Event-based MPC for propofol administration in anesthesia.

BACKGROUND AND OBJECTIVE: The automatic control of anesthesia is a demanding task mostly due to the presence of nonlinearities, intra- and inter-patient variability and specific clinical requirements to be meet. The traditional approach to achieve the desired depth of hypnosis level is based on knowledge and experience of the anesthesiologist. In contrast to a typical automatic control system, their actions are based on events that are related to the effect of the administrated drug. Thus, it is interesting to build a control system that will be able to mimic the behavior of the human way of actuation, simultaneously keeping the advantages of an automatic system. METHODS: In this work, an event-based model predictive control system is proposed and analyzed. The nonlinear patient model is used to form the predictor structure and its linear part is exploited to design the predictive controller, resulting in an individualized approach. In such a scenario, the BIS is the controlled variable and the propofol infusion rate is the control variable. The event generator governs the computation of control action applying a dead-band sampling technique. The proposed control architecture has been tested in simulation considering process noise and unmeasurable disturbances. The evaluation has been made for a set of patients using nonlinear pharmacokinetic/pharmacodynamic models allowing realistic tests scenarios, including inter- and intra-patient variability. Results For the considered patients dataset the number of control signal changes has been reduced of about 55% when compared to the classical control system approach and the drug usage has been reduced of about 2%. At the same time the control performance expressed by the integrated absolute error has been degraded of about 11%. CONCLUSIONS: The event-based MPC control system meets all the clinical requirements. The robustness analysis also demonstrates that the event-based architecture is able to satisfy the specifications in the presence of significant process noise and modelling errors related to inter- and intra-patient variability, providing a balanced solution between complexity and performance.

A modified PID-based control scheme for depth-of-hypnosis control: Design and experimental results.

BACKGROUND AND OBJECTIVE: Many methodologies have been proposed for the control of total intravenous anesthesia in general surgery, as this yields a reduced stress for the anesthesiologist and an increased safety for the patient. The objective of this work is to design a PID-based control system for the regulation of the depth of hypnosis by propofol and remifentanil coadministration that takes into account the clinical practice. METHODS: With respect to a standard PID control system, additional functionalities have been implemented in order to consider specific requirements related to the clinical practice. In particular, suitable boluses are determined and used in the induction phase and a nonzero baseline infusion is used in the maintenance phase when the predicted effect-site concentration drops below a safety threshold. RESULTS: The modified controller has been experimentally assessed on a group of 10 patients receiving general anesthesia for elective plastic surgery. The control system has been able to induce and maintain adequate anesthesia without any manual intervention from the anesthesiologist. CONCLUSIONS: Results confirm the effectiveness of the overall design approach and, in particular, highlight that the new version of the control system, with respect to a standard PID controller, provides significant advantages from a clinical standpoint.

Event-Based control of depth of hypnosis in anesthesia.

BACKGROUND AND OBJECTIVE: In this paper, we propose the use of an event-based control strategy for the closed-loop control of the depth of hypnosis in anesthesia by using propofol administration and the bispectral index as a controlled variable. METHODS: A new event generator with high noise-filtering properties is employed in addition to a PIDPlus controller. The tuning of the parameters is performed off-line by using genetic algorithms by considering a given data set of patients. RESULTS: The effectiveness and robustness of the method is verified in simulation by implementing a Monte Carlo method to address the intra-patient and inter-patient variability. A comparison with a standard PID control structure shows that the event-based control system achieves a reduction of the total variation of the manipulated variable of 93% in the induction phase and of 95% in the maintenance phase. CONCLUSIONS: The use of event based automatic control in anesthesia yields a fast induction phase with bounded overshoot and an acceptable disturbance rejection. A comparison with a standard PID control structure shows that the technique effectively mimics the behavior of the anesthesiologist by providing a significant decrement of the total variation of the manipulated variable.

Optimized PID control of depth of hypnosis in anesthesia.

BACKGROUND AND OBJECTIVE: This paper addresses the use of proportional-integral-derivative controllers for regulating the depth of hypnosis in anesthesia by using propofol administration and the bispectral index as a controlled variable. In fact, introducing an automatic control system might provide significant benefits for the patient in reducing the risk for under- and over-dosing. METHODS: In this study, the controller parameters are obtained through genetic algorithms by solving a min-max optimization problem. A set of 12 patient models representative of a large population variance is used to test controller robustness. The worst-case performance in the considered population is minimized considering two different scenarios: the induction case and the maintenance case. RESULTS: Our results indicate that including a gain scheduling strategy enables optimal performance for induction and maintenance phases, separately. Using a single tuning to address both tasks may results in a loss of performance up to 102% in the induction phase and up to 31% in the maintenance phase. Further on, it is shown that a suitably designed low-pass filter on the controller output can handle the trade-off between the performance and the noise effect in the control variable. CONCLUSIONS: Optimally tuned PID controllers provide a fast induction time with an acceptable overshoot and a satisfactory disturbance rejection performance during maintenance. These features make them a very good tool for comparison when other control algorithms are developed.

Randomized Evidence for Reduction of Perioperative Mortality: An Updated Consensus Process.

OBJECTIVE: Of the 230 million patients undergoing major surgical procedures every year, more than 1 million will die within 30 days. Thus, any nonsurgical interventions that help reduce perioperative mortality might save thousands of lives. The authors have updated a previous consensus process to identify all the nonsurgical interventions, supported by randomized evidence, that may help reduce perioperative mortality. DESIGN AND SETTING: A web-based international consensus conference. PARTICIPANTS: The study comprised 500 clinicians from 61 countries. INTERVENTIONS: A systematic literature search was performed to identify published literature about nonsurgical interventions, supported by randomized evidence, showing a statistically significant impact on mortality. A consensus conference of experts discussed eligible papers. The interventions identified by the conference then were submitted to colleagues worldwide through a web-based survey. MEASUREMENTS AND MAIN RESULTS: The authors identified 11 interventions contributing to increased survival (perioperative hemodynamic optimization, neuraxial anesthesia, noninvasive ventilation, tranexamic acid, selective decontamination of the gastrointestinal tract, insulin for tight glycemic control, preoperative intra-aortic balloon pump, leuko-depleted red blood cells transfusion, levosimendan, volatile agents, and remote ischemic preconditioning) and 2 interventions showing increased mortality (beta-blocker therapy and aprotinin). Interventions then were voted on by participating clinicians. Percentages of agreement among clinicians in different countries differed significantly for 6 interventions, and a variable gap between evidence and clinical practice was noted. CONCLUSIONS: The authors identified 13 nonsurgical interventions that may decrease or increase perioperative mortality, with variable agreement by clinicians. Such interventions may be optimal candidates for investigation in high-quality trials and discussion in international guidelines to reduce perioperative mortality.

Randomized evidence for reduction of perioperative mortality: an updated consensus process

Objective: Out of the 230 million patients undergoing major surgical procedure every year, morethan 1 million will die within 30 days. Thus, any nonsurgical interventions that help reduce perioperative mortality might save thousands of lives. We decided to update a previous consensus process to identify all the nonsurgical interventions, supported by randomized evidence, that may help reduce perioperative mortality. Design and Setting: A web-based international consensus conference. Participants: 500 hundred clinicians from 61 countries. Interventions: A systematic literature search was performed to identify published literature aboutnonsurgical interventions, supported by randomized evidence showing a statistically significant impact on mortality. Eligible papers were discussed by a Consensus Conference of experts. The interventions identified by the conference were then submitted to colleagues worldwide through aweb-based survey...