A novel, cassette-based nitric oxide delivery system with an advanced feedback control algorithm accurately delivers nitric oxide via the anesthesia machine independent of fresh gas flow rate and volatile anesthetic agent.

Nitric oxide (NO), a selective pulmonary vasodilator, can be delivered via conventional ICU and anesthesia machine ventilators. Anesthesia machines are designed for rebreathing of circulating gases, reducing volatile anesthetic agent quantity used. Current cylinder- and ionizing-based NO delivery technologies use breathing circuit flow to determine NO delivery and do not account for recirculated gases; therefore, they cannot accurately dose NO at FGF below patient minute ventilation (MV). A novel, cassette-based NO delivery system (GENOSYL® DS, Vero Biotech Inc.) uses measured NO concentration in the breathing circuit as an input to an advanced feedback control algorithm, providing accurate NO delivery regardless of FGF and recirculation of gases. This study evaluated GENOSYL® DS accuracy with different anesthesia machines, ventilation parameters, FGFs, and volatile anesthetics. GENOSYL® DS was tested with GE Aisys and Dräger Fabius anesthesia machines to determine NO dose accuracy with FGF < patient MV, and with a Getinge Flow-i anesthesia machine to determine NO dose accuracy when delivering various volatile anesthetic agents. Neonatal and adult mechanical ventilation parameters and circuits were used. GENOSYL® DS maintained accurate NO delivery with all three anesthesia machines, at low FGF with recirculation of gases, and with all volatile anesthetic agents at different concentrations. Measured NO2 levels remained acceptable at ≤ 1 ppm with set NO dose ≤ 40 ppm. GENOSYL® DS, with its advanced feedback control algorithm, is the only NO delivery system capable of accurately dosing NO with anesthesia machines with rebreathing ventilation parameters (FGF < MV) regardless of anesthetic agent.

Influence of Remifentanil on the Control Performance of the Bispectral Index Controlled Bayesian-Based Closed-Loop System for Propofol Administration.

BACKGROUND: This study investigated the clinical performance of a model-based, patient-individualized closed-loop (CL) control system for propofol administration using the bispectral index (BIS) as a controlled variable during the induction and maintenance of anesthesia with propofol and remifentanil and studied the influence of the targeted effect-site concentration of remifentanil (CeREMI) on its clinical performance. METHODS: In 163 patients, propofol was administered using a CL system (BIS target [BISTARGET] between 40 and 50). Initial CeREMI targets between 2 and 7.5 ng/mL were selected as deemed clinically required. Performance parameters during induction were the time required to initially cross the target BIS, the time required to reach the maximal drug effect after induction (TPEAK, BIS) and the corresponding BIS at this moment, and the time required to regain the target BIS at the end of induction. Performance during maintenance was defined as the percentage of case time with target BIS ± 10 from target and the amount of performance error (PE) between the observed and target BIS values and its derived median PE (MDPE) as a measure of control bias, median absolute PE (MDAPE) as a measure of control inaccuracy, divergence as a measure of the time-related trend of the measured BIS values relative to the target BIS values, and wobble as a measure of intrasubject variability in prediction error. The secondary end point was the hemodynamic stability of the patient during CL control. RESULTS: The applied CL system induced and maintained anesthesia within clinically accepted ranges. The percentage of case time [mean (standard deviation [SD]) across all study participants] with BIS ± 10 from the target was 82% (14%). The mean (SD) population MDPE and MDAPE were -6.6% (5.5%) and 11.2% (5.5%), respectively. A negative divergence [-0.001 (0.004)] and acceptable wobble [9.7% (4.0%)] were found. The correlation between the system PE and CeREMI was low and only influenced by a CeREMI <2.8 ng/mL. Hemodynamic stability stayed within the clinically acceptable range. CONCLUSIONS: The applied CL system for propofol administration has an acceptable performance in the CeREMI range of 2.8-7.5 ng/mL during the induction and maintenance of anesthesia. There was no evidence of a strong association between CeREM and the CL performance. This study also shows that when the CeREMI is <2.8 ng/mL, it might be more challenging to prevent arousal during propofol anesthesia.

Estimating the Impact of Carbon Dioxide Absorbent Performance Differences on Absorbent Cost During Low-Flow Anesthesia.

BACKGROUND: Reducing fresh gas flow when using a circle anesthesia circuit is the most effective strategy for reducing both inhaled anesthetic vapor cost and waste. As fresh gas flow is reduced, the amount of exhaled gas rebreathed increases, but the utilization of carbon dioxide absorbent increases as well. Reducing fresh gas flow may not make economic sense if the increased cost of absorbent utilization exceeds the reduced cost of anesthetic vapor. The primary objective of this study was to determine the minimum fresh gas flow at which absorbent costs do not exceed vapor savings. Another objective is to provide a qualitative insight into the factors that influence absorbent performance as fresh gas flow is reduced. METHODS: A mathematical model was developed to compare the vapor savings with the cost of carbon dioxide absorbent as a function of fresh gas flow. Parameters of the model include patient size, unit cost of vapor and carbon dioxide absorbent, and absorbent capacity and efficiency. Boundaries for fresh gas flow were based on oxygen consumption or a closed-circuit condition at the low end and minute ventilation to approximate an open-circuit condition at the high end. Carbon dioxide production was estimated from oxygen consumption assuming a respiratory quotient of 0.8. RESULTS: For desflurane, the cost of carbon dioxide absorbent did not exceed vapor savings until fresh gas flow was almost equal to closed-circuit conditions. For sevoflurane, as fresh gas flow is reduced, absorbent costs increase more slowly than vapor costs decrease so that total costs are still minimized for a closed circuit. Due to the low cost of isoflurane, even with the most effective absorbent, the rate of absorbent costs increase more rapidly than vapor savings as fresh gas flow is reduced, so that an open circuit is least expensive. The total cost of vapor and absorbent is still lowest for isoflurane when compared with the other agents. CONCLUSIONS: The relative costs of anesthetic vapor and carbon dioxide absorbent as fresh gas flow is reduced are dependent on choice of anesthetic vapor and performance of the carbon dioxide absorbent. Absorbent performance is determined by the product selected and strategy for replacement. Clinicians can maximize the performance of absorbents by replacing them based on the appearance of inspired carbon dioxide rather than the indicator. Even though absorbent costs exceed vapor savings as fresh gas flow is reduced, isoflurane is still the lowest cost choice for the environmentally sound practice of closed-circuit anesthesia.

Behavior of a dual closed-loop controller of propofol and remifentanil guided by the bispectral index for postoperative sedation of adult cardiac surgery patients: a preliminary open study.

A dual-loop controller permits the automated titration of propofol and remifentanil during anesthesia; it has never been used in intensive care after cardiac surgery. The goal of this preliminary study was to determine the efficacy of this controller to provide postoperative sedation in 19 adult cardiac surgery patients with a Bispectral Index target of 50. Results are presented as numbers (percentages) or medians [25th-75th percentiles]. The sedation period lasted 139 min [89-205] during which the Richmond Agitation Sedation Scale was at - 5 and the Behavioral Pain Scale score at three points for all patients and observation times but one (82 out of 83 assessments). Sedation time in the range 40-60 for the Bispectral Index was 87% [57-95]; one patient had a period of electrical silence defined as Suppression Ratio at least > 10% for more than 60 s. The time between the end of infusions and tracheal extubation was 84 min [63-129]. The Richmond Agitation Sedation Scale was 0 [0-0], 0 [- 1 to 0], and 0 [0-0] respectively during the 3 h following extubation while the verbal numerical pain scores were 6 [4.5-7], 5 [4-6], and 2 [0-5]. Mean arterial pressure decreased during sedation requiring therapeutic interventions, mainly vascular filling in 15 (79%) patients. Automated sedation device was discontinued in two patients for hemodynamic instability. No patient had awareness of the postoperative sedation period. Dual closed-loop can provide postoperative sedation after cardiac surgery but the choice of the depth of sedation should take into account the risk of hypotension.

Feasibility of Fully Automated Hypnosis, Analgesia, and Fluid Management Using 2 Independent Closed-Loop Systems During Major Vascular Surgery: A Pilot Study.

Automated titration of intravenous anesthesia and analgesia using processed electroencephalography monitoring is no longer a novel concept. Closed-loop control of fluid administration to provide goal-directed fluid therapy has also been increasingly described. However, simultaneously combining 2 independent closed-loop systems together in patients undergoing major vascular surgery has not been previously detailed. The aim of this pilot study was to evaluate the clinical performance of fully automated hypnosis, analgesia, and fluid management using 2 independent closed-loop controllers in patients undergoing major vascular surgery before implementation within a larger study evaluating true patient outcomes.

Perioperative Considerations for Evolving Artificial Pancreas Devices.

Type 1 diabetes mellitus is a lifelong condition. It requires intensive patient involvement including frequent glucose measurements and subcutaneous insulin dosing to provide optimal glycemic control to decrease short- and long-term complications of diabetes mellitus without causing hypoglycemia. Variations in insulin pharmacokinetics and responsiveness over time in addition to illness, stress, and a myriad of other factors make ideal glucose control a challenge. Control-to-range and control-to-target artificial pancreas devices (closed-loop artificial pancreas devices [C-APDs]) consist of a continuous glucose monitor, response algorithm, and insulin delivery device that work together to automate much of the glycemic management for an individual while continually adjusting insulin dosing toward a glycemic target. In this way, a C-APD can improve glycemic control and decrease the rate of hypoglycemia. The MiniMed 670G (Medtronic, Fridley, MN) system is currently the only Food and Drug Administration-cleared C-APD in the United States. In this system, insulin delivery is continually adjusted to a glucose concentration, and the patient inputs meal-time information to modify insulin delivery as needed. Data thus far suggest improved glycemic control and decreased hypoglycemic events using the system, with decreased need for patient self-management. Thus, the anticipated use of these devices is likely to increase dramatically over time. There are limited case reports of safe intraoperative use of C-APDs, but the Food and Drug Administration has not cleared any device for such use. Nonetheless, C-APDs may offer an opportunity to improve patient safety and outcomes through enhanced intraoperative glycemic control. Anesthesiologists should become familiar with C-APD technology to help develop safe and effective protocols for their intraoperative use. We provide an overview of C-APDs and propose an introductory strategy for intraoperative study of these devices.

Regulatory Considerations for Physiological Closed-Loop Controlled Medical Devices Used for Automated Critical Care: Food and Drug Administration Workshop Discussion Topics.

Part of the mission of the Center for Devices and Radiological Health (CDRH) at the US Food and Drug Administration is to facilitate medical device innovation. Therefore, CDRH plays an important role in helping its stakeholders such as manufacturers, health care professionals, patients, patient advocates, academia, and other government agencies navigate the regulatory landscape for medical devices. This is particularly important for innovative physiological closed-loop controlled (PCLC) devices used in critical care environments, such as intensive care units, emergency settings, and battlefield environments. CDRH's current working definition of a PCLC medical device is a medical device that incorporates physiological sensor(s) for automatic manipulation of a physiological variable through actuation of therapy that is conventionally made by a clinician. These emerging devices enable automatic therapy delivery and may have the potential to revolutionize the standard of care by ensuring adequate and timely therapy delivery with improved performance in high workload and high-stress environments. For emergency response and military applications, automatic PCLC devices may play an important role in reducing cognitive overload, minimizing human error, and enhancing medical care during surge scenarios (ie, events that exceed the capability of the normal medical infrastructure). CDRH held an open public workshop on October 13 and 14, 2015 with the aim of fostering an open discussion on design, implementation, and evaluation considerations associated with PCLC devices used in critical care environments. CDRH is currently developing regulatory recommendations and guidelines that will facilitate innovation for PCLC devices. This article highlights the contents of the white paper that was central to the workshop and focuses on the ensuing discussions regarding the engineering, clinical, and human factors considerations.

Pressure-flow characteristics of breathing systems and their components for pediatric and adult patients.

BACKGROUND: Breathing circuits connect the ventilator to the patients' respiratory system. Breathing tubes, connectors, and sensors contribute to artificial airway resistance to a varying extent. We hypothesized that the flow-dependent resistance is higher in pediatric breathing systems and their components compared to respective types for adults. AIMS: We aimed to characterize the resistance of representative breathing systems and their components used in pediatric patients (including devices for adults) by their nonlinear pressure-flow relationship. METHODS: We used a physical model to measure the flow-dependent pressure gradient (∆P) across breathing tubes, breathing tube extensions, 90°- and Y-connectors, flow- and carbon dioxide sensors, water traps and reusable, disposable and coaxial breathing systems for pediatric and for adult patients. ∆P was analyzed for usual flow ranges and statistically compared at a representative flow rate of 300 mL∙s-1 (∆P300 ). RESULTS: ∆P across pediatric devices always exceeded ∆P across the corresponding devices for adult patients (all P < .001 [no 95% CI includes 0]). ∆P300 across breathing system components for adults was always below 0.2 cmH2 O but reached up to 4.6 cmH2 O in a flow sensor for pediatric patients. ∆P300 was considerably higher across the reusable compared to the disposable pediatric breathing systems (1.9 vs 0.3 cmH2 O, P < .001, [95% CI -1.59 to -1.56]). CONCLUSION: The resistances of pediatric breathing systems and their components result in pressure gradients exceeding those for adults several fold. Considering the resistance of individual components is crucial for composing a breathing system matching the patient's needs. Compensation of the additional resistance should be considered if a large composed resistance is unavoidable.

Closed-loop regulation of arterial pressure after acute brain death.

The purpose of this concept study was to investigate the possibility of automatic mean arterial pressure (MAP) regulation in a porcine heart-beating brain death (BD) model. Hemodynamic stability of BD donors is necessary for maintaining acceptable quality of donated organs for transplantation. Manual stabilization is challenging, due to the lack of vasomotor function in BD donors. Closed-loop stabilization therefore has the potential of increasing availability of acceptable donor organs, and serves to indicate feasibility within less demanding patient groups. A dynamic model of nitroglycerine pharmacology, suitable for controller synthesis, was identified from an experiment involving an anesthetized pig, using a gradient-based output error method. The model was used to synthesize a robust PID controller for hypertension prevention, evaluated in a second experiment, on a second, brain dead, pig. Hypotension was simultaneously prevented using closed-loop controlled infusion of noradrenaline, by means of a previously published controller. A linear model of low order, with variable (uncertain) gain, was sufficient to describe the dynamics to be controlled. The robustly tuned PID controller utilized in the second experiment kept the MAP within a user-defined range. The system was able to prevent hypertension, exceeding a reference of 100 mmHg by more than 10%, during 98% of a 12 h experiment. This early work demonstrates feasibility of the investigated modelling and control synthesis approach, for the purpose of maintaining normotension in a porcine BD model. There remains a need to characterize individual variability, in order to ensure robust performance over the expected population.

Physician-Directed Versus Computerized Closed-Loop Control of Blood Pressure Using Phenylephrine in a Swine Model.

BACKGROUND: Vasopressors provide a rapid and effective approach to correct hypotension in the perioperative setting. Our group developed a closed-loop control (CLC) system that titrates phenylephrine (PHP) based on the mean arterial pressure (MAP) during general anesthesia. As a means of evaluating system competence, we compared the performance of the automated CLC with physicians. We hypothesized that our CLC algorithm more effectively maintains blood pressure at a specified target with less blood pressure variability and reduces the dose of PHP required. METHODS: In a crossover study design, 6 swine under general anesthesia were subjected to a normovolemic hypotensive challenge induced by sodium nitroprusside. The physicians (MD) manually changed the PHP infusion rate, and the CLC system performed this task autonomously, adjusted every 3 seconds to achieve a predetermined MAP. RESULTS: The CLC maintained MAP within 5 mm Hg of the target for (mean ± standard deviation) 93.5% ± 3.9% of the time versus 72.4% ± 26.8% for the MD treatment (P = .054). The mean (standard deviation) percentage of time that the CLC and MD interventions were above target range was 2.1% ± 3.3% and 25.8% ± 27.4% (P = .06), respectively. Control statistics, performance error, median performance error, and median absolute performance error were not different between CLC and MD interventions. PHP infusion rate adjustments by the physician were performed 12 to 80 times in individual studies over a 60-minute period. The total dose of PHP used was not different between the 2 interventions. CONCLUSIONS: The CLC system performed as well as an anesthesiologist totally focused on MAP control by infusing PHP. Computerized CLC infusion of PHP provided tight blood pressure control under conditions of experimental vasodilation.

Effects of different fresh gas flows with or without a heat and moisture exchanger on inhaled gas humidity in adults undergoing general anaesthesia: A systematic review and meta-analysis of randomised controlled trials.

BACKGROUND: The minimum inhaled gas absolute humidity level is 20 mgH2O l for short-duration use in general anaesthesia and 30 mgH2O l for long-duration use in intensive care to avoid respiratory tract dehydration. OBJECTIVE: The aim is to compare the effects of different fresh gas flows (FGFs) through a circle rebreathing system with or without a heat and moisture exchanger (HME) on inhaled gas absolute humidity in adults undergoing general anaesthesia. DESIGN: Systematic review and meta-analyses of randomised controlled trials. We defined FGF (l min) as minimal (0.25 to 0.5), low (0.6 to 1.0) or high (≥2). We extracted the inhaled gas absolute humidity data at 60 and 120 min after connection of the patient to the breathing circuit. The effect size is expressed as the mean differences and corresponding 95% confidence intervals (CI). DATA SOURCES: PubMed, EMBASE, SciELO, LILACS and CENTRAL until January 2017. RESULTS: We included 10 studies. The inhaled gas absolute humidity was higher with minimal flow compared with low flow at 120 min [mean differences 2.51 (95%CI: 0.32 to 4.70); P = 0.02] but not at 60 min [mean differences 2.95 (95%CI: -0.95 to 6.84); P = 0.14], and higher with low flow compared with high flow at 120 min [mean differences 7.19 (95%CI: 4.53 to 9.86); P < 0.001]. An inhaled gas absolute humidity minimum of 20 mgH2O l was attained with minimal flow at all times but not with low or high flows. An HME increased the inhaled gas absolute humidity: with minimal flow at 120 min [mean differences 8.49 (95%CI: 1.15 to 15.84); P = 0.02]; with low flow at 60 min [mean differences 9.87 (95%CI: 3.18 to 16.57); P = 0.04] and 120 min [mean differences 7.19 (95%CI: 3.29 to 11.10); P = 0.003]; and with high flow of 2 l min at 60 min [mean differences 6.46 (95%CI: 4.05 to 8.86); P < 0.001] and of 3 l min at 120 min [mean differences 12.18 (95%CI: 6.89 to 17.47); P < 0.001]. The inhaled gas absolute humidity data attained or were near 30 mgH2O l when an HME was used at all FGFs and times. CONCLUSION: All intubated patients should receive a HME with low or high flows. With minimal flow, a HME adds cost and is not needed to achieve an appropriate inhaled gas absolute humidity.

The Feasibility of a Completely Automated Total IV Anesthesia Drug Delivery System for Cardiac Surgery.

BACKGROUND: In this pilot study, we tested a novel automatic anesthesia system for closed-loop administration of IV anesthesia drugs for cardiac surgical procedures with cardiopulmonary bypass. This anesthesia drug delivery robot integrates all 3 components of general anesthesia: hypnosis, analgesia, and muscle relaxation. METHODS: Twenty patients scheduled for elective cardiac surgery with cardiopulmonary bypass were enrolled. Propofol, remifentanil, and rocuronium were administered using closed-loop feedback control. The main objective was the feasibility of closed-loop anesthesia defined as successful automated cardiac anesthesia without manual override by the attending anesthesiologist. Secondary qualitative observations were clinical and controller performances. The clinical performance of hypnosis control was the efficacy to maintain a bispectral index (BIS) of 45. To evaluate the hypnosis performance, BIS values were stratified into 4 categories: "excellent," "good," "poor," and "inadequate" hypnosis control defined as BIS values within 10%, ranging from 11% to 20%, ranging from 21% to 30%, or >30% of the target value, respectively. The clinical performance of analgesia was the efficacy to maintain NociMap values close to 0. The analgesia performance was assessed classifying the NociMap values in 3 pain control groups: -33 to +33 representing excellent pain control, -34 to -66 and +34 to +66 representing good pain control, and -67 to -100 and +67 to +100 representing insufficient pain control. The controller performance was calculated using the Varvel parameters. RESULTS: Robotic anesthesia was successful in 16 patients, which is equivalent to 80% (97.5% confidence interval [CI], 53%-95%) of the patients undergoing cardiac surgery. Four patients were excluded from the final analysis because of technical problems with the automated anesthesia delivery system. The secondary qualitative observations revealed that the clinical performance of hypnosis allowed an excellent and good control during 70% (97.5% CI, 63%-76%) of maintenance time and an insufficient clinical performance of analgesia for only 3% (97.5% CI, 1%-6%) of maintenance time. CONCLUSIONS: The completely automated closed-loop system tested in this investigation could be used successfully and safely for cardiac surgery necessitating cardiopulmonary bypass. The results of the present trial showed satisfactory clinical performance of anesthesia control.

Inhaled anaesthetics and nitrous oxide: Complexities overlooked: things may not be what they seem.

This review re-examines existing pharmacokinetic and pharmacodynamic concepts of inhaled anaesthetics. After showing where uptake is hidden in the classic FA/FI curve, it is argued that target-controlled delivery of inhaled agents warrants a different interpretation of the factors affecting this curve (cardiac output, ventilation and blood/gas partition coefficient). Blood/gas partition coefficients of modern agents may be less important clinically than generally assumed. The partial pressure cascade from delivered to inspired to end-expired is re-examined to better understand the effect of rebreathing during low-flow anaesthesia, including the possibility of developing a hypoxic inspired mixture despite existing machine standards. Inhaled agents are easy to administer because they are transferred according to partial pressure gradients. In addition, the narrow dose-response curves for the three end points of general anaesthesia (loss of response to verbal command, immobility and autonomic reflex control) allow the clinical use of MACawake, MAC and MACBAR to determine depth of anaesthesia. Opioids differentially affect these clinical effects of inhaled agents. The effect of ventilation-perfusion relationships on gas uptake is discussed, and it is shown how moving beyond Riley's useful but simplistic model allows us to better understand both the concept and the magnitude of the second gas effect of nitrous oxide. It is argued that nitrous oxide remains a clinically useful drug. We hope to bring old (but ignored) and new (but potentially overlooked) information into the educational and clinical arenas to stimulate discussion among clinicians and researchers. We should not let technology pass by our all too engrained older concepts.

Accuracy of inhaled agent usage displays of automated target control anesthesia machines.

Automated low flow anesthesia machines report how much inhaled anesthetic agent has been used for each anesthetic. We compared these reported values with the amount of agent that had disappeared by weighing the vaporizer/injectors before and after each anesthetic. The vaporizers/injectors of the Aisys, Zeus and FLOW-i were weighed with a high precision weighing scale before and after anesthesia with either desflurane in O2/air or sevoflurane in O2/N2O. These values were compared with the values reported by the cumulative agent use display tools of the respective anesthesia machines using a linear curve fit. Twenty-five measurements were performed in each group, except for the sevoflurane data with the Aisys that were available from another study (87 pairs). We also determined the amount lost by inserting and removing the vaporizers/injectors or by performing a machine checkout, corrected the measured amounts for these artifacts and repeated the linear fits. The average amount of sevoflurane and desflurane wasted by inserting and removing the cassette for the Aisys, Zeus, and FLOW-i were 0.21, 0.12, and 0.04 mL and 0.12, 0.61, and 1.13 mL liquid agent, respectively. The average amount of sevoflurane and desflurane wasted by the machine checkout with the Aisys, Zeus, and FLOW-i were 1.78, 0.21, and 1.67 mL and 2.39, 0.67, and 4.19 mL, respectively. Performance error of the displayed amount of agent use remained within 10 % of the weighed amount, expect for amounts less than 3 mL sevofurane with the FLOW-i and less than 20 mL desflurane with the Aisys and FLOW-i. Cumulative agent usage displayed by the Aisys, Zeus, and FLOW-i is within 10 % of the measured consumption, except for low consumption cases (<3 mL sevoflurane, <20 mL desflurane). The differences may be due to either measurement error or cumulative agent display error. The current results can help the researchers decide whether the displayed amounts are accurate enough for their study purposes. The extent to which these discrepancies differ between different units of the same machine remains unstudied.

Hypoxic guard systems do not prevent rapid hypoxic inspired mixture formation.

Because a case report and theoretical mass balances suggested that hypoxic guard systems may not prevent the formation of hypoxic inspired mixtures (FIO2 ≤ 21 %) over the clinically used fresh gas flow (FGF) range, we measured FIO2 over a wide range of hypoxic guard limits for O2/N2O and O2/air mixtures. After IRB approval, 16 ASA I-II patients received sevoflurane in either O2/N2O (n = 8) or O2/air (n = 8) using a Zeus(®) anesthesia machine in the conventional mode. After using an 8 L/min FGF with FDO2 = 25% for 10 min, the following hypoxic guard limits were tested for 4 min each, expressed as [total FGF in L/min; FDO2 in %]: [0.3;85], [0.4;65], [0.5;50], [0.7;36], [0.85;30], [1.0;25], [1.25;25], [1.5;25], [2;25], [3;25], [5;25], and [8;25]. In between these [FGF;FDO2] combinations, 8 L/min FGF with 25% O2 was used for 4 min to return to the same baseline FIO2 (25%) before the start of the next combination. This sequence was studied once in each patient receiving O2/air (n = 8), but twice in each patient who received O2/N2O (n = 8) to examine the effect of decreasing N2O uptake over time, resulting in three groups: early O2/N2O, late O2/N2O, and O2/air group. The [FGF;FDO2]-FIO2 relationship was examined. The overall [FGF;FDO2]-FIO2 relationship in the three groups was similar. In all 1, 1.25, and 1.5 L/min FGF groups, FIO2 decreased below 21% in all but one patient; this occurred within 1 min in at least one patient. In the 0.7 L/min O2/air group and the 3 L/min late O2/N2O and O2/air groups, FIO2 decreased below 21% in one patient. Current hypoxic guard systems do not reliably prevent a hypoxic FIO2 with O2/N2O and O2/air mixtures, particularly between 0.7 and 3 L/min.

The humidity in a Dräger Primus anesthesia workstation using low or high fresh gas flow and with or without a heat and moisture exchanger in pediatric patients.

BACKGROUND: An inhaled gas absolute humidity of 20 mg H2O·L is the value most considered as the threshold necessary for preventing the deleterious effects of dry gas on the epithelium of the airways during anesthesia. Because children have small minute ventilation, we hypothesized that the humidification of a circle breathing system is lower in children compared with adults. The Primus anesthesia workstation (Dräger Medical, Lübeck, Germany) has a built-in hotplate to heat the patient's exhaled gases. A heat and moisture exchanger (HME) is a device that can be used to further humidify and heat the inhaled gases during anesthesia. To evaluate the humidifying properties of this circle breathing system during pediatric anesthesia, we compared the temperature and humidity of inhaled gases under low or high fresh gas flow (FGF) conditions and with or without an HME. METHODS: Forty children were randomly allocated into 4 groups according to the ventilation of their lungs by a circle breathing system in a Dräger Primus anesthesia workstation with low (1 L·min) or high (3 L·min) FGF without an HME (1L and 3L groups) or with an HME (Pall BB25FS, Pall Biomedical, East Hills, NY; HME1L and HME3L groups). The temperature and absolute humidity of inhaled gases were measured at 10, 20, 40, 60, and 80 minutes after connecting the patient to the breathing circuit. RESULTS: The mean inhaled gas temperature was higher in HME groups (HME1L: 30.3°C ± 1.1°C; HME3L: 29.3°C ± 1.2°C) compared with no-HME groups (1L: 27.0°C ± 1.2°C; 3L: 27.1°C ± 1.5°C; P < 0.0001). The mean inhaled gas absolute humidity was higher in HME than no-HME groups and higher in low-flow than high-flow groups ([HME1L: 25 ± 1 mg H2O·L] > [HME3L: 23 ± 2 mg H2O·L] > [1L: 17 ± 1 mg H2O·L] > [3L: 14 ± 1 mg H2O·L]; P < 0.0001). CONCLUSIONS: In a pediatric circle breathing system, the use of neither high nor low FGF provides the minimum humidity level of the inhaled gases thought to reduce the risk of dehydration of airways. Insertion of an HME increases the humidity and temperature of the inhaled gases, bringing them closer to physiological values. The use of a low FGF enhances the HME efficiency and consequently increases the inhaled gas humidity values. Therefore, the association of an HME with low FGF in the breathing circuit is the most efficient way to conserve the heat and the moisture of the inhaled gas during pediatric anesthesia.

Feedback control for clinicians.

Although feedback control and automation has revolutionized many fields of human activity, it has yet to have a significant impact on healthcare, particularly when a patient is in the loop. Although there have been a number of studies concerned with closed-loop control of anesthesia, they have yet to have an impact on clinical practice. For such systems to be successful, engineers and clinicians have to work hand in hand, for this they have to have a basic understanding of each other's fields. The goal of this paper is to introduce clinicians to basic concepts in control engineering, with an emphasis on the properties of feedback control. Concepts such as modelling for control, feedback and uncertainty, robustness, feedback controller such as proportional-integral-derivative control, predictive control and adaptive control are briefly reviewed. Finally we discuss the safety issues around closed-loop control and discuss ways by which safe control can be guaranteed.

An enriched simulation environment for evaluation of closed-loop anesthesia.

To simulate and evaluate the administration of anesthetic agents in the clinical setting, many pharmacology models have been proposed and validated, which play important roles for in silico testing of closed-loop control methods. However, to the authors' best knowledge, there is no anesthesia simulator incorporating closed-loop feedback control of anesthetic agent administration freely available and accessible to the public. Consequently, many necessary but time consuming procedures, such as selecting models from the available literatures and establishing new simulator algorithms, will be repeated by different researchers who intend to explore a novel control algorithm for closed-loop anesthesia. To address this issue, an enriched anesthesia simulator was devised in our laboratory and made freely available to the anesthesia community. This simulator was built by using MATLAB(®) (The MathWorks, Natick, MA). The GUI technology embedded in MATLAB was chosen as the tool to develop a human-machine interface. This simulator includes four types of anesthetic models, and all have been wildly used in closed-loop anesthesia studies. For each type of model, 24 virtual patients were created with significant diversity. In addition, the platform also provides a model identification module and a control method library. For the model identification module, the least square method and particle swarm optimization were presented. In the control method library, a proportional-integral-derivative control and a model predictive control were provided. Both the model identification module and the control method library are extensive and readily accessible for users to add user-defined functions. This simulator could be a benchmark-testing platform for closed-loop control of anesthesia, which is of great value and has significant development potential. For convenience, this simulator is termed as Wang's Simulator, which can be downloaded from http://www.AutomMed.org .

Automated titration of propofol and remifentanil decreases the anesthesiologist's workload during vascular or thoracic surgery: a randomized prospective study.

Closed loop target-control infusion systems using a Bispectral (BIS) signal as an input (TCI Loop) can automatically maintain intravenous anesthesia in a BIS range of 40-60 %. Our purpose was to assess to what extent such a system could decrease anesthesia workload in comparison to the use of a stand alone TCI system manually adjusted to fit the same BIS range of 40-60 % (TCI Manual). Patients scheduled for elective vascular or thoracic surgery were randomized to the TCI Loop or TCI Manual method for administering propofol and remifentanil during both induction and maintenance of general anesthesia. Assessment of workload was performed by an independent observer who quoted each time the physician looked at the BIS monitor. The number of propofol and remifentanil target modifications, the percentage of time of adequate anesthesia i.e. BIS in the range 40-60 and hemodynamic data were recorded. Eighteen patients per group were enrolled. Characteristics, duration of surgery and propofol-remifentanil consumption were similar between groups. However, the percentage of time in the BIS range 40-60 % was higher in the TCI Loop versus TCI Manual groups (94 % ± 12 vs. 74 % ± 19, p < 0.001). Mean arterial pressure was lower with TCI Manual (78 ± 6 vs. 88 ± 13 mmHg, p < 0.001). The number of times the anesthesiologist watched the controller or BIS monitor (p < 0.05) and the number of manual adjustments (p < 0.001) performed in each group was lower with TCI Loop group during induction and maintenance of anesthesia. An automated controller strikingly frees the anesthesiologist from manual intervention to adjust drug delivery.