMEM was used to check for parsimony. The resulting equation was solved for FD, and prospectively tested by having the formula calculate FD to be used by the anesthesiologist after randomly selecting a FGF, a target FA (FAt), and a specified time interval (1 - 5 min) after turning on the vaporizer after which FAt had to be reached. The following targets were tested: desflurane FAt 3.5% after 3.5 min (n = 40), 5% after 5 min (n = 37), and 6% after 4.5 min (n = 37). RESULTS: Solving the equation derived during model development for FD yields FD=-(e(-FGF*-0.23+FGF*0.24)*(e(FGF*-0.23)*FAt*Ht*0.1-e(FGF*-0.23)*FGF*2.55+40.46-e(FGF*-0.23)*40.46+e(FGF*-0.23+Time/-4.08)*40.46-e(Time/-4.08)*40.46))/((-1+e(FGF*0.24))*(-1+e(Time/-4.08))*39.29). Only height (Ht) could be withheld as a significant covariate. Median performance error and median absolute performance error were -2.9 and 7.0% in the 3.5% after 3.5 min group, -3.4 and 11.4% in the 5% after 5 min group, and -16.2 and 16.2% in the 6% after 4.5 min groups, respectively. CONCLUSIONS: An empirical model can be used to predict the FGF - FD combinations that attain a target end-expired anesthetic agent concentration with clinically acceptable accuracy within the first 5 min of the start of administration. The sequences are easily calculated in an Excel file and simple to use (one fixed FGF - FD setting), and will minimize agent consumption and reduce pollution by allowing to determine the lowest possible FGF that can be used. Different anesthesia machines will likely have different equations for different agents.

Desflurane Consumption During Automated Closed-circuit Delivery is Higher Than When a Conventional Anesthesia Machine is Used With a Simple Vaporizer-O2-N2O Fresh Gas Flow Sequence.

BACKGROUND: The Zeus® (Dräger, Lübeck, Germany), an automated closed-circuit anesthesia machine, uses high fresh gas flows (FGF) to wash-in the circuit and the lungs, and intermittently flushes the system to remove unwanted N2. We hypothesized this could increase desflurane consumption to such an extent that agent consumption might become higher than with a conventional anesthesia machine (Anesthesia Delivery Unit [ADU®], GE, Helsinki, Finland) used with a previously derived desflurane-O2-N2O administration schedule that allows early FGF reduction. METHODS: Thirty-four ASA PS I or II patients undergoing plastic, urologic, or gynecologic surgery received desflurane in O2/N2O. In the ADU group (n = 24), an initial 3 min high FGF of O2 and N2O (2 and 4 L.min-1, respectively) was used, followed by 0.3 L.min-1 O2 + 0.4 L.min-1 N2O. The desflurane vaporizer setting (FD) was 6.5% for the first 15 min, and 5.5% during the next 25 min. In the Zeus group (n = 10), the Zeus® was used in automated closed circuit anesthesia mode with a selected end-expired (FA) desflurane target of 4.6%, and O2/N2O as the carrier gases with a target inspired O2% of 30%. Desflurane FA and consumption during the first 40 min were compared using repeated measures one-way ANOVA. RESULTS: Age and weight did not differ between the groups (P > 0.05), but patients in the Zeus group were taller (P = 0.04). In the Zeus group, the desflurane FA was lower during the first 3 min (P < 0.05), identical at 4 min (P > 0.05), and slightly higher after 4 min (P < 0.05). Desflurane consumption was higher in the Zeus group at all times, a difference that persisted after correcting for the small difference in FA between the two groups. CONCLUSION: Agent consumption with an automated closed-circuit anesthesia machine is higher than with a conventional anesthesia machine when the latter is used with a specific vaporizer-FGF sequence. Agent consumption during automated delivery might be further reduced by optimizing the algorithm(s) that manages the initial FGF or by tolerating some N2 in the circuit to minimize the need for intermittent flushing.

Can Modern Infrared Analyzers Replace Gas Chromatography to Measure Anesthetic Vapor Concentrations?

BACKGROUND: Gas chromatography (GC) has often been considered the most accurate method to measure the concentration of inhaled anesthetic vapors. However, infrared (IR) gas analysis has become the clinically preferred monitoring technique because it provides continuous data, is less expensive and more practical, and is readily available. We examined the accuracy of a modern IR analyzer (M-CAiOV compact gas IR analyzer (General Electric, Helsinki, Finland) by comparing its performance with GC. METHODS: To examine linearity, we analyzed 3 different concentrations of 3 different agents in O2: 0.3, 0.7, and 1.2% isoflurane; 0.5, 1, and 2% sevoflurane; and 1, 3, and 6% desflurane. To examine the effect of carrier gas composition, we prepared mixtures of 1% isoflurane, 1 or 2% sevoflurane, or 6% desflurane in 100% O2 (= O2 group); 30%O2+ 70%N2O (= N2O group), 28%O2 + 66%N2O + 5%CO2 (= CO2 group), or air. To examine consistency between analyzers, four different M-CAiOV analyzers were tested. RESULTS: The IR analyzer response in O2 is linear over the concentration range studied: IR isoflurane % = -0.0256 + (1.006 * GC %), R = 0.998; IR sevoflurane % = -0.008 + (0.946 * GC %), R = 0.993; and IR desflurane % = 0.256 + (0.919 * GC %), R = 0.998. The deviation from GC calculated as (100*(IR-GC)/GC), in %) ranged from -11 to 11% for the medium and higher concentrations, and from -20 to +20% for the lowest concentrations. No carrier gas effect could be detected. Individual modules differed in their accuracy (p = 0.004), with differences between analyzers mounting up to 12% of the medium and highest concentrations and up to 25% of the lowest agent concentrations. CONCLUSION: M-CAiOV compact gas IR analyzers are well compensated for carrier gas cross-sensitivity and are linear over the range of concentrations studied. IR and GC cannot be used interchangeably, because the deviations between GC and IR mount up to ± 20%, and because individual analyzers differ unpredictably in their performance.