Closed loop muscle relaxant infusion
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Closed loop muscle relaxant infusion

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muscle relaxant closed loop administration

muscle relaxant closed loop administration

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    Closed loop muscle relaxant infusion Closed loop muscle relaxant infusion Presentation Transcript

    • Closed loop infusion of muscle relaxants Claudio Melloni Anestesia e Rianimazione Ospedale di Faenza(RA)
    • Why? Perfetto adattamento alle necessità » » » » » » » » Onset rapido….. Mantenimento ottimale Rapido offset Mancanza di PORC e delle sue sequele Diminuzione del consumo di farmaco/i Contenimento dei costi… Riduzione dei tempi di ripresa ottimizzazione turnover in sala op.
    • How deep is deep? Per IOT:scomparsa di tutte 4 le risposte al TOF Per mantenimento;1 solo del TOF presente ovvero 10% del T1.(. Viby-Mogensen J. Clinical assessment of neuromuscular transmission. Br J Anaesth 1982; 54:209-23. , Brull SJ, Silverman DG. Intraoperative use of muscle relaxants. Anesthesiology Clinics of North America 1993; 11:325-44. ) (On-demand, surgeon-controlled doses of mivacurium were injected at a mean of T1 42.3 ± 36%.while anesthesiologists maintained a 90% blockade Abdulatif M; Taylouni E.Surgeon controlled mivacurium infusion during elective cesarean section.CanAnesth.Soc.J.95:42;num 2. Saddler JM, Marks LF, Norman J. Comparison of atracurium-induced neuromuscular block in rectus abdominis and hand muscles of man. Br J Anaesth 1992; 69:26-8. Esigenze particolari;chirurgia oculare,della carena……..blocchi più profondi -
    • Saddler JM, Marks LF, Norman J. Comparison of atracuriuminduced neuromuscular block in rectus abdominis and hand muscles of man. Br J Anaesth 1992; 69:26-8. - We have compared neuromuscular block in the rectus abdominis and the hand muscles in 11 adult patients. Atracurium 0.5 mg kg-1 was administered by single bolus and anaesthesia maintained with isoflurane and nitrous oxide in oxygen. Train-of-four (TOF) stimulation was applied to the 10th intercostal space in the anterior axillary line and to the ulnar nerve at the wrist. Electromyographic (EMG) responses were recorded over the rectus abdominis and hypothenar muscles. Neuromuscular block had a significantly faster onset in the rectus abdominis (mean 1.6 (SEM 0.2) min) than in the hand (2.4 (0.3) min) (P less than 0.001). Recovery occurred more rapidly in the rectus abdominis: time to 25% TOF recovery was 39 (3) min at rectus abdominis and 51 (4) min at the hand (P less than 0.001). Time to 75% TOF recovery was 56 (4) min at rectus abdominis and 72 (6) min at the hand (P less than 0.001).
    • Comparison of atracuriuminduced neuromuscular block in rectus abdominis and hand muscles of man. Br J Anaesth 1992; 69:26-8. Saddler JM, Marks LF, Norman J. 80 70 60 50 Rectus abd AP 40 30 20 10 0 TOF25% TOF 75%
    • Hull A, Miller DR.Cumulatioon and reversal with prolonged infusion of atracurium or vecuronium.Can.Anaesth.Soc.J 1992:39;num7 A randomized, double-blind study was undertaken to compare the tendencies for cumulation, and reversal characteristics of atracurium (ATR) and vecuronium (VEC) when administered by continuous infusion for long surgical procedures under balanced anaesthesia. Eligible subjects were between 50 and 75 yr of age and were free of neuromuscular disease. Patients in the ATR group (n = 25) received a loading dose of atracurium 0.25 mg × kg-1, followed by an infusion initially set at 5.0 mg × kg-1 × min-1. In the VEC group (n = 25) patients received a loading dose of vecuronium 0.05 mg × kg-1, followed by an infusion at 1.0 mg × kg-1 × min-1. During surgery, the
    • Martineau RJ,Jean BSt,Kitts JB, Curran MC,Lindsay P, Hull A, Miller DR.Cumulation and reversal with prolonged infusion of atracurium or vecuronium.Can.Anaesth.Soc.J 1992:39;num7
    • Dosi richieste per il mantenimento Dosi richieste per il mantenimento + difficile che in induzione... farmaci cumulativi compensare per la distribuzione nel tempo variabilità interindividuale covariate:età,funzione epatica,renale,enzimi( variabilità intraindividuale ICU (Segredo BJA 1998,80,715-9)
    • Obbiettivi del closed loop Obbiettivi del closed loop da dimostrare.... diminuire la diminuire la fatica per fatica per l'anestesista l'anestesista +sicurezza +sicurezza migliorare le migliorare le condizioni condizioni chirurgiche chirurgiche abbreviare i abbreviare i tempi di tempi di ripresa ripresa
    • Utilità del closed loop Possibilità di studio delle interferenze farmacologiche(gas,vapori….) nelle stesse condizioni diminuzioni dei dosaggi??? (razionalizzazione????)
    • Advantages of closed loop vs manual control of atracurium infusion 6 5 4 3 Eager BM, Flynn PJ, Hughes R. Iufusion of atracurium for long surgical procedures. Br J Anaesth 1984; 56:447-52. ?? mason 1 Eager mason2 mason3 martineau Martineau RJ,Jean BSt,Kitts JB, Curran MC,Lindsay P, Hull A, Miller DR. Cumulatioon and reversal with prolonged infusion of atracurium or vecuronium. Can.Anaesth.Soc.J 1992:39;num7 2 1 0 dose required to maintain T1 10%
    • Atracurium infusion rates to maintain 90% blockade under 4 different anesthetic techniques.O'Hara DA, Derbyshire GJ, Overdyk FJ, Bogen DK, Marshall BE. Closed-loop infusion of atracurium with four different anesthetic techniques. Anesthesiology 1991; 74:258-63 8 6 microgr/kg/min 4 2 0 haloth enflurane isoflurane morph/N2O
    • Olkkola KT, Tammisto T. Quantifying the interaction of rocuronium (Org 9426) with etomidate, fentanyl, midazolam, propofol, thiopental, and isoflurane using closed-loop feedback control of rocuronium infusion. Anesth Analg 1994; 78:691-6.
    • Olkkola KT, Tammisto T. Quantifying the interaction of rocuronium (Org 9426) with etomidate, fentanyl, midazolam, propofol, thiopental, and isoflurane using closed-loop feedback control of rocuronium infusion. Anesth Analg 1994; 78:691-6.
    • Steady state infusion of rocuronium controlled by a closed loop feedback model during tiva (Olkkola KT, Tammisto T. Quantifyig the interaction of rocuronium (Org 9426) with etomidate, fentanyl, midazolam, propofol, thiopental, and isoflurane using closed-loop feedback control of rocuronium infusion. Anesth Analg 1994; 78:691-6. 0,70 0,60 0,50 mg/kg/h 0,40 0,30 0,20 0,10 * etomidate fentanyl midazolam propofol thiopental isoflurane 0,7% 0,00 Compared to IV anesthetics, isoflurane decreases the rocuronium infusion requirement by 35%–40%.
    • Abdulatif M; Taylouni E.Surgeon controlled mivacurium infusion during elective cesarean section.CanAnesth.Soc.J.95:42;num 2. 24 C/S,elettivi, a termine TPS/Scc/IOT/Isofl/N2O/fent MMG 2 gruppi;anestesista vs chirurgo » Anestesista:mivacurium qb per T1 10% » Chirurgo:mivacurium boli qb per rilasciamento addominale
    • Comparison of anesthesiologist vs surgeon controlled relaxation with mivacurium for C/S. 80,0 70,0 60,0 % 50,0 % 40,0 30,0 mg 20,0 % 10,0 0,0 dose tot T1 end surgery Tof end of Antagonism surgery Anest Chir
    • The goals of automated control The goals of automated control The accuracy of the control depends on the accuracy of the sensors used to measure the controlled variable To keep the average value of the controlled variable within defined limits. These limits may be fixed in advance or may be varied if the system is to adapt to changes in conditions. Within these limits, to minimize oscillations in the controlled variable. The system must remain stable, so that over time the size of the oscillations either becomes smaller or remains constant at an acceptable level, rather than increasing, which would allow the controlled variable to swing wildly.
    • Modelli On/OFF Model based Fuzzy logic
    • DeVries JW, Ros HH, Booij LHD: Infusion of vecuronium controlled by a closed-loop system. Br J Anaesth 58:1100-1103, 1986 Nicomorph+aloperidol:TPS/fent vecu 0.07 mg/kg/N2O iot closed loop activated <16% control EMG hypothenar
    • Schematic diagram of the control system and oscillations around the preset value(DeVries JW, Ros HH, Booij LHD: Infusion of vecuronium controlled by a closed-loop system. Br J Anaesth 58:1100-1103, 1986) passive element :adaptor between NTM and comparator Controller;solid state relay and syringe pump; Pump on isteresi Pump off swithched on when the input of the comparator >value A and switched off when it was lower than B
    • DeVries JW, Ros HH, Booij LHD: Infusion of vecuronium controlled by a closed-loop system. Br J Anaesth 58:1100-1103, 1986
    • DeVries JW, Ros HH, Booij LHD: Infusion of vecuronium controlled by a closed-loop system. Br J Anaesth 58:1100-1103, 1986 Depression of nmt oscillated around the preset value:13-17% of control; no twitch height <10% or> 25% avg vecu 1.1 microgr/kg /min(range 0.8-1.5) rapid recovery:mean 11 min,range 522 pts awakened at T1 70% & tof 50% antagonism 3/28
    • Controllers type TYPE On/off: Problems: overshoot , oscillation about the setpoint. PID: the system react, not just to the magnitude of the error, but to the accumulated error over time (integral of error) and the rate of change of error (derivative of error). A control system that reacts to all three attributes of error is known as a proportionalintegral-derivative (PID) controller. steady-state offset error, a poor response time, some overshoot.
    • A feedback controller uses the error signal to calculate the correct infusion rate of a drug for maintaining the response at or near the chosen setpoint. The error signal is the difference between the setpoint and the desired response. Closed-loop controllers require a specific monitor of the desired response, which “feed back” to regulate the controlling agent. For muscle relaxant control, the measured response usually is the electromyogram (EMG). A PID controller takes three components of the measured response to increase the speed and accuracy of control: the error signal itself (proportional component), a summation of the area between the EMG response curve and the EMG setpoint level (integral component), and the rate of change of the error signal
    • Controllers type:II PID 2 phases; better overshoot,shorter response time(initial bolus allowed…) Adaptive The tuning of a controller does not need to be permanently fixed. Adaptive control systems are those in which the tuning is varied to adapt to changing conditions. proportional:input to the system is proportional to the error
    • Controllers type:III state estimation The output response of the patient to an input is estimated by equations that include the response in the “effect” compartment and any time delays (i.e., the kinetics and dynamics of the response). The equations are rewritten to define the response at time (t + Dt) in terms of the response at time t and a state vector. The advantage of state estimation is that all of the characteristics of the system, including nonlinear and time-varying responses, are modeled into the system.
    • 3. Adaptive Rametti et al.( dTC),Bradlow et al.( atracurium ) using on-line state estimation. They initially estimated the patient response to a bolus of drug, modeling the response with a nonlinear least-squares method. The model included the time delay in the onset of relaxation and the nonlinear pharmacodynamics of muscle relaxant agents. Depending on the patient response, the parameters of the controller were updated. The controller had both minimal overshoot and minimal oscillation about the operating point.
    • O'Hara DA, Derbyshire GJ, Overdyk FJ, Bogen DK, Marshall BE. Closed-loop infusion of atracurium with four different anesthetic techniques. Anesthesiology 1991; 74:258-63. 32 patients EMG PID controller for the automated closedloop delivery of atracurium Groups :halothane, enflurane, isoflurane, or N2O/morphine anesthesia. TPS/Atrac bolus infusion calculated to maintain the (EMG) at a setpoint of 90% nmb.
    • average overshoot for the controller was 10.1% and the mean steady-state error 3.0%. mean infusion rates for atracurium N2O/morphine, halothane 0.8%, enflurane 1.7%, and isoflurane 1.4% at 90% blockade were 5.7 ± 0.6, 4.9 ± 0.3, 3.5 ± 0.3, and 4.1 ± 0.5 mg × kg-1 × min-1, respectively (mean ± SE). This controller performed well in comparison to previously developed controllers, and in addition was used as a research tool for rapid estimation of infusion rates.
    • O'Hara DA, Derbyshire GJ, Overdyk FJ, Bogen DK, Marshall BE. Closed-loop infusion of atracurium with four different anesthetic techniques. Anesthesiology 1991; 74:258-63.
    • EMG with time(upper graph) and PID control(pump rate)(lower graph) for one patient in the halothane group O'Hara DA, Derbyshire GJ, Overdyk FJ, Bogen.DK, Marshall BE. Closed-loop infusion of atracurium with four different anesthetic techniques. Anesthesiology 1991; 74:258-63.
    • EMG response to a bolus and PID control of atraurium under narcotic/N2O anesthesia ;setpoint changed from 80 to 90% blockade at time 45 min.O'Hara DA, Derbyshire GJ, Overdyk FJ, Bogen DK, Marshall BE. Closed-loop infusion of atracurium with four different anesthetic techniques. Anesthesiology 1991; 74:258-63.
    • Performances of various muscle relaxant controllers from the literature.O'Hara DA, Derbyshire GJ, Overdyk FJ, Bogen DK, Marshall BE. Closed-loop infusion of atracurium with four different anesthetic techniques. Anesthesiology 1991; 74:258-63.
    • Muscle relaxant controllers
    • Model driven
    • Olkkola KT, Schwilden H. Quantitation of the interaction between atracurium and succinylcholine using closed-loop feedback control of infusion of atracurium. Anesthesiology 1990; 73:614-8. TPS/N2= 60%,flunitrazepam,fent EMG Datex relaxograph. T1/Tc TOF q.20 sec. Model driven closed feedback system(Fresenius pump/Toshiba computer/RS232 90% depression(T1 10%)set point
    • Model driven computerized infusion of atracurium Olkkola KT, Schwilden H. Quantitation of the interaction between atracurium and succinylcholine using closed-loop feedback control of infusion of atracurium. Anesthesiology 1990; 73:614-8. 2 compartment open mammillary model;hypothetical effect compartment linked to the central compartment integrated PK-PD model with 2 formulas; » 1st representing the relationship between drug input and concentration of the drug in the effect compartment » 2nd representing the relationship between concentration and effect
    • Model driven computerized infusion of atracurium Olkkola KT, Schwilden H. Quantitation of the interaction between atracurium and succinylcholine using closed-loop feedback control of infusion of atracurium. Anesthesiology 1990; 73:614-8.
    • Rate of atracurium infusion(mg/kg/min) under balanced i.v.anesthesia Olkkola KT, Schwilden H. Quantitation of the interaction between atracurium and succinylcholine using closed-loop feedback control of infusion of atracurium. Anesthesiology 1990; 73:614-8. 0.43 0.36 +/-0.10 0.28 +/-0.06 0.21 0.14 0.07 0.00 atrac ch+atrac
    • Cumulative dose + SE calculated as mg of atracurium /body weight in the 2 groups given atracurium preceded by succinylcholine( Sch+Atr) or without(ATR) to produce a constant 90% nmblockade by closed loop administration of atracurium. Olkkola KT, Schwilden H. Quantitation of the interaction between atracurium and succinylcholine using closed-loop feedback control of infusion of atracurium. Anesthesiology 1990; 73:614-8.
    • Data for one patient in the group treated with atrac only;infusion rate for a constant 90% block and cumulative atrac dosage with fitted cumulative dose(straight line) Olkkola KT, Schwilden H. Quantitation of the interaction between atracurium and succinylcholine using closedloop feedback control of infusion of atracurium. Anesthesiology 1990; 73:614-8.
    • Data for one patient in the group given Scc before atrac:rate of infusion for a 90% blockade and cumulative dosage of atrc with fitted cumulative dose(sraight line) of atrac .( Olkkola KT, Schwilden H. Quantitation of the interaction between atracurium and succinylcholine using closed-loop feedback control of infusion of atracurium. Anesthesiology 1990; 73:614-8.
    • Olkkola KT, Tammisto T. Quantifying the interaction of rocuronium (Org 9426) with etomidate, fentanyl, midazolam, propofol, thiopental, and isoflurane using closed-loop feedback control of rocuronium infusion. Anesth Analg 1994; 78:691-6.
    • Black box concept Black box concept proposta di controllo..... Controller: Dose of nmb body blockade desired expected Algorythm E P/ID....
    • Controller Controller calculates the difference between the measured output and the desired output (let's call it the error "e"), and correct the input according to a preset algorithm to minimize this difference. Error Error how fast it changed (derivative) how fast it changed (derivative) what was its overall time course (integral). what was its overall time course (integral). infusion rate algorithm looks like :: infusion rate algorithm looks like v(t) = weight.[ kp.(e) + ki.ò edt+kd .. de/dt] v(t) = weight.[ kp.(e) + ki.ò edt+kd de/dt] Fuzzy logic: Fuzzy logic: error signal (E) between the actual and desired TI value error signal (E) between the actual and desired TI value is processed first to form the differential (D = dE/dt) and is processed first to form the differential (D = dE/dt) and integral (I) components. The error signal (E) gives the integral (I) components. The error signal (E) gives the proportional component (P) directly proportional component (P) directly
    • parameters parameters Initial infusion rate time rom initial bolus to 5% recovery....sensitivity.... additional boluses if T1 >10% when nmb started to recover ;for atrac 5 mg over 3 min.... requirement of a fast increase in the nmblockade When the set point was reduced from 20% to 10%, an additional bolus dose of atracurium was administered equal to 10% of the value of the current mg h-1 integral (I) component of the fuzzy controller output. Dose limits: atracurium infusion rate was subject to an upper limit of 100 mg h-1, the atracurium infusion was temporarily stopped if the median T1 value was more than 5% below the set point.
    • Rules of functioning fuzzy logic IF T1 is greater than the set point by a LARGE amount AND T1 is moving towards the set point but only SLOWLY THEN set the atracurium infusion rate to a HIGH level.” The first line of this rule is a proportional (P) controller component, the second a differential (D) component. These antecedent components are fuzzy rule inputs. The final line is the fuzzy rule output.
    • Mason DG, Edwards ND, Linkens DA, Reilly CS. Performances assessment of a fuzzy logic controller for atracurium-induced neuromuscular block. Br. J. Anaesth. 1996; 76:396-400 fuzzy controller atracurium-induced neuromuscular block 10 ASA I or II patients Datex Relaxograph T1 set point set at 10% of baseline for at least 30 min (phase I). The T1 set point was then increased to 20% and then returned to 10% for two further periods of at least 30 min duration (phases II and III). The mean (SD) of the mean T1 error in 10 patients for phases I, II and III were 1.1 (1.4)%, -0.43 (1.2)% and 0.28 (0.94)%, respectively. The results show that a simple fuzzy logic controller can provide good accuracy with insensitivity to set point changes despite the considerable inter-individual variation in infusion
    • Mason DG, Edwards ND, Linkens DA, Reilly CS. Performances assessment of a fuzzy logic controller for atracurium-induced neuromuscular block. Br. J. Anaesth. 1996; 76:396-400 Fuzzy logic control is a simple, although effective, technique for controlling non-linear and uncertain processes . The effect of neuromuscular blockers is non-linear and fuzzy logic provides a simple way to create a non-linear controller. Fuzzy logic accommodates uncertainty by dealing in imprecise, qualitative terms such as low, medium and high. This also provides control rules which are easy to understand and therefore simple to modify.
    • The derivation of the fuzzy rules is a common bottleneck in the application of fuzzy logic controllers. Conventionally, these fuzzy rules are based on emulating the control actions of an expert. Such a case was reported recently with the clinical application of fuzzy logic control to arterial pressure regulation using isoflurane . However, with neuromuscular block no such experience is readily available to draw on for derivation of the fuzzy rulebase. This situation was the main driving force behind the introduction of selforganizing fuzzy logic controllers . For this study, however, a fuzzy rulebase was hand-crafted based on a simulation involving the non-linear atracurium dose-
    • Mason DG, Edwards ND, Linkens DA, Reilly CS. Performances assessment of a fuzzy logic controller for atracurium-induced neuromuscular block. Br. J. Anaesth. 1996; 76:396-400 A particular configuration of fuzzy logic controller known as PD+I (proportional, differential plus integral) was found to be appropriate for this application via the use of computer simulation studies . This fuzzy controller comprises separate PD and I components which correspond to dynamic and memory parts, respectively. The error signal (E) between the actual and desired TI value is processed first to form the differential (D = dE/dt) and integral (I) components. The error signal (E) gives the proportional component (P) directly. These error signals which are input to the fuzzy controller first need to be scaled to suit the particular control application. The separate outputs of the fuzzy PD and fuzzy I components also require
    • The error signal (E) gives the proportional component (P) directly. These error signals which are input to the fuzzy controller first need to be scaled to suit the particular control application. The separate outputs of the fuzzy PD and fuzzy I components also require scaling to suit the specific application. These input and output scaling factors for this fuzzy controller were identified by iterative computer simulations until good control performance was observed. We then assessed the performance of this fuzzy atracurium controller in clinical practice.
    • Mason DG, Edwards ND, Linkens DA, Reilly CS. Performances assessment of a fuzzy logic controller for atracurium-induced neuromuscular block. Br. J. Anaesth. 1996; 76:396-400 The initial T1 set point was entered as 10% of baseline, a file name was entered for data storage and the concentration of atracurium (2 mg ml-1) was entered so that the computer could convert the controller output from mass rate (mg h-1) to volume flow rate (ml h-1). In addition, the patient's weight was entered for calculation of the atracurium loading dose. When the computer system was satisfied that no alarm conditions were active, it delivered a loading dose of atracurium 0.33 mg kg-1 at 1200 ml h-1 to facilitate tracheal intubation. Anaesthesia was maintained with a propofol infusion of 8-10 mg kg-1 h1, the patient's lungs ventilated with 66% nitrous oxide in oxygen and morphine administered as appropriate.
    • Mason DG, Edwards ND, Linkens DA, Reilly CS. Performances assessment of a fuzzy logic controller for atracurium-induced neuromuscular block. Br. J. Anaesth. 1996; 76:396-400 The fuzzy controller used the median of the last three T1 values. The Datex Relaxograph performed a trainof-four stimulation every 20 s to calculate the T1 error values at 1-min intervals which the fuzzy controller then used. The controller remained active at the initial 10% set point level for at least 30 min (phase I). The set point was then increased to 20% by keyboard entry and then returned to 10% again for two further periods of at least 30 min duration (phases II and III) (). When the set point was reduced from 20% to 10%, an additional bolus dose of atracurium was administered equal to 10% of the value of the current mg h-1 integral (I) component of the fuzzy controller
    • Mason DG, Edwards ND, Linkens DA, Reilly CS. Performances assessment of a fuzzy logic controller for atracurium-induced neuromuscular block. Br. J. Anaesth. 1996; 76:396-400 Several different computer systems for feedback control of atracurium infusions have been reported. The periods used for performance analysis in these studies differ. Most have analysed only steady state performance . We included transient phases in our performance analysis. Unlike previously reported clinical studies we tested the controller sensitivity to set point changes. Most studies have used EMG to monitor neuromuscular block. However, various different maintenance anaesthetics were used, some of which potentiate the effects of neuromuscular blockers. It is therefore not possible to provide a valid comparison of performance across these different atracurium controllers in terms of mean, SD and RMSD. However, there appears to be no statistically or clinically significant difference in reported controller performances. The main advantage the fuzzy controller offers over previously reported controllers is its simplicity and its friendly or intuitive designer interface. For example, a possible fuzzy
    • Mason DG, Edwards ND, Linkens DA, Reilly CS. Performances assessment of a fuzzy logic controller for atracurium-induced neuromuscular block. Br. J. Anaesth. 1996; 76:396-400
    • Mason DG, Edwards ND, Linkens DA, Reilly CS. Performances assessment of a fuzzy logic controller for atracurium-induced neuromuscular block. Br. J. Anaesth. 1996; 76:396-400
    • Ross JJ, Mason DG, Linkens DA, Edwards ND. Selflearning fuzzy logic control of neuromuscular block. British Journal of Anaesthesia 1997; 78: 412-5. performance of a “self-learning” fuzzy logic controller atracurium 20 ASA I and II patients Datex Relaxograph control to a T1 twitch height set point of 10% of baseline neuromuscular function The controller commenced with a blank rule-base and instructed a Graseby 3400 infusion pump to administer an atracurium infusion to maintain this level of block.
    • The system achieved stable control of neuromuscular block with a mean T1 error of -0.52% (SD 0.55%) accommodating a range in mean atracurium infusion rate of 0.25–0.44 mg kg-1 h-1. These results compare favourably with the more computationally intensive and unwieldy adaptive control strategies for atracurium infusion used previously. There was less variation in infusion rates than in our previously studied fixed rules fuzzy controller.
    • Ross JJ, Mason DG, Linkens DA, Edwards ND. Selflearning fuzzy logic control of neuromuscular block. British Journal of Anaesthesia 1997; 78: 412-5.
    • Ross JJ, Mason DG, Linkens DA, Edwards ND. Selflearning fuzzy logic control of neuromuscular block. British Journal of Anaesthesia 1997; 78: 412-5. Recovery of T1 was monitored every 20 s, giving an indication of patient sensitivity to the drug, allowing the controller to create its first control rule. Thus, for instance, if recovery was rapid, a high initial infusion rate was selected as T1 approached 10%, to a maximum rate of 100 mg h-1. If T1 failed to decrease below the 10% set point, the computer was programmed to deliver an additional 5-mg bolus and repeat as necessary until T1 was less than 10%. The fuzzy controller commenced operation when T1 had recovered to between 5% and 10%. To reduce spurious data from noisy signals the median of the previous three readings was used. This median T1 value, calculated each
    • Ross JJ, Mason DG, Linkens DA, Edwards ND. Selflearning fuzzy logic control of neuromuscular block. British Journal of Anaesthesia 1997; 78: 412-5.
    • Ross JJ, Mason DG, Linkens DA, Edwards ND. Selflearning fuzzy logic control of neuromuscular block. British Journal of Anaesthesia 1997; 78: 412-5 Fuzzy logic is an appropriate, simple and effective technique for controlling non-linear and unpredictable processes, dealing in imprecise, qualitative (i.e. “fuzzy”) terms such as “low”, “medium” or “high” rather than precise measurements. This imprecision permits very simple but effective control rules to be generated which are easy to modify and update rapidly in realtime. Fuzzy logic control is intrinsically suited to the control of physiological processes because it requires little hard input data before it can begin functioning, unlike other strategies such as “neural networks”.
    • For closed-loop control of neuromuscular block the following features need to be addressed when designing the system: recognition of the onset and, more importantly, the rate of decay of neuromuscular block; recognition of the difference between desired and actual T1 value (error); recognition of the rate of change in error from the desired T1 value; and elimination of drift from the desired T1 value when achieved, that is steady state error.
    • Using a fixed rule-base, we have demonstrated previously that fuzzy logic control is appropriate for controlling neuromuscular block. However, the development of such a controller required the construction of a hand-crafted rule-base which was time and labour intensive. However, by incorporating a “self-learning” layer to the fuzzy controller, it becomes self-teaching in real-time in the clinical situation and dispensed with the need for a pre-set fixed rule-base. Our self-learning controller starts with a blank rulebase, and this is the first study to investigate the clinical application of such an intelligent control technique.
    • Ross et Self-learning fuzzy logic control of neuromuscular block. British Journal of Anaesthesia 1997; 78: 412-5 The “self-learning” strategy implemented in our controller functioned by rapidly and repeatedly measuring T1 twitch height and modifying the atracurium infusion rate. This allowed the controller to recognize the patient's drug requirements and select infusion rates appropriate to maintain 90% neuromuscular block. Initially, the fuzzy rule-base is completely blank as the controller is unaware of its first rule until control begins. This first rule is simple and generated by assessing the return of neuromuscular tone towards the desired T1 height. The effect is then assessed and adapted by generating new rules as control continues. This is
    • Ross et Self-learning fuzzy logic control of neuromuscular block. British Journal of Anaesthesia 1997; 78: 412-5 The results of this study showed improved performance over previous controllers. Control was as good as our previous fixed-rule controller with less erratic infusion rates being demanded; the controller delivered a mean SD atracurium infusion rate of 0.16 mg kg-1 h-1 for the first 30 min compared with 0.23 mg kg-1 h-1 in our previous study. Control was implemented with a basic amount of information. At no point did the controller have to administer a bolus in order to regain control of a deteriorating situation and in no case was a diverging or progressively unstable oscillation entered.
    • While fuzzy logic has been used in other fields in anaesthesia this is the first occasion where, by application of a self-learning facility to the fuzzy logic controller, a physiological process during anaesthesia has been controlled entirely by machine alone. The controller determined individual drug requirements and administered atracurium accurately in each case, demonstrating the ability to assess and respond to fluctuating patient conditions during surgery. The success of this self-learning control system should encourage research into the control of other physiological processes.
    • and concentration-response relation of rocuronium infusion during propofol-nitrous oxide and isofluranenitrous oxide anaesthesia. Eur J Anaesthesiol 1997; 14: 488-94.
    • Ross JJ, Mason DG, Linkens DA, Edwards ND. Selflearning fuzzy logic control of neuromuscular block. British Journal of Anaesthesia 1997; 78: 412-5.
    • Asbury AJ, Tzabar Y. Fuzzy logic: new ways of thinking for anaesthesia. British Journal of Anaesthesia 1995; 75: 12. Although they might not like to admit it, anaesthetists use “rules of thumb” when managing patients. Imagine a patient on the operating table: as the operation proceeds, changes in the patient's physiological state are monitored by the anaesthetist who adjusts the drug inflow or possibly ventilation. The anaesthetist probably uses a rule of thumb to determine the extent and direction of his adjustments. That anaesthetists use imprecise, personal rules does not prevent them from providing a safe and effective anaesthetic; every doctor uses some type of rules, but sometimes simple rules are obscured by an aura of profundity. This is merely one aspect to consider if computers are to assist anaesthetists in their work. Consider a rule of thumb such as “If the end–tidal carbon dioxide concentration increases slowly, then increase the minute ventilation a little”. In addition to a proposed action, this rule contains imprecise terms such as “a little” and “slowly”, terms that are difficult to express and manipulate in a computer. Humans have no difficulty with such imprecise information or even uncertain value judgements such as “the blood pressure is high”, but they are the obstacles to exploiting an expert's knowledge in a computer system simply because there is no language to describe imprecise data in a way that a computer understands . The key to this problem lies in an article published in 1965 by Lofti Zadeh, then Professor of Electrical Engineering at the University of California at Berkeley who coined the term “fuzzy sets”. A set is merely a group of distinguishable objects, or even distinguishable concepts such as elephants, cars, whole numbers or good thoughts. In the classical understanding of sets, an item would belong rigidly to one set or another. For example, a spoon would belong to the set titled “spoons”, and everything else would belong to the set titled “not–spoons”, there is no middle ground for spoon–like items (e.g. ladles and spades). The concept of a fuzzy set is one where an item can simultaneously belong to several sets to different degrees, from not belonging (or 0% membership) through to totally belonging (or 100% membership) to a set. This is a reasonable concept as may be seen in the following example. Consider a collection of systolic arterial pressure measurements from 20 to 220 mm Hg, and assign them into sets such as “normal”, “very low”, “high”, etc. Using classical logic (), each value then takes on 100% membership of one, and only one set. This logic becomes less reasonable when 99 mm Hg is
    • tuning, microprocessor-based closed-loop control of atracurium- induced neuromuscular blockade. British Journal of Anaesthesia 1988; 61: 685-92.
    • 8: Bradlow HS, Uys PC, Rametti LB. On-line control of atracurium induced muscle relaxation. Journal of Biomedical Engineering 1986; 8:72-75. 9: MacLeod, AD, Asbury AJ, Gray WM, Linkens DA. Automatic control of neuromuscular block with atracurium. British Journal of Anaesthesia 1989; 63:31-35. 10: Uys PC, Morrell DF, Bradlow HS, Rametti LB. Self-tuning, microprocessorbased closed-loop control of atracurium-
    • Performance assessment of a fuzzy controller for atracurium-induced neuromuscular block. Br. J. Anaesth. 1996; 76:396-400.
    • Administration des curares pour chirurgie plastique : apports de l'adaptation bayésienne. Ann.Fr.Anesth.Reanim. 15[6], R279. 1996.
    • J.A. Kuipers, F.Boer, E.Olofsen, J.G.Bovill and A.G.Burm, Recirculatory Pharmacokinetics and Pharmacodynamics of Rocuronium in Patients: The Influence of Cardiac Output. Anesthesiology; 94: 47-55 2001.
    • rate (ETI) of cisatracurium more than isoflurane, sevoflurane, or propofol Can J Anesth 2001 / 48 / 532537 thomashemmerling@hotmail.com The present study investigated the interaction between the cumulative dose requirements of cisatracurium and anesthesia with isoflurane, sevoflurane, desflurane or propofol using closed-loop feedback control.Methods: Fifty-six patients (18–85 yr, vitrectomies of more than one hour) were studied. In the volatile anesthetics groups, anesthesia was maintained by 1.3 MAC of isoflurane, sevoflurane or desflurane; in
    • dose requirement for one patient (isoflurane 1.3 mac) Hemmerling TM, Schuettler J, Schwilden H. Desflurane reduces the effective therapeutic infusion rate (ETI) of cisatracurium more than isoflurane, sevoflurane, or propofol Can J Anesth 2001 / 48 / 532537
    • desflurane,isoflurane,sevoflurane,propofol groups. Hemmerling TM, Schuettler J, Schwilden H. Desflurane reduces the effective therapeutic infusion rate (ETI) of cisatracurium more than isoflurane, sevoflurane, or propofol Can J Anesth 2001 / 48 / 532537 Isoflurane, sevoflurane and desflurane at 1.3 MAC reduce the cumulative dose requirements of cisatracurium by 42%, 41% and 60% in comparison to propofol at 6–8 mg×kg-1×hr-1. Desflurane significantly reduced the cumulative dose requirements of cisatracurium in comparison to evoflurane and isoflurane .
    • rate (ETI) of cisatracurium more than isoflurane, sevoflurane, or propofol Can J Anesth 2001 / 48 / 532537 The controller performance was regarded as sufficient at an average difference from 2.0% (group D) to 3.2% (group I) between the set point of T1%=10% and the measured degree of neuromuscular blockade.
    • cisatracurium more than isoflurane, sevoflurane, or propofol Can J Anesth 2001 / 48 / 532-537 The controller performance for cisatracurium was different from those found for other nondepolarizing muscle relaxants such as vecuronium, atracurium or rocuronium. In the latter study, Olkkola et al. investigated the interaction of rocuronium with several iv anesthetics or isoflurane; the best controller performance values were achieved at 0.2% to 0.8% average offset from set point. The controller performance found in our study could have been anticipated because cisatracurium shows a more marked hysteresis and slower onset time than the other three non-depolarizing muscle relaxants. Wulf et al. recently showed a significant decrease of ED50 and ED95 of cisatracurium during anesthesia with 1.5 MAC (in a mixture of 70% nitrous oxide/30% oxygen) of desflurane, sevoflurane or isoflurane in comparison to propofol. It is interesting to note that the time to reach 25% of control level of TOF stimulation was not statistically different between the groups, but recovery index and time to reach a TOF ratio of 0.7 were significantly prolonged during anesthesia with desflurane and sevoflurane in comparison to propofol, but not so for isoflurane. There are, however, several limitations to that study. The cumulative dose technique might underestimate the potency of the neuromuscular blocking drugs. Diffusion of the inhaled anesthetic requires more than 30 min to reach equilibrium and this time span is different for the volatile anesthetic tested. Hendricks et al. showed that uptake for desflurane and isoflurane might even take up to an hour. These findings limit at least the interpretation of the degree of ED50 or ED95 reductions. Wulf et al. admit themselves that the application of the total dose in increments could have underestimated the effect of the duration of action of cisatracurium during continuous infusion of propofol. Finally, in contrast to the current study, which used the algorithm presented by Mapleson In contrast to the present study, most studies have compared cumulative dose requirements of volatile anesthetics in breathing gas mixtures including nitrous oxide. A recent study, however, shows by calculating isoboles for desflurane and cumulative doses of nitrous oxide, that the decrease of the required desflurane concentrations by the administration of nitrous oxide might be less than expected from their MAC values. This could mean that for different volatile anesthetics,
    • 10: Olkkola KT, Schwilden H. Adaptive closedloop feedback control of vecuronium-induced neuromuscular relaxation. Eur J Anaesth 1991; 8:7-12. 11: Olkkola KT, Kansanaho M. Quantifying the interaction of vecuronium with enflurane using closed-loop feedback control of vecuronium infusion. Acta Anaesthesiol Scand 1995; 39:489-93.
    • Kansanaho M, Olkkola KT. Quantifying the effect of enflurane on atracurium infusion requirements. Can J Anaesth 1995; 42:103-8. The present study was designed to evaluate the interaction between atracurium and enflurane in 40 adult surgical patients using closed-loop feedback control of infusions of atracurium. Anaesthesia was induced with thiopentone and fentanyl and intubation was facilitated with atracurium 0.5 mg × kg-1 lean body
    • This study was designed to quantify the effect of clinically relevant concentrations of enflurane on atracurium infusion requirements and to investigate the possible time dependence of this interaction. We used the technique of closed-loop feedback control of atracurium infusion to maintain a steady neuromuscular blockade of 90%.
    • the effect of enflurane on atracurium infusion requirements. Can J Anaesth 1995; 42:103-8.
    • the effect of enflurane on atracurium infusion requirements. Can J Anaesth 1995; 42:103-8.
    • as his/her own control) Kansanaho M, Olkkola KT. Quantifying the effect of enflurane on atracurium infusion requirements. Can J Anaesth 1995; 42:103-8. 0.36 0.28 N2O/O2 enflurane 0.3% enflurane 0.6% enflurane 0.9% 0.21 mg/kg/h 0.14 0.07 0.00 Ist 90 min IInd 90 min
    • Olkkola KT, Tammisto T. Quantifying the interaction of rocuronium (Org 9426) with etomidate, fentanyl, midazolam, propofol, thiopental, and isoflurane using closed-loop feedback control of rocuronium infusion. Anesth Analg 1994; 78:691-6. The present study was designed to evaluate the interactions of rocuronium with etomidate, fentanyl, midazolam, propofol, thiopental, and isoflurane using closed-loop feedback control of infusion of rocuronium. Sixty patients were randomly assigned to one of six sequences where anesthesia was maintained with etomidate, fentanyl, midazolam, propofol, or thiopental and nitrous oxide, or with isoflurane and nitrous oxide. The possible interaction of rocuronium with the anesthetics was quantified by determining the asymptotic steady-state rate of infusion (Iss) of rocuronium necessary to produce a constant 90% neuromuscular block. This was accomplished by applying nonlinear curve fitting to data on the cumulative dose requirement during the initial 90-min period after bolus administration of rocuronium. Patient characteristics and controller performance, i.e., the ability of the controller to maintain the neuromuscular block constant at the set-point, did not differ significantly between the groups. Iss values calculated per lean body mass were 0.64 ± 0.22, 0.60 ± 0.15, 0.61 ± 0.21, 0.67 ± 0.31, 0.63 ± 0.15, and 0.39 ± 0.17
    • Olkkola KT, Tammisto T. Quantifying the interaction of rocuronium (Org 9426) with etomidate, fentanyl, midazolam, propofol, thiopental, and isoflurane using closed-loop feedback control of rocuronium infusion. Anesth Analg 1994; 78:691-6. After induction of anesthesia, but before rocuronium for neuromuscular block, we used a RelaxographÒ neuromuscular transmission monitor (Datex, Helsinki, Finland) to obtain control electromyographic values. Specifically, the train-of-four sequence was assessed (frequency of stimuli, 2 Hz; pulse
    • nonlinear curve fitting to fit the following formula to the curve representing the cumulative dose requirement of rocuronium during the initial 90-min period after the bolus administration of rocuronium : where D = amount of rocuronium contained its apparent distribution
    • Meretoja, O. A.; Taivainen, T.; Wirtavuori, K.; Olkkola, K. T.Pharmacodynamics of mivacurium in infants.BJA 1994;73 :num4... ABSTRACT: A computerized infusion system was used to determine mivacurium infusion requirements to maintain 95% and 50% neuromuscular block in 15 infants less than 1 yr of age. Neuromuscular block was measured by adductor pollicis EMG and anaesthesia maintained with 66% nitrous oxide in oxygen and
    • Meretoja, O. A.; Taivainen, T.; Wirtavuori, K.; Olkkola, K. T.Pharmacodynamics of mivacurium in infants.BJA 1994;73 :num4...
    • Meretoja, O. A.; Taivainen, T.; Wirtavuori, K.; Olkkola, K. T.Pharmacodynamics of mivacurium in infants.BJA 1994;73 :num4... We have evaluated the pharmacodynamics of mivacurium in infants using a model–driven computerized infusion device to maintain two different levels of neuromuscular block. The infusion device was easy to use and resulted in relatively rapid control of the target neuromuscular block. If mivacurium infusion is adjusted by
    • Meretoja, O. A.; Olkkola, K. T.Pharmacodynamics of mivacvurium in children using a computer controlled infusion.BJA 1993:71: A computerized infusion system was used to determine requirement for a mivacurium infusion to maintain a 95% and a 50% neuromuscular block in 21 children aged 1–15 yr. Neuromuscular block was measured by adductor pollicis EMG and anaesthesia maintained with 66% nitrous oxide in oxygen and alfentanil 50–100 mg kg-1 h-1.
    • infusione requirements of mivacurium Meretoja, O. A.; Olkkola, K. T.Pharmacodynamics of mivacvurium in children using a computer controlled infusion.BJA 1993:71 :
    • graph) and a 95%(lower graph) nmblockade. Meretoja, O. A.; Olkkola, K. T.Pharmacodynamics of mivacvurium in children using a computer controlled infusion.BJA 1993:71:
    • Meretoja, O. A.; Olkkola, K. T.Pharmacodynamics of mivacvurium in children using a computer controlled infusion.BJA 1993:71: During nitrous oxide in oxygen and alfentanil anaesthesia, children required an average of mivacurium 950 mg kg-1 h-1 (16 mg kg-1 min1) to maintain a 95% neuromuscular block. This rate is similar to that reported earlier for children during open control of mivacurium infusion . It seems, therefore, that use of a computer-
    • Meretoja, O. A.; Olkkola, K. T.Pharmacodynamics of mivacvurium in children using a computer controlled infusion.BJA 1993:71: MODEL-DRIVEN COMPUTERIZED INFUSION OF MIVACURIUM A two-compartment, open mammillary model with a hypothetical effect compartment linked to the central compartment was assumed to represent a valid model for the pharmacokinetics of mivacurium . The integrated pharmacokinetic and pharmacodynamic model we used consists of two formulae (both given as a function of time, t), one representing the relationship between the function for drug input, I(t), and the concentration of the drug in the effect compartment, Ce(t): and one representing the relationship between concentration Ce(t) and effect E(t) : The function G(t) is given by the effect compartment concentration
    • Meretoja OA, Brown TCK. Maintenance requirement of alcuronium in paediatric patients. Anaesthesia and Intensive Care 1990; 18:452-454. 15: Meretoja OA, Luosto T. Doseresponse characteristics of pancuronium in neonates, infants and children. Anaesthesia and
    • Olkkola, K. T.; Tammisto, T. KLAUS T. OLKKOLA, M.D., TAPANI TAMMISTO, M.D., Department of Anaesthesia, University of Helsinki, Haartmaninkatu 4, FIN–00290 Helsinki, Finland. Accepted for Publication: January 24, 1994.
    • AUTHOR(S): Meretoja, O. A.; Olkkola, K. T. OLLI A. MERETOJA, M.D., Department of Anaesthesia, Children's Hospital University of Helsinki, SF-00290 Helsinki, Finland. KLAUS T. OLKKOLA, M.D., Department of Anaesthesia,
    • Kansanaho M, Olkkola KT. Quantifying the effect of enflurane on atracurium infusion requirements. Can J Anaesth 1995; 42:103-8 Kansanaho et al. studied the influence of several doses of enflurane on the cumulative dose requirements of atracurium to maintain a constant 90% neuromuscular block; this study showed that enflurane decreased the atracurium requirements in a dose-dependant manner: 0.5 MAC of enflurane reduced the
    • FFECTIVE FEEDBACK CONTROL systems for the delivery of muscle relaxants in humans have been introduced over the past few years. Methods for control have included on-off, proportional infusion, state estimation, and proportional-integral-derivative (PID). A feedback controller uses the error signal to calculate the correct infusion rate of a drug for maintaining the response at or near the chosen setpoint. The error signal is the difference between the setpoint and the desired response. Closed-loop controllers require a specific monitor of the desired response, which “feed back” to regulate the controlling agent. For muscle relaxant control, the measured response usually is the electromyogram (EMG). A PID controller takes three components of the measured response to increase the
    • 2: 3: Rametti LB, Bradlow HS, Uys PC: Online parameter estimation and control of dtubocurarine-induced muscle relaxation. Med Biol Eng Comput 23:556-564, 1985 4: Bradlow HS, Uys PC, Rametti LB: On-line control of atracurium
    • control of neuromuscular blockade. Anaesthesia 41:316-320, 1986
    • Shanks CA, Avram MJ, Fragen RJ, O'Hara DA: Pharmacokinetics and pharmacodynamics of vecuronium infusion administered by bolus and infusion during halothane or balanced anesthesia. Clin Pharmacol Ther 42:459-464, 1987 19: Jaklitsch RR, Westenskow DR, Pace NL, Streisand JB, East KA: A
    • 1: d'Hollander AA, Hennart DA, Barvais L, Baurin M. Administration of atracurium by infusion for long surgical procedures. Simple techniques for routine use. Br J Anaesth 1986; 58 (suppl 1):56S–59S. 2: Eager BM, Flynn PJ, Hughes R. Iufusion of atracurium for long surgical procedures. Br J Anaesth 1984; 56:44752. 3: Gramstad L, Lilleasen P. Neuromuscular blocking effects of
    • 15. Ebeling BJ, Muller W, Tonner P, Olkkola KT, Stoekel H. Adaptative feedback-controlled infusion versus repetitive injections of vecuronium in patients during isoflurane anesthesia. Journal of Clinical Anesthesia 1991; 3: 181-5. 16. Schwilden H, Olkkola KT. Use of a pharmacokineticdynamic model for the automatic feedback control of atracurium. Eur J Clin Pharmacol. 1991; 40: 293-6. 17. 18. Kansanaho M, Hynynen M, Olkkola KT. Model-driven closed-loop feedback infusion of atracurium and vecuronium during hypothermic cardiopulmonary bypass. J Cardiothorac Vasc Anesth 1997; 11: 58-61. 21. Olkkola KT, Kansanaho M. Quantifying the interaction of vecuronium with enflurane using closed- loop feedback control of vecuronium infusion. Acta Anaesthesiol Scand. 1995; 39: 489-93.
    • anesthesia.Anesthesiology 1992:77 vol 3... O'Hara, Dorene A., M.D. M.S.E.*; Bogen, Daniel K., M.D. Ph.D.†; Noordergraaf, Abraham, Ph.D.‡ I. Introduction II. Background on Control Theory A. Basic control system components and terminology B. Types of control systems 1. Open-loop
    • For muscle relaxant control, the measured response usually is the electromyogram (EMG). A PID controller takes three components of the measured response to increase the speed and accuracy of control: the error signal itself (proportional component), a summation of the area between the EMG response curve and the EMG
    • 1: Beemer GH. Continuous infusion of muscle relaxants—why and how. Anaesthesia and Intensive Care 1987; 15:83-89. 2: Bradlow HS, Uys PC, Rametti LB. On-line control of atracurium induced muscle relaxation. Journal of Biomedical Engineering 1986; 8:72-75. 3: Webster NR, Cohen AT. Closed-loop administration of atracurium: steadystate neuromuscular blockade during surgery using a computer controlled