Jan F. A. Hendrickx

Is synergy the rule? A review of anesthetic interactions producing hypnosis and immobility.

BACKGROUND: Drug interactions may reveal mechanisms of drug action: additive interactions suggest a common site of action, and synergistic interactions suggest different sites of action. We applied this reasoning in a review of published data on anesthetic drug interactions for the end-points of hypnosis and immobility. METHODS: We searched Medline for all manuscripts listing propofol, etomidate, methohexital, thiopental, midazolam, diazepam, ketamine, dexmedetomidine, clonidine, morphine, fentanyl, sufentanil, alfentanil, remifentanil, droperidol, metoclopramide, lidocaine, halothane, enflurane, isoflurane, sevoflurane, desflurane, N2O, and Xe that contained terms suggesting interaction: interaction, additive, additivity, synergy, synergism, synergistic, antagonism, antagonistic, isobologram, or isobolographic. When available, data were reanalyzed using fraction analysis or response surface analysis. RESULTS: Between drug classes, most interactions were synergistic. The major exception was ketamine, which typically interacted in either an additive or infra-additive (antagonistic) manner. Inhaled anesthetics typically showed synergy with IV anesthetics, but were additive or, in the case of nitrous oxide and isoflurane, possibly infra-additive, with each other. CONCLUSIONS: Except for ketamine, IV anesthetics acting at different sites usually demonstrated synergy. Inhaled anesthetics usually demonstrated synergy with IV anesthetics, but no pair of inhaled anesthetics interacted synergistically.

Absorption, Metabolism, and Excretion of Paliperidone, a New Monoaminergic Antagonist, in Humans

Absorption, metabolism, and excretion of paliperidone, an atypical antipsychotic, was studied in five healthy male subjects after a single dose of 1 mg of [14C]paliperidone oral solution (∼16 μCi/subject). One week after dosing, 88.4 to 93.8% (mean 91.1%) of the administered radioactivity was excreted: 77.1 to 87.1% (mean 79.6%) in urine and 6.8 to 14.4% (mean 11.4%) in the feces. Paliperidone was the major circulating compound (97% of the area under the plasma concentration-time curve at 24 h). No metabolites could be detected in plasma. Renal excretion was the major route of elimination with 59% of the dose excreted unchanged in urine. About half of the renal excretion occurred by active secretion. Unchanged drug was not detected in feces. Four metabolic pathways were identified as being involved in the elimination of paliperidone, each of which accounted for up to a maximum of 6.5% of the biotransformation of the total dose. Biotransformation of the drug occurred through oxidative N-dealkylation (formation of the acid metabolite M1), monohydroxylation of the alicyclic ring (M9), alcohol dehydrogenation (formation of the ketone metabolite M12), and benzisoxazole scission (formation of M11), the latter in combination with glucuronidation (M16) or alicyclic hydroxylation (M10). Unchanged drug, M1, M9, M12, and M16 were detected in urine; M10 and M11 were detected in feces. The monohydroxylated metabolite M9 was solely present in urine samples of extensive CYP2D6 metabolizers, whereas M10, another metabolite monohydroxylated at the alicyclic ring system, was present in feces of poor metabolizers as well. In conclusion, paliperidone is not metabolized extensively and is primarily renally excreted.

Alfentanil pharmacokinetics and metabolism in humans

The metabolism of alfentanil was studied in three healthy subjects after a 1-h infusion of 2.5 mg alfentanil-3H. One of the subjects was a poor hydroxylator of debrisoquinc. Pharmacokinetic parameters were similar in the three subjects and were in the same range as those reported for volunteers. The majority of the administered radioactivity was excreted in the urine (90% of the dose), but unchanged alfentanil represented only 0.16–0.47% of the dose. Alfentanil and metabolites were characterized by HPLC co-chromatography with reference compounds and/or by mass spectrometry and quantified by GLC and radio-HPLC. The main metabolic pathway was N-dealkylation at the piperidine nitrogen, with formation of noralfentanil (30% of the dose). Other Phase I pathways were aromatic hydroxylation, N-dealkylation of the piperidinc ring from the phenylpropanamide nitrogen, O-demelhylation, and amide hydrolysis followed by N-acetylatton. Glucuronic acid conjugation of aromatic or aliphatic hydroxyl functions was the main Phase II pathway. The second major metabolite was the glucuronide of N-(4-hydroxyphenyl) propanamide (14% of the dose). The metabolite pattern in these subjects was qualitatively very similar to that described previously in rats and dogs. Differences in the mass balance of urinary metabolites between the three subjects were very small, and there was no qualitative or quantitative evidence for a deficiency in the metabolism of alfentanil in the subject who was a poor metabolizer of debrisoquine.

Additivity Versus Synergy: A Theoretical Analysis of Implications for Anesthetic Mechanisms

BACKGROUND: Inhaled anesthetics have been postulated to act at multiple receptors, with modest action at each site summing to produce immobility to noxious stimulation. Recent experimental results affirm prior findings that inhaled anesthetics interact additively. Synergy implies multiple sites of action by definition. In this essay, we explore the converse: does additivity imply a single site of action? METHODS: The interaction of one versus two ligands competing for the same binding site at a receptor was explored using the law of mass action. Circuits were then constructed to investigate how the potency of drugs and the steepness of the concentration versus response relationship is amplified by the arrangement of suppressors into serial circuits, and enhancers into parallel circuits. Assemblies of suppressor and enhancer circuits into signal processing units were then explored to investigate the constraints signal processing units impose on additive interactions. Lastly, the relationship between synergy, additivity, and fractional receptor occupancy was explored to understand the constraints imposed by additivity. RESULTS: Drugs that compete for a single receptor, and that similarly affect the receptor, must be additive in their effects. Receptors that bind suppressors in serial circuits, or enhancers in parallel circuits, increase the apparent potency of the drugs and the steepness of the concentration versus response relationship. When assemblies of suppressor and enhancer circuits are arranged into signal processing units, the interactions may be additive or synergistic. The primary determinant is the relationship between the concentration of drug associated with the effect of interest and the concentration associated with 50% receptor occupancy, kd. Effects mediated by very low concentrations are more likely to be additive. Similarly, inhaled anesthetics that act at separate sites are unlikely to exhibit additive interactions if anesthetic drug effect occurs at concentrations at or above 50% receptor occupancy. However, if anesthetic drug effect occurs at very low levels of receptor occupancy, then additivity is expected even among anesthetics acting on different receptors. CONCLUSIONS: Additivity among drugs acting on different receptors is only likely if the concentrations responsible for the drug effect of interest are well below the concentration associated with 50% receptor occupancy.

Inhaled Anesthetics Do Not Combine to Produce Synergistic Effects Regarding Minimum Alveolar Anesthetic Concentration in Rats

BACKGROUND: We hypothesized that pairs of inhaled anesthetics having divergent potencies [one acting weakly at minimum alveolar anesthetic concentration (MAC); one acting strongly at MAC] on specific receptors/channels might act synergistically, and that such deviations from additivity would support the notion that anesthetics act on multiple sites to produce anesthesia. METHODS: Accordingly, we studied the additivity of MAC for 11 anesthetic pairs divergently (one weakly, one strongly) affecting a specific receptor/channel at MAC. By “divergently,” we usually meant that at MAC the more strongly acting anesthetic enhanced or blocked the in vitro receptor or channel at least twice (and usually more) as much as did the weakly acting anesthetic. The receptors/channels included: TREK-1 and TASK-3 potassium channels; and &ggr;-aminobutyric acid type A, glycine, N-methyl-d-aspartic acid, and acetylcholine receptors. We also studied the additivity of cyclopropane-benzene because the N-methyl-d-aspartic acid blocker MK-801 had divergent effects on the MACs of these anesthetics. We also studied four pairs that included nitrous oxide because nitrous oxide had been reported to produce infraadditivity (antagonism) when combined with isoflurane. RESULTS: All combinations produced a result within 10% of that which would be predicted by additivity except for the combination of isoflurane with nitrous oxide where infraadditivity was found. CONCLUSIONS: Such results are consistent with the notion that inhaled anesthetics act on a single site to produce immobility in the face of noxious stimulation.

Cerebral haemodynamic physiology during steep Trendelenburg position and CO2 pneumoperitoneum

BACKGROUND The steep (40°) Trendelenburg position optimizes surgical exposure during robotic prostatectomy. The goal of the current study was to elucidate the influence of this patient positioning on cerebral blood flow and zero flow pressure (ZFP), and to assess the validity of different methods of evaluating ZFP. METHODS In 21 consecutive patients who underwent robotic endoscopic radical prostatectomy under general anaesthesia, transcranial Doppler flow velocity waveforms and invasive arterial and central venous pressure (CVP) waveforms suitable for analysis were recorded throughout the whole operative procedure in 14. The ZFP was determined by regression analysis of the pressure-flow plot and by different simplified formulas. The effective cerebral perfusion pressure (eCPP), pulsatility index (PI), and resistance index (RI) were determined. RESULTS While patients were in the Trendelenburg position, the ZFP increased in parallel with the CVP. The PI, RI, gradient between the ZFP and CVP, and the gradient between the CPP and the eCPP did not increase significantly (P<0.05) after 3 h of the steep Trendelenburg position. Using the formula described by Czosnyka and colleagues, the ZFP correlated closely with that calculated by linear regression throughout the course of the operation. CONCLUSIONS Prolonged steep Trendelenburg positioning and CO(2) pneumoperitoneum does not compromise cerebral perfusion. ZFP and eCPP are reliable variables for assessing brain perfusion during prolonged steep Trendelenburg positioning.

Desflurane consumption during automated closed-circuit delivery is higher than when a conventional anesthesia machine is used with a simple vaporizer-O2-N2O fresh gas flow sequence

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

Maintaining sevoflurane anesthesia during low-flow anesthesia using a single vaporizer setting change after overpressure induction.

STUDY OBJECTIVE A sevoflurane vaporizer dial setting of 1.9% was previously found to maintain the end-expired sevoflurane concentration (Et(sevo)) at 1.3% during maintenance of anesthesia for procedures up to one hour with an O(2) FGF of 1 L/min. We examined whether applying these parameters could simplify low-flow sevoflurane anesthesia after overpressure induction using two slightly different techniques. DESIGN Prospective clinical study. SETTING Large teaching hospital. PATIENTS Sixteen patients receiving general anesthesia for a variety of peripheral procedures. INTERVENTIONS Anesthesia was induced with overpressure with sevoflurane (8%) in an 8 L. min(-1) O(2)/N(2)O mixture (30%/70%). After a laryngeal mask airway (LMA) was placed, fresh gas flow (FGF) was lowered to 1 L. min(-1) using O(2) and N(2)O (FiO(2) 30%) with patients breathing spontaneously. In group I patients (n = 8), the vaporizer dial was set at 1.9% at the same time the FGF was lowered. In group II patients (n = 8), the vaporizer was turned off until Et(sevo) had decreased to 1.3%, after which the dial was set at 1.9%. The course of Et(sevo) in the two groups was examined. MEASUREMENTS AND MAIN RESULTS In group I, Et(sevo) after 3 min was 4.88 +/- 1. 12%. Et(sevo) decreased slowly after reduction of FGF to 1.83 +/- 0. 19%, 1.59 +/- 0.18%, and 1.52 +/- 0.19% at 10, 20, and 30 min, respectively. In group II, Et(sevo) after 3 min was 4.34 +/- 0.84%, and decreased more rapidly after reduction of FGF to 1 L. min(-1) than in group I. Et(sevo) was 1.40 +/- 0.09%, 1.40 +/- 0.11%, and 1. 38 +/- 0.13% at 10, 20, and 30 min, respectively. CONCLUSIONS After high-flow overpressure induction with sevoflurane, a single change in vaporizer setting (to 1.9%) and FGF (to 1 L. min(-1)) suffices for the Et(sevo) to approach the predicted Et(sevo) (1.3%) within 10-15 min; thereafter the Et(sevo) remains nearly constant. As expected, the predicted Et(sevo) is attained slightly faster when the vaporizer is temporarily turned off. Clinically applying previously derived pharmacokinetic parameters simplifies low-flow sevoflurane anesthesia after overpressure induction.

Metabolism and Excretion of RWJ-333369 (1,2-Ethanediol, 1-(2-Chlorophenyl)-, 2-carbamate, (S)-) in Mice, Rats, Rabbits, and Dogs

The in vivo metabolism and excretion of RWJ-333369 [1,2-ethanediol, 1-(2-chlorophenyl)-, 2-carbamate, (S)-], a novel neuromodulator, were investigated in mice, rats, rabbits, and dogs after oral administration of 14C-RWJ-333369. Plasma, urine, and feces samples were collected, assayed for radioactivity, and profiled for metabolites. In almost all species, the administered radioactive dose was predominantly excreted in urine (>85%) with less than 10% in feces. Excretion of radioactivity was rapid and nearly complete at 96 h after dosing in all species. Unchanged drug excreted in urine was minimal (<2.3% of the administered dose) in all species. The primary metabolic pathways were O-glucuronidation (rabbit > mouse > dog > rat) of RWJ-333369 and hydrolysis of the carbamate ester followed by oxidation to 2-chloromandelic acid. The latter metabolite was subsequently metabolized in parallel to 2-chlorophenylglycine and 2-chlorobenzoic acid (combined hydrolytic and oxidative pathways: rat > dog > mouse > rabbit). Other metabolic pathways present in all species included chiral inversion in combination with O-glucuronidation and sulfate conjugation (directly and/or following hydroxylation of RWJ-333369). Species-specific pathways, including N-acetylation of 2-chlorophenylglycine (mice, rats, and dogs) and arene oxidation followed by glutathione conjugation of RWJ-333369 (mice and rats), were more predominant in rodents than in other species. Consistent with human metabolism, multiple metabolic pathways and renal excretion were mainly involved in the elimination of RWJ-333369 and its metabolites in animal species. Unchanged drug was the major plasma circulating drug-related substance in the preclinical species and humans.

Do distribution volumes and clearances relate to tissue volumes and blood flows? A computer simulation.

BackgroundKinetics of inhaled agents are often described by physiological models. However, many pharmacokinetic concepts, such as context-sensitive half-times, have been developed for drugs described by classical compartmental models. We derived classical compartmental models that describe the course of the alveolar concentrations (FA) generated by the physiological uptake and distribution models used by the Gas Man® program, and describe how distribution volumes and clearances relate to tissue volumes and blood flows.MethodsGas Man® was used to generate FA vs. time curves during the wash-in and wash-out period of 115 min each with a high fresh gas flow (8 L.min-1), a constant alveolar minute ventilation (4 L.min-1), and a constant inspired concentration (FI) of halothane (0.75%), isoflurane (1.15%), sevoflurane (2%), or desflurane (6%). With each of these FI, simulations were ran for a 70 kg patient with 5 different cardiac outputs (CO) (2, 3, 5, 8 and 10 L.min-1) and for 5 patients with different weights (40, 55, 70, 85, and 100 kg) but the same CO (5 L.min-1). Two and three compartmental models were fitted to FA of the individual 9 runs using NONMEM. After testing for parsimony, goodness of fit was evaluated using median prediction error (MDPE) and median absolute prediction error (MDAPE). The model was tested prospectively for a virtual 62 kg patient with a cardiac output of 4.5 L.min-1 for three different durations (wash-in and wash-out period of 10, 60, and 180 min each) with an FI of 1.5% halothane, 1.5% isoflurane, sevoflurane 4%, or desflurane 12%.ResultsA three-compartment model fitted the data best (MDPE = 0% and MDAPE ≤ 0.074%) and performed equally well when tested prospectively (MDPE ≤ 0.51% and MDAPE ≤ 1.51%). The relationship between CO and body weight and the distribution volumes and clearances is complex.ConclusionThe kinetics of anesthetic gases can be adequately described e by a mammilary compartmental model. Therefore, concepts that are traditionally thought of as being applicable to the kinetics of intravenous agents can be equally well applied to anesthetic gases. Distribution volumes and clearances cannot be equated to tissue volumes and blood flows respectively.