E REVIEW ARTICLE
Closed-Loop Control of Anesthesia: A Primer for Anesthesiologists Guy A. Dumont, PhD, PEng*† and J. Mark Ansermino, MBBCh, MSc (Inf), FFA (SA), FRCPC† Feedback control is ubiquitous in nature and engineering and has revolutionized safety in fields from space travel to the automobile. In anesthesia, automated feedback control holds the promise of limiting the effects on performance of individual patient variability, optimizing the workload of the anesthesiologist, increasing the time spent in a more desirable clinical state, and ultimately improving the safety and quality of anesthesia care. The benefits of control systems will not be realized without widespread support from the health care team in close collaboration with industrial partners. In this review, we provide an introduction to the established field of control systems research for the everyday anesthesiologist. We introduce important concepts such as feedback and modeling specific to control problems and provide insight into design requirements for guaranteeing the safety and performance of feedback control systems. We focus our discussion on the optimization of anesthetic drug administration. (Anesth Analg 2013;XX:00–00)
W
hy would one want to use a closed-loop controller for drug administration? Control and feedback play a crucial role in both the natural and engineered world. Despite the prevalence of control systems, we are often unaware of their presence. In the engineered world, control is omnipresent and although rarely visible it is a critical enabling technology.1 For example, mobile telephony would not be possible without sophisticated schemes for power control, automatic frequency control, and automatic gain control. Modern cars have dozens of sophisticated control loops, from braking control, steering control, to powertrain control. Indeed if it were not for control, cars would not be able to meet today’s stringent emission control requirements. Control is also a key technology for the development of the smart grid required to supply electricity efficiently to our homes today and in the future. Homeostasis is the physiologic closed-loop control, which is present in every system in every living organism. In nature, from the complex ecology of the planet to the single cell, feedback and control are essential to maintain life.2,3 Even today the anesthesiologist is constantly engaged in control and feedback. Actions, such as adjusting drug or fluid administration, are based on some observation of the clinical environment or monitoring devices. This control can extend to hypnosis, analgesia (antinociception), neuromuscular blockade, temperature, metabolic status, ventilation, and hemodynamic homeostasis (Fig. 1).4 Due to the complexity and performance pressure of the clinical environment and the large degree of individual
From the Departments of *Electrical & Computer Engineering and †Anesthesiology, Pharmacology & Therapeutics, University of British Columbia; and ‡Department of Anesthesia, BC Children’s Hospital, Vancouver, British Columbia, Canada. Accepted for publication April 03, 2013. Funding: Not funded. Conflicts of Interest: See Disclosures at the end of the article. Reprints will not be available from the authors. Address correspondence to Guy A. Dumont, PhD, PEng, Department of Electrical Engineering, 2332 Main Mall, Vancouver, British Columbia V6T 1Z4, Canada. Address e-mail to
[email protected]. Copyright © 2013 International Anesthesia Research Society DOI: 10.1213/ANE.0b013e3182973687
patient variability, the performance of the anesthesiologist controller is suboptimal. In addition, there is increasing evidence that intraoperative performance by the anesthesiologist controller may influence longer-term outcomes. Intraoperative normothermia5 and protocol-driven fluid optimization6 have been shown to reduce postoperative mortality. Occurrences of low mean arterial blood pressure (MAP) and deep hypnotic levels may be associated with postoperative mortality.7–9 A cumulative time with Bispectral Index (BIS) (an electroencephalographic [EEG] based index of hypnotic effect) 15 minutes at a “triple low” of low MAP, low DOH (BIS), and low minimum alveolar concentration of volatile anesthesia may be associated with an extended hospital stay and increased mortality at 30 days. In addition, if the recent reports of a reduction in postoperative delirium and cognitive decline with anesthesia guided by processed EEG68,69 can be confirmed, significant outcome advantages could be realized by automation of drug delivery.
Finally, the question of intellectual property surrounding closed-loop control of anesthesia has to be resolved to attract potential investors. The concept of feedback itself is not patentable, and most control algorithms for anesthesia that have been published are based on known methodologies. What are more likely to be patentable are methods for tuning, ensuring safety, or the use of a particular sensor in the loop as preferred embodiment of the invention. Also, the process control industry tends to rely on protecting their solutions with undisclosed know-how and trade secrets, and control vendors may publish their basic control methodology to establish technical credibility.
CONCLUSIONS
The introduction of automation promises to reduce the variability and increase the safety of many processes in anesthesia, including automated anesthetic drug delivery. The ubiquitous real gains in performance promised by adoption of feedback control can be realized in anesthesia but will necessitate a strong engineering approach to the design, analysis, validation, and verification of closed-loop systems. Given that these elements are secured, and if major suppliers of anesthesia equipment are engaged in participating in the development and testing of such a system, we may in a few years see widespread use of closed-loop control of anesthesia and analgesia in daily clinical practice. E DISCLOSURES
Name: Guy A. Dumont, PhD, PEng. Contribution: Guy A. Dumont helped prepare this manuscript. Attestation: Guy A. Dumont approved the final manuscript. Conflicts of Interest: Guy A. Dumont is co-inventor of the NeuroSENSE monitor (NeuroWave Systems Inc., Cleveland, OH) and has consulted for NeuroWave Systems Inc. He has also consulted for GE Healthcare. Name: J. Mark Ansermino, MBBCh, MSc (Inf), FFA (SA), FRCPC. Contribution: J. Mark Ansermino helped prepare this manuscript. Attestation: J. Mark Ansermino approved the final manuscript. Conflicts of Interest: J. Mark Ansermino has consulted for GE Healthcare. This manuscript was handled by: Dwayne R. Westenskow, PhD. REFERENCES 1. Samad T, Annasamy AM. The impact of control technology. IEEE Control Systems Society 2011. Available at: http://ieeecss. org/main/IoCT-report. Accessed November 15, 2012 2. Khammash M, El-Samad H. Systems biology: from physiology to gene regulation. IEEE Control Systems Magazine 2004;24:62–76 3. Iglesias PA, Khammash M, Munsky B, Sontag ED, Del Vecchio D. Systems biology and control—a tutorial. 46th IEEE Conference on Decision and Control 2007;1–12 4. Rinehart J, Liu N, Alexander B, Cannesson M. Closed-loop systems in anesthesia: is there a potential for closed-loop fluid management and hemodynamic optimization? Anesth Analg 2012;114:130–43 5. Kurz A, Sessler DI, Lenhardt R. Perioperative normothermia to reduce the incidence of surgical-wound infection and shorten hospitalization. Study of Wound Infection and Temperature Group. N Engl J Med 1996;334:1209–15 6. Hamilton MA, Cecconi M, Rhodes A. A systematic review and meta-analysis on the use of preemptive hemodynamic intervention to improve postoperative outcomes in moderate and high-risk surgical patients. Anesth Analg 2011;112:1392–402
XXX 2013 • Volume XX • Number XX www.anesthesia-analgesia.org 7
Copyright © 2013 International Anesthesia Research Society. Unauthorized reproduction of this article is prohibited.
E Review Article 7. Monk TG, Saini V, Weldon BC, Sigl JC. Anesthetic management and one-year mortality after noncardiac surgery. Anesth Analg 2005;100:4–10 8. Sessler DI, Sigl JC, Kelley SD, Chamoun NG, Manberg PJ, Saager L, Kurz A, Greenwald S. Hospital stay and mortality are increased in patients having a “triple low” of low blood pressure, low bispectral index, and low minimum alveolar concentration of volatile anesthesia. Anesthesiology 2012;116:1195–203 9. Watson PL, Shintani AK, Tyson R, Pandharipande PP, Pun BT, Ely EW. Presence of electroencephalogram burst suppression in sedated, critically ill patients is associated with increased mortality. Crit Care Med 2008;36:3171–7 10. Leslie K, Myles PS, Forbes A, Chan MT. The effect of bispectral index monitoring on long-term survival in the B-aware trial. Anesth Analg 2010;110:816–22 11. Lindholm ML, Träff S, Granath F, Greenwald SD, Ekbom A, Lennmarken C, Sandin RH. Mortality within 2 years after surgery in relation to low intraoperative bispectral index values and preexisting malignant disease. Anesth Analg 2009;108:508–12 12. Kertai MD, Pal N, Palanca BJ, Lin N, Searleman SA, Zhang L, Burnside BA, Finkel KJ, Avidan MS; B-Unaware Study Group. Association of perioperative risk factors and cumulative duration of low bispectral index with intermediate-term mortality after cardiac surgery in the B-Unaware Trial. Anesthesiology 2010;112:1116–27 13. Kertai MD, Palanca BJ, Pal N, Burnside BA, Zhang L, Sadiq F, Finkel KJ, Avidan MS; B-Unaware Study Group. Bispectral index monitoring, duration of bispectral index below 45, patient risk factors, and intermediate-term mortality after noncardiac surgery in the B-Unaware Trial. Anesthesiology 2011;114:545–56 14. Cohen NH. Anesthetic depth is not (yet) a predictor of mortality! Anesth Analg 2005;100:1–3 15. Mackey DC. Can we finally conquer the problem of medical quality? The systems-based opportunities of data registries and medical teamwork. Anesthesiology 2012;117:225–6 16. Kheterpal S. Random clinical decisions: identifying variation in perioperative care. Anesthesiology 2012;116:3–5 17. Liu N, Chazot T, Hamada S, Landais A, Boichut N, Dussaussoy C, Trillat B, Beydon L, Samain E, Sessler DI, Fischler M. Closedloop coadministration of propofol and remifentanil guided by bispectral index: a randomized multicenter study. Anesth Analg 2011;112:546–57 18. Albertos P, Mareels I. Feedback and Control for Everyone. Berlin, Germany: Springer Berlin– Heidelberg, 2010 19. Hjalmarsson H. From experiment design to closed-loop control. Automatica 2005;41:393–438 20. Ljung L. System Identification: Theory for the User. 2nd ed. Upper Saddle River, NJ: Prentice Hall, 1999 21. Slotine JJE, Li W. Applied Nonlinear Control. Upper Saddle River, NJ: Prentice Hall, 1990 22. Absalom AR, Struys MMRF. Overview of Target Controlled Infusions and Total Intravenous Anaesthesia. Gent, Belgium: Academia Press, 2007 23. Guzmán JL, Hägglund T, Åström KJ, Dormido S, Berenguel M, Piguet Y. Feedforward Control Concepts Through Interactive Tools. Milano, Italy: 18th IFAC World Congress, 2011:6361–6 24. Mandel JE, Sarraf E. The variability of response to propofol is reduced when a clinical observation is incorporated in the control: a simulation study. Anesth Analg 2012;114:1221–9 25. Black HS. Inventing the negative feedback amplifier. IEEE Spectrum 1977;14:54–60 26. Åström KJ, Murray RM. Feedback Systems: An Introduction for Scientists and Engineers. Princeton, NJ: Princeton University Press, 2008 27. Zhou K, Doyle JC. Essentials of Robust Control. Upper Saddle River, NJ: Prentice Hall, 1997 28. Åström KJ, Hägglund T. Advanced PID Control. Research Triangle Park, NC: The Instrumentation, Systems, and Automation Society, 2006 29. Ang KH, Chong GCY, Li Y. PID control system analysis, design, and technology. IEEE Trans Control Syst Technol 2005;13:559–76
8 www.anesthesia-analgesia.org
30. Maciejowski JM. Predictive Control with Constraints. Upper Saddle River, NJ: Prentice Hall, 2002 31. Ionescu CM, De Keyser R, Torrico BC, De Smet T, Struys MM, Normey-Rico JE. Robust predictive control strategy applied for propofol dosing using BIS as a controlled variable during anesthesia. IEEE Trans Biomed Eng 2008;55:2161–70 32. Mahfouf M, Linkens DA. Generalized Predictive Control and Bioengineering. London, UK: Taylor & Francis, 1998 33. De Smet T, Struys MM, Neckebroek MM, Van den Hauwe K, Bonte S, Mortier EP. The accuracy and clinical feasibility of a new bayesian-based closed-loop control system for propofol administration using the bispectral index as a controlled variable. Anesth Analg 2008;107:1200–10 34. Moore BL, Quasny TM, Doufas AG. Reinforcement learning versus proportional-integral-derivative control of hypnosis in a simulated intraoperative patient. Anesth Analg 2011;112:350–9 35. Lan JY, Abbod MF, Yeh RG, Fan SZ, Shieh JS. Review: intelligent modeling and control in anesthesia. J Med Biol Eng 2012;32:293–308 36. Farmer TG Jr, Edgar TF, Peppas NA. The future of open- and closed-loop insulin delivery systems. J Pharm Pharmacol 2008;60:1–13 37. Aubin JP, Bayen AM, Saint-Pierre P. Viability Theory: New Directions. Berlin, Germany: Springer Berlin–Heidelberg, 2011 38. Tomlin CJ, Lygeros J, Shankar Sastry S. A game theoretic approach to controller design for hybrid systems. Proc IEEE Inst Electr Electron Eng 2000;88:949–70 39. International Electrotechnical Commission. Medical Electrical Equipment, Part 1–10: General Requirements for Basic Safety and Essential Performance—Collateral Standard: Process Requirements for the Development of Physiologic Closed-Loop Controllers. Geneva, Switzerland: IEC, 2007 40. Bickford RG. Automatic electroencephalographic control of general anesthesia. Electroencephalog Clin Neurophysiol 1950;2:93–6 41. Zbinden AM, Frei F, Westenskow DR, Thomson DA. Control of end-tidal halothane concentration. Part B: verification in dogs. Br J Anaesth 1986;58:563–71 42. Brown BH, Perks R, Anthony M, Asbury J, Linkens DA. Closedloop control of muscle relaxation during surgery. Clin Phys Physiol Meas 1980;1:203–10 43. Monk CR, Millard RK, Hutton P, Prys-Roberts C. Automatic arterial pressure regulation using isoflurane: comparison with manual control. Br J Anaesth 1989;63:22–30 44. Schwilden H, Stoeckel H, Schüttler J. Closed-loop feedback control of propofol anaesthesia by quantitative EEG analysis in humans. Br J Anaesth 1989;62:290–6 45. Chilcoat, RT. A review of the control of depth of anaesthesia. Trans Inst M C 1980;2:38–45 46. Gentilini A, Frei CW, Glattfedler AH, Morari M, Sieber TJ, Wymann R, Schnider TW, Zbinden AM. Multitasked closed-loop control in anesthesia. IEEE Eng Med Biol Mag 2001;20:39–53 47. Gentilini A, Schaniel C, Morari M, Bieniok C, Wymann R, Schnider T. A new paradigm for the closed-loop intraoperative administration of analgesics in humans. IEEE Trans Biomed Eng 2002;49:289–99 48. Gentilini A, Rossoni-Gerosa M, Frei CW, Wymann R, Morari M, Zbinden AM, Schnider TW. Modeling and closed-loop control of hypnosis by means of bispectral index (BIS) with isoflurane. IEEE Trans Biomed Eng 2001;48:874–89 49. Absalom AR, Sutcliffe N, Kenny GN. Closed-loop control of anesthesia using Bispectral index: performance assessment in patients undergoing major orthopedic surgery under combined general and regional anesthesia. Anesthesiology 2002;96:67–73 50. Absalom AR, Kenny GN. Closed-loop control of propofol anaesthesia using bispectral index: performance assessment in patients receiving computer-controlled propofol and manually controlled remifentanil infusions for minor surgery. Br J Anaesth 2003;90:737–41 51. Liu N, Chazot T, Genty A, Landais A, Restoux A, McGee K, Laloë PA, Trillat B, Barvais L, Fischler M. Titration of propofol for anesthetic induction and maintenance guided by the bispectral index: closed-loop versus manual control: a
anesthesia & analgesia
Copyright © 2013 International Anesthesia Research Society. Unauthorized reproduction of this article is prohibited.
Closed-Loop Control of Anesthesia
prospective, randomized, multicenter study. Anesthesiology 2006;104:686–95 52. Puri GD, Kumar B, Aveek J. Closed-loop anaesthesia delivery system (CLADS) using bispectral index: a performance assessment study. Anaesth Intensive Care 2007;35:357–62 53. Hemmerling TM, Charabati S, Zaouter C, Minardi C, Mathieu PA. A randomized controlled trial demonstrates that a novel closed-loop propofol system performs better hypnosis control than manual administration. Can J Anaesth 2010;57:725–35 54. Dumont GA, Martinez A, Ansermino JM. Robust control of depth of anesthesia. Int J Adapt Control Signal Process 2009;23:435–54 55. Dumont GA, Liu N, Petersen C, Chazot T, Fischler M, Ansermino JM. Closed-loop administration of propofol guided by the NeuroSENSE: clinical evaluation using robust proportional-integral-derivative design. Conf Proc American Society of Anesthesiologists (ASA), October 15–19, 2011, Chicago, IL. A1170 56. Soltesz K, van Heusden K, Dumont GA, Hägglund T, Petersen C, West N, Ansermino JM. Closed-loop anesthesia in children using a PID controller: a pilot study. Conf Proc IFAC Conference on Advances in PID Control, March 28–30, 2012, Brescia, Italy 57. van Heusden K, Dumont GA, Soltesz K, Petersen C, West N, Ansermino JM. Clinical evaluation of closed-loop controlled propofol infusion in children. Conf Proc World Congress of Anaesthesiologists, March 25–30, 2012, Buenos Aires, Argentina. Paper no. 616 58. West N, Dumont GA, van Heusden K, Khosravi S, Petersen C, Ansermino JM. The administration of closed-loop control of anesthesia for gastrointestinal endoscopic investigations in children. Conf Proc Pediatric Anesthesiology, February 23–26, 2012, Tampa, FL. SP-241 59. Soltesz K, Hahn JO, Dumont GA, Ansermino JM. Individualized PID control of depth of anesthesia based on patient model identification during the induction phase of anesthesia. Conf Proc IEEE Conference on Decision and Control and European Control Conference (CDC-ECC), December 12–15, 2011, Orlando, FL. 855–60
60. Sawaguchi Y, Furutani E, Shirakami G, Araki M, Fukuda K. A model-predictive hypnosis control system under total intravenous anesthesia. IEEE Trans Biomed Eng 2008;55:874–87 61. Reboso JA, Méndez JA, Reboso HJ, León AM. Design and implementation of a closed-loop control system for infusion of propofol guided by bispectral index (BIS). Acta Anaesthesiol Scand 2012;56:1032–41 62. Liu N, Chazot T, Hamada S, Landais A, Boichut N, Dussaussoy C, Trillat B, Beydon L, Samain E, Sessler DI, Fischler M. Closedloop coadministration of propofol and remifentanil guided by bispectral index: a randomized multicenter study. Anesth Analg 2011;112:546–57 63. Liu N, Le Guen M, Benabbes-Lambert F, Chazot T, Trillat B, Sessler DI, Fischler M. Feasibility of closed-loop titration of propofol and remifentanil guided by the spectral M-Entropy monitor. Anesthesiology 2012;116:286–95 64. Hemmerling T, Charabti S. McSleepy: a completely automatic anesthesia delivery system. Conf Proc American Society of Anesthesiologists (ASA), October 17–21, 2009, New Orleans, LA. A460 65. Janda M, Simanski O, Bajorat J, Pohl B, Noeldge-Schomburg GF, Hofmockel R. Clinical evaluation of a simultaneous closedloop anaesthesia control system for depth of anaesthesia and neuromuscular blockade*. Anaesthesia 2011;66:1112–20 66. Simanski O, Janda M, Schubert A, Bajorat J, Hofmockel R, Lampe B. Progress of automatic drug delivery in anaesthesia— the ‘Rostock assistant system for anaesthesia control (RAN)’. Int J Adapt Control Signal Process 2009;23:504–21 67. Manberg PJ, Vozella CM, Kelley SD. Regulatory challenges facing closed-loop anesthetic drug infusion devices. Clin Pharmacol Ther 2008;84:166–9 68. Chan MT, Cheng BC, Lee TM, Gin T; The CODA Trial Group. BIS-guided anesthesia decreases postoperative delirium and cognitive decline. J Neurosurg Anesthesiol 2013;25:33–42 69. Ballard C, Jones E, Gauge N, Aarsland D, Nilsen OB, Saxby BK, Lowery D, Corbett A, Wesnes K, Katsaiti E, Arden J, Amoako D, Amaoko D, Prophet N, Purushothaman B, Green D. Optimised anaesthesia to reduce post operative cognitive decline (POCD) in older patients undergoing elective surgery, a randomised controlled trial. PLoS One 2012;7:e37410
XXX 2013 • Volume XX • Number XX www.anesthesia-analgesia.org 9
Copyright © 2013 International Anesthesia Research Society. Unauthorized reproduction of this article is prohibited.
