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Medication error is a well-recognised cause of harm to patients undergoing anaesthesia. From the first 4000 reports in the webAIRS anaesthetic incident reporting system, we identified 462 reports of medication errors. These reports were reviewed iteratively by several reviewers paying particular attention to their narratives. The commonest error category was incorrect dose (29.4%), followed by substitution (28.1%), incorrect route (7.6%), omission (6.5%), inappropriate choice (5.8%), repetition (5.4%), insertion (4.1%), wrong timing (3.5%), wrong patient (1.5%), wrong side (1.5%) and others (6.5%). Most (58.9%) of the errors resulted in at least some harm (20.8% mild, 31.0% moderate and 7.1% severe). Contributing factors to the medication errors included the presence of look-alike medications, storage of medications in the incorrect compartment, inadequate labelling of medications, pressure of time, anaesthetist fatigue, unfamiliarity with the medication, distraction, involvement of multiple people and poor communication. These data add to current evidence suggesting a persistent and concerning failure effectively to address medication safety in anaesthesia. The wide variation in the nature of the errors and contributing factors underline the need for increased systematic and multifaceted efforts underpinned by a strengthening of the current focus on safety culture to improve medication safety in anaesthesia. This will require the concerted and committed engagement of all concerned, from practitioners at the clinical workface, to those who fund and manage healthcare.

BACKGROUND Oxycodone pharmacokinetics have been described in premature neonates through to obese adults. Covariate influences have been accounted for using allometry (size) and maturation of oxycodone clearance with age. The target concentration is dependent on pain intensity that may differ over pain duration or between individuals. METHODS We assumed a target concentration of 35 mcg.L-1 (acceptable range ±20%) to be associated with adequate analgesia without increased risk of adverse effects from respiratory depression. Pharmacokinetic simulation was used to estimate dose in neonates through to obese adults given intravenous or parenteral oxycodone. RESULTS There were 84% of simulated oxycodone concentrations within the acceptable range during maintenance dosing. Variability around the simulated target concentration decreased with age. The maturation of oxycodone clearance is reflected in changes to context-sensitive halftime where clearance is immature in neonates compared with older children and adults. The intravenous loading and maintenance doses for a typical 5-year-old child are 100 mcg.kg-1 and 33 mcg.kg-1 .h-1 . In a typical adult, the loading dose is 100 mcg.kg-1 and maintenance dose 23 mcg.kg-1 .h-1 . CONCLUSION Simulation was used to suggest loading and maintenance doses to attain an oxycodone concentration of 35 mcg.L-1 predicted in adults. Although the covariates age and weight contribute 92% variability for clearance, there remains variability accounting for 16% of concentrations outside the target range. Duration of analgesic effect after ceasing infusion is anticipated to be longer in neonates where context-sensitive halftime is greater than older children and adults.

Hysteresis is reported between plasma concentration and analgesic effect from nonsteroidal anti-inflammatory drugs. It is possible that the temporal delay between plasma and CSF nonsteroidal anti-inflammatory drugs mirrors this hysteresis. The temporal relationship between plasma and CSF concentrations of COX-inhibitors (celecoxib, rofecoxib, valdecoxib) has been described. The purpose of this secondary data analysis was to develop a compartmental model for plasma and CSF disposition of these COX-2 inhibitors.Plasma and CSF concentration-time profiles and protein binding data in 10 adult volunteers given oral celecoxib 200 mg, valdecoxib 40 mg and rofecoxib 50 mg were available for study. Nonlinear mixed effects models with a single plasma compartment were used to link a single CSF compartment with a transfer factor and an equilibration rate constant (Keq). To enable predictive modeling in pediatrics, celecoxib pharmacokinetics were standardized using allometry.Movement of all three unbound plasma COX-2 drugs into CSF was characterized by a common equilibration half-time (TTransfer of unbound COX-2 inhibitors from plasma to CSF compartment can be described with a delayed effect model using an equilibration rate constant to collapse observed hysteresis. An additional transfer factor was required to account for passage across the blood-brain barrier. Use of a target concentration strategy for dose and consequent plasma (total and unbound) and CSF concentration prediction could be used to inform pediatric clinical studies.

Background Oxycodone is used in children and adults for the control of acute postoperative pain. Covariate influences such as age, size, and fat mass on oxycodone pharmacokinetic parameters over the human lifespan are poorly quantified. Methods Pooled oxycodone time-concentration profiles were available from preterm neonates to adults. Data from intravenous, intramuscular, buccal, and epidural formulations were analyzed using nonlinear mixed-effects models. Normal fat mass was used to determine the influence of fat on oxycodone pharmacokinetics. Theory-based allometry was used to scale pharmacokinetic parameters to a 70 kg individual. A maturation function described the increase in clearance in neonates and infants. Results There were 237 subjects (24 weeks postmenstrual age to 75 years; 0.44-110 kg) providing 1317 plasma concentrations. A three-compartment model with first-order elimination best described oxycodone disposition. Population parameter estimates were clearance (CL) 48.6 L.h-1 .70 kg-1 (CV 71%); intercompartmental clearances (Q2) 220 L.h-1 .70 kg-1 (CV 64%); Q3 1.45 L.h-1 .70 kg-1 ; volume of distribution in the central compartment (V1) 98.2 L.70 kg-1 (CV 76%); rapidly equilibrating peripheral compartment (V2) 90.1 L. 70 kg-1 (CV 76%); slow equilibrating peripheral compartment (V3) 28.9 L.70 kg-1 . Total body weight was the best size descriptor for clearances and volumes. Absorption halftimes (TABS ) were: 1.1 minutes for intramuscular, 70 minutes for epidural, 82 minutes for nasogastric, and 159.6 minutes for buccal administration routes. The relative bioavailability after nasogastric administration was 0.673 with a lag time of 8.7 minutes. Conclusions Clearance matured with age; 8% of the typical adult value at 24 weeks postmenstrual age, 33% in a term neonate and reached 90% of the adult clearance value by the end of the first year of life. Allometric scaling using total body weight was the better size descriptor of oxycodone clearance than fat-free mass.

Background Etomidate is frequently selected over propofol for induction of anaesthesia because of a putatively favourable haemodynamic profile, but data confirming this perception are limited. Methods Patients undergoing cardiac surgery were randomised to induction of anaesthesia with propofol or etomidate. Phase I (n=75) was conducted as open-label, whereas Phase II (n=75) was double blind. Mean arterial blood pressure (MAP) and boluses of vasopressor administered after induction were recorded. The primary endpoint was the area under the curve below baseline MAP (MAP-time integral) during the 10 min after induction. Secondary endpoints were the use of vasopressors over the same period, and the effect of blinding on the aforementioned endpoints. Groups were compared using regression models with phase and anaesthetist as factors. Results The mean difference between etomidate and propofol in the MAP-time integral below baseline was 2244 mm Hg s (95% confidence interval, 581–3906; P=0.009), representing a 34% greater reduction with propofol. Overall, vasopressors were used in 10/75 patients in the etomidate group vs 21/75 in the propofol group (P=0.38), and in 20/74 patients during the blinded phase vs 11/76 during the open-label phase (P=0.31). The interaction between randomisation and phase (open-labelled or blinded) was not significant for either primary (P=0.73) or secondary endpoints (P=0.90). Conclusions Propofol caused a 34% greater reduction in MAP-time integral from baseline after induction of anaesthesia than etomidate, despite more frequent use of vasopressors with propofol, confirming the superior haemodynamic profile of etomidate in this context. The proportion of patients receiving vasopressors increased slightly, albeit not significantly, in both groups in the blinded phase. Clinical trial registration Australian and New Zealand Clinical Trials Registry, ACTRN12614000717651.

We implemented the World Health Organization surgical safety checklist at Auckland City Hospital from November 2007. We hypothesised that the checklist would reduce postoperative mortality and increase days alive and out of hospital, both measured to 90 postoperative days. We compared outcomes for cohorts who had surgery during 18-month periods before vs. after checklist implementation. We also analysed outcomes during 9 years that included these periods (July 2004-December 2013). We analysed 9475 patients in the 18-month period before the checklist and 10,589 afterwards. We analysed 57,577 patients who had surgery from 2004 to 2013. Mean number of days alive and out of hospital (95%CI) in the cohort after checklist implementation was 1.0 (0.4-1.6) days longer than in the cohort preceding implementation, p

Postoperative wound infections represent an important source of morbidity and mortality in children. Perioperative antibiotic prophylaxis has been shown to decrease the risk of developing infections and hospital guidelines surrounding antibiotic use exist to standardize patient care. Despite supporting evidence, rates of compliance with guidelines vary. Quality improvement initiatives have been introduced to improve compliance with intraoperative antibiotic guidelines. Thorough infection surveillance, including antibiotic provision in presurgical checklists, computerized voice antibiotic administration prompts, and national feedback systems are now increasingly common. Few studies have been conducted investigating the effectiveness of prophylactic antibiotics in children. Outcome measures such as morbidity and mortality and return to the operating room can be used to examine the relationship between antibiotic use and patient outcome but these measures are limited in that they occur infrequently or are subjective and difficult to measure. Metrics such as days alive out of hospital and length of hospital stay may be useful alternatives for ongoing monitoring of infections and identifying improvements in patient outcomes. Guidelines on antibiotic prophylaxis have facilitated an increase in the correct provision of perioperative antibiotics and a reduction in the incidence of postoperative infection. Measures of patient outcome such as days alive out of hospital and length of hospital stay are easy to collect and calculate but further work is needed to confirm the utility of these measures for monitoring infection rates.

The aim of this study was to analyse the incidents related to awareness during general anaesthesia in the first 4,000 cases reported to webAIRS—an anaesthetic incident reporting system established in Australia and New Zealand in 2009. Included incidents were those in which the reporter selected “neurological” as the main category and “awareness/dreaming/ nightmares” as a subcategory, those where the narrative report included the word “awareness” and those identified by the authors as possibly relevant to awareness. Sixty-one awareness-related incidents were analysed: 16 were classified as “awareness”, 31 were classified as “no awareness but increased risk of awareness” and 14 were classified as “no awareness and no increased risk of awareness”. Among 47 incidents in the former two categories, 42 (89%) were associated with low anaesthetic delivery and 24 (51%) were associated with signs of intraoperative wakefulness. Memory of intraoperative events caused significant ongoing distress for five of the 16 awareness patients. Patients continue to be put at risk of awareness by a range of well-described errors (such as syringe swaps) but also by some new errors related to recently introduced anaesthetic equipment, such as electronic anaesthesia workstations.

Background Simulation has been used to investigate clinical questions in anesthesia, surgery, and related disciplines, but there are few data demonstrating that results apply to clinical settings. We asked “would results of a simulation-based study justify the same principal conclusions as those of a larger clinical study?” Methods We compared results from a randomized controlled trial in a simulated environment involving 80 cases at three centers with those from a randomized controlled trial in a clinical environment involving 1,075 cases. In both studies, we compared conventional methods of anesthetic management with the use of a multimodal system (SAFERsleep®; Safer Sleep LLC, Nashville, Tennessee) designed to reduce drug administration errors. Forty anesthesiologists each managed two simulated scenarios randomized to conventional methods or the new system. We compared the rate of error in drug administration or recording for the new system versus conventional methods in this simulated randomized controlled trial with that in the clinical randomized controlled trial (primary endpoint). Six experts were asked to indicate a clinically relevant effect size. Results In this simulated randomized controlled trial, mean (95% CI) rates of error per 100 administrations for the new system versus conventional groups were 6.0 (3.8 to 8.3) versus 11.6 (9.3 to 13.8; P = 0.001) compared with 9.1 (6.9 to 11.4) versus 11.6 (9.3 to 13.9) in the clinical randomized controlled trial (P = 0.045). A 10 to 30% change was considered clinically relevant. The mean (95% CI) difference in effect size was 27.0% (−7.6 to 61.6%). Conclusions The results of our simulated randomized controlled trial justified the same primary conclusion as those of our larger clinical randomized controlled trial, but not a finding of equivalence in effect size.

Background Ibuprofen is widely used for ductus arteriosus closure in premature neonates and for analgesia in children and adults. There are no maturation descriptors of clearance. This lack of maturation understanding limits dosing recommendations from premature neonates to adulthood. Methods Published clearance estimates from different aged patients determined after administration from time-concentration profiles were used to construct a maturation model based on size and age. Curve fitting was performed using nonlinear mixed-effects models. A target concentration strategy was used to estimate maintenance dose at different ages. Results There were three publications reporting an estimate of individual clearance estimates in premature neonates, three reporting population clearances in infants, 11 in children 2-15 years (1 with individual and 9 with population clearances), and 13 adult studies (1 with individual and 12 with population clearances). Clearance maturation, standardized to a 70 kg person was described using the Hill equation. Mature clearance was 3.81 (CV 15.5%, 95%CI 3.72, 3.92) L/h/70 kg. The maturation half-time was 36.8 (CV 9.2%, 95%CI 34.7, 40.9) weeks postmenstrual age and the Hill coefficient 11.5 (95%CI 8.1, 15). A target effect of four units (visual analogue scale 0-10) correlated with an effect site concentration of 6.3 mg/L: a concentration achieved at trough after 400 mg 8 hourly in adults. Conclusion Previously published pharmacokinetic parameters can be used to develop maturation models that address gaps in current knowledge regarding the influence of age on a drug's disposition. Maturation of ibuprofen clearance was rapid and was 90% of adult values by the first month of life in term neonates (ie, 44 weeks postmenstrual age) and 98% of standardized adult estimates by 3 months of age (53 weeks postmenstrual age). Clearance informed dosing predictions in all ages (premature neonate to adult) and matched those doses in common use in children older than 3 months.

Pharmacokinetic-pharmacodynamic (PKPD) population modelling has advanced adult anaesthesia. Current literature was reviewed to discern use of this analytic technique for benefit in the perioperative management of children.Variability in drug response, selection of a dose that achieves a desired target concentration and optimizing sampling protocols for further studies are all facets of paediatric anaesthesia that have benefitted from modelling approaches. PKPD models have driven the maintenance dose rate in target-controlled infusion pumps used for total intravenous anaesthesia. Although many of the models used in these pumps were developed in adults, translation for paediatric use has followed, including subgroups, such as neonates and obese children. The use of drug effect measures (e.g. bispectral index) has improved the predictive performance of pharmacodynamic models. Simulation studies have facilitated an increase in safety by quantifying drug variability, and identifying where possible adverse drug events may occur.Modelling and simulation continue to have an important role optimizing drug use during anaesthesia. Models incorporating influential covariates that better describe drug pharmacokinetics and pharmacodynamics improve anaesthetic treatments and safety in diverse populations and clarify drug role and impact. Their use developing paediatric clinical studies improves trial conduct, often with fewer subjects required for study.

Background Oral morphine has been proposed as an effective and safe alternative to codeine for after-discharge pain in children following surgery but there are few data guiding an optimum safe oral dose. Aims The aim of this study was to characterize the absorption pharmacokinetics of enteral morphine in order to simulate time–concentration profiles in children given common oral morphine dose regimens. Methods Children (2–6 years, n = 34) undergoing elective surgery and requiring opioid analgesia were randomized to receive preoperative oral morphine (100 mcg·kg−1, 200 mcg·kg−1, 300 mcg·kg−1). Blood sampling for morphine assay was performed at 30, 60, 90, 120, 180, and 240 min. Morphine serum concentrations were determined by liquid chromatography–mass spectroscopy and pharmacokinetic parameters were calculated using nonlinear mixed effects models. Current data were pooled with published time–concentration profiles from children (n = 1059, age 23 weeks postmenstrual age – 3 years) administered intravenous morphine, to determine oral bioavailability (F), absorption lag time (TLAG), and absorption half-time (TABS). These parameter estimates were used to predict concentrations in children given oral morphine (100, 200, 300, 400, 500 mcg·kg−1) at different dosing intervals (3, 4, 5, 6, 8, 12 h). Results The oral morphine formulation had F 0.298 (CV 36.5%), TLAG 0.45 (CV 63.6%) h and TABS 0.71 (CV 55%) h. A single-dose morphine 100 mcg·kg−1 achieved a mean CMAX 10 mcg·l−1. Repeat 4-hourly dosing achieved mean steady-state concentration 13–18 mcg·l−1; concentrations associated with good analgesia after intravenous administration. Serum concentration variability was large ranging from 5 to 55 mcg·l−1 at steady state. Conclusions Oral morphine 200 mcg·kg−1 then 100 mcg·kg−1 4 h or 150 mcg·kg−1 6 h achieves mean concentrations associated with analgesia. There was high serum concentration variability suggesting that respiration may be compromised in some children given these doses.

SummaryBackground Few pharmacokinetic (PK) and pharmacodynamic (PD) data exist for COX-2 selective inhibitors in children. We wished to characterize the PKPD of parecoxib and its active metabolite, valdecoxib, in this population. Methods Children (n = 59) were randomized to parecoxib 0.25 mg·kg−1, 1 mg·kg−1, and 2 mg·kg−1 during tonsillectomy ± adenoidectomy. Samples (4–6 per child) were obtained from indwelling cannula over 6 h. A second group of inpatient children (n = 15) given 1 mg·kg−1 contributed PK data from 6 to 24 h. Pain scores and rescue medication for the first group were recorded postoperatively for up to 24 h. PK data were pooled with those (10 samples/24 h) from a published study of children (n = 38) who underwent surgery. A three-compartment parent and one-compartment metabolite model with first-order elimination was used to describe data using nonlinear mixed effects models. An EMAX model described the relationship between dose and rescue morphine equivalents during recovery. Results Parecoxib PK parameter estimates were CLPARECOXIB 19.1 L·h−1·70 kg−1, V1PARECOXIB 4.2 L·70 kg−1, Q2PARECOXIB 6.29 L·h−1·70 kg−1, V2PARECOXIB 130 L·70 kg−1, Q3PARECOXIB 6.02 L·h−1·70 kg−1, and V3PARECOXIB 2.03 L·70 kg−1. We assumed all parecoxib was metabolized to valdecoxib with CLVALDECOXIB 9.53 L·h−1·70 kg−1 and VVALDECOXIB 51 L·70 kg−1. There was no maturation of clearance over the age span studied. There were no differences in pain scores between groups on waking, discharge, 12 h, or 24 h. There were no differences in analgesia consumption over 24 h between groups for tramadol, fentanyl, and morphine rescue use. Fentanyl and morphine consumption, expressed as morphine equivalents (0.13 mg·kg−1) in the 0.25 mg·kg−1 group, was greater than that observed in the 1 or 2 mg·kg−1 groups (0.095 mg·kg−1) in PACU. Conclusions Parecoxib 0.9 mg·kg−1 in a 2-year-old, 0.75 mg·kg−1 in a 7-year-old, and 0.65 mg·kg−1 in a 12-year-old child achieves dose equivalence of 40 mg in a standard 70 kg person. Clearance maturation may occur in infants younger than the current cohort. Parecoxib doses above 1 mg·kg−1 add no additional analgesia.

Appropriate hand hygiene reduces hospital-acquired infections. Anesthesiologists work in environments with numerous hand hygiene opportunities (HHOs). In a prospective observational study, we investigated the potential for an anesthesiologist to return a positive alcohol breath test during routine practice when using alcohol hand gel. We observed ten volunteer anesthesiologists over four hours while they implemented the World Health Organization (WHO) “five moments for hand hygiene” using our hospital’s adopted standard 70% ethanol hand gel. We measured the expired alcohol concentration at shift start and every fifteen minutes thereafter with a fuel cell breathalyzer calibrated to measure the percentage of blood alcohol concentration (BAC). Blood alcohol specimens (analyzed with gas chromatography) were collected at shift start and, when possible, immediately after a participant’s first positive breathalyzer test. Of the 130 breathalyzer tests obtained, there were eight (6.2%) positive breath alcohol results from six of the ten participants, all within two minutes of a HHO. The highest value breathalyzer BAC recorded was 0.064%, with an overall mean (SD) of 0.023 (0.017)%. Five (62.5%) of the positive breathalyzer tests returned to zero in less than seven minutes. All of three blood specimens obtained immediately after a positive breathalyzer reading tested negative for alcohol. Anesthesia practitioners using alcohol hand gel in a manner that conforms with recommended hand hygiene can test positive for alcohol on a breathalyzer assay. Positive tests probably arose from inhalation of alcohol vapour into the respiratory dead space following gel application. If workplace breath testing for alcohol is implemented, it should be completed more than 15 min after applying alcohol hand gel. Positive results should be verified with a BAC test.

AIMS: Manual propofol infusion regimens for neonates and infants have been determined from clinical observations in children under the age of 3 years undergoing anesthesia. We assessed the performance of these regimens using reported age-specific pharmacokinetic parameters for propofol. Where performance was poor, we propose alternative dosing regimens. METHODS: Simulations using a reported general purpose pharmacokinetic propofol model were used to predict propofol blood plasma concentrations during manual infusion regimens recommended for children 0-3 years. Simulated steady state concentrations were 6-8 µg.mL-1 in the first 30 minutes that were not sustained during 100 minutes infusions. Pooled clinical data (n = 161, 1902 plasma concentrations) were used to determine an alternative pharmacokinetic parameter set for propofol using nonlinear mixed effects models. A new manual infusion regimen for propofol that achieves a steady-state concentration of 3 µg.mL-1 was determined using a heuristic approach. RESULTS: A manual dosing regimen predicted to achieve steady-state plasma concentration of 3 µg.mL-1 comprised a loading dose of 2 mg.kg-1 followed by an infusion rate of 9 mg.kg-1 .h-1 for the first 15 minutes, 7 mg.kg-1 .h-1 from 15 to 30 minutes, 6 mg.kg-1 .h-1 from 30 to 60 minutes, 5 mg.kg-1 .h-1 from 1 to 2 hours in neonates (38-44 weeks postmenstrual age). Dose increased with age in those aged 1-2 years with a loading dose of 2.5 mg.kg-1 followed by an infusion rate of 13 mg.kg-1 .h-1 for the first 15 minutes, 12 mg.kg-1 .h-1 from 15 to 30 minutes, 11 mg.kg-1 .h-1 from 30 to 60 minutes, and 10 mg.kg-1 .h-1 from 1 to 2 hours. CONCLUSION: Propofol clearance increases throughout infancy to reach 92% that reported in adults (1.93 L.min.70 kg-1 ) by 6 months postnatal age and infusion regimens should reflect clearance maturation and be cognizant of adverse effects from concentrations greater than the target plasma concentration. Predicted concentrations using a published general purpose pharmacokinetic propofol model were similar to those determined using a new parameter set using richer neonatal and infant data. ispartof: PEDIATRIC ANESTHESIA vol:29 issue:9 pages:907-914 ispartof: location:France status: published

Background The impact of tramadol in children given acetaminophen-ibuprofen combination therapy is uncertain in acute pediatric pain management. A model describing the interaction between these three drugs would be useful to understand the role of supplemental analgesic therapy. Methods Children undergoing tonsillectomy were given oral paracetamol and ibuprofen perioperatively. Blood was taken for paracetamol and ibuprofen drug assay on up to six occasions over 6 h after the initial dose. Tramadol was administered by caregivers for unacceptable postoperative pain. Pain was measured using the Parent's Postoperative Pain Measurement rating two hourly on the first postoperative day. A first-order absorption, one-compartment linear model with first-order elimination was used to describe acetaminophen and ibuprofen disposition. Analgesia was described using an EMAX model extended for three drugs, assuming additive effects. Curve fitting was performed using nonlinear mixed effects models. Results Pharmacodynamic parameter estimates, expressed using fractional Hill equation, were maximum effect (EMAX ) 0.65 (95%CI 0.54, 0.74), the concentration of acetaminophen associated with 50% of the maximal drug effect (C50, ACET ) 7.06 (95%CI 7.03, 7.72) mg/L, and the ibuprofen C50 (C50, IBU ) 3.95 (95%CI 2.57, 7.53) mg/L. The Hill coefficient was 1.48 (95%CI 0.92, 2.62) and an interaction term was fixed at zero (additivity). The half-time (t1/2 keo) for equilibration between the plasma and effect site was 0.34 hour (95%CI 0.23, 1.98) for acetaminophen and 1.04 hour (95%CI 0.75, 1.77) for ibuprofen. Tramadol had a C50, TRAM of 0.07 (95%CI 0.048, 1.07) mg/L with a t1/2 keo,TRAM 1.78 hour (95%CI 1.06, 1.96). Conclusion Ibuprofen has an EC50 for analgesia in children similar to that of adults (3.95 mg/L; 95%CI 2.57-7.53, vs 5-10 mg/L adults). The maximum effect from combination therapy (ie, 65% reduction in pain score) achieves satisfactory analgesia with commonly used doses but increased dose adds little additional benefit. The addition of tramadol to this analgesic mixture prolongs analgesia duration.

Propofol and remifentanil are commonly combined for total IV anesthesia. The pharmacokinetics (PK), pharmacodynamics (PD), and drug interactions of the combination are well understood, but the use of a combined PK and PD model to control target-controlled infusion pumps has not been investigated. In this study, we prospectively tested the accuracy of a PD target-controlled infusion algorithm for propofol and remifentanil using a response surface model of their combined effects on Bispectral Index (BIS).Effect-site, target-controlled infusions of propofol and remifentanil were given using an algorithm based on standard PK models linked to a PD response surface model of their combined effects on BIS. The combination of a targeted BIS value and adjustable ratio of propofol to remifentanil was used to adjust infusion rates. The standard model performance measures of median performance error (bias) and median absolute performance error (inaccuracy), expressed as percentages, were used to assess accuracy of the infusions in a convenience sample of 50 adult patients undergoing surgery with general anesthesia. The influence of age and weight on the performance of the model was also assessed.Patients had a mean (range) age of 48 (19-73) years, weight of 80 (45-169) kg, and body mass index of 28 (19-45) kg/m. The overall model had a bias of 8% (SD 24%) and inaccuracy of 25% (SD 13%). Performance was least accurate during the early induction phase of anesthesia. There was no significant bias in BIS predictions with increasing age (P = 0.44) or weight (P = 0.56).The algorithm performed adequately in a clinical setting. The algorithm could be further refined, and assessment of its accuracy and utility in comparison to current clinical practice for giving IV anesthesia is warranted.

Background Diclofenac dosing in children for analgesia is currently extrapolated from adult data. Oral diclofenac 1.0 mg·kg(-1) is recommended for children aged 1-12 years. Analgesic effect from combination diclofenac/acetaminophen is unknown. Methods Children (n = 151) undergoing tonsillectomy (c. 1995) were randomized to receive acetaminophen elixir 40 mg·kg(-1) before surgery and 20 mg·kg(-1) rectally at the end of surgery with diclofenac suspension 0.1 mg·kg(-1) , 0.5 mg·kg(-1) , or 2.0 mg·kg(-1) before surgery or placebo. A further 93 children were randomized to receive diclofenac 0.1 mg·kg(-1) , 0.5 mg·kg(-1) , or 2.0 mg·kg(-1) only. Postoperative pain was assessed (visual analogue score, VAS 0-10) at half-hourly intervals from waking until discharge. Data were pooled with those from a further 222 children and 30 adults. One-compartment models with first-order absorption and elimination described the pharmacokinetics of both medicines. Combined drug effects were described using a modified EMAX model with an interaction term. An interval-censored model described the hazard of study dropout. Results Analgesia onset had an equilibration half-time of 0.496 h for acetaminophen and 0.23 h for diclofenac. The maximum effect (EMAX ) was 4.9. The concentration resulting in 50% of EMAX (C50 ) was 1.23 mg·l(-1) for diclofenac and 13.3 mg·l(-1) for acetaminophen. A peak placebo effect of 6.8 occurred at 4 h. Drug effects were additive. The hazard of dropping out was related to pain (hazard ratio of 1.35 per unit change in pain). Diclofenac 1.0 mg·kg(-1) with acetaminophen 15 mg·kg(-1) achieves equivalent analgesia to acetaminophen 30 mg·kg(-1) . Conclusions Combination therapy can be used to achieve similar analgesia with lower doses of both drugs.

Background Propofol mixed with racemic ketamine (or 'ketofol') is popular for short procedural sedation and analgesia. Use is creeping into anesthesia, yet neither the optimal combination nor infusion rate is known. The EC(50) of propofol's antiemetic effect is reported to be 0.343 mg·l(-1), while ketamine analgesia is thought to persist with concentrations above 0.2 mg·l(-1). We aimed to determine a ketofol dosing regimen for anesthesia 30-min and 1.5-h duration in a healthy child that did not unduly compromise recovery. Methods Pharmacokinetic-pharmacodynamic parameters were used to simulate drug concentration and effect profiles over time for different ratios of propofol to ketamine ratios (1 : 1 to 10 : 1) and rates. The target effect was the 95% probability of loss of response to a 5-s transcutaneous tetanus (P05). Combined effects were additive, with a propofol EC(50) of 3.1 mg·l(-1), ketamine EC(50) of 0.64 mg·l(-1), and slope of 5.4. The time to predicted 50% probability of return of this response after ceasing infusion (P(50)) was determined for a 5-year-old 20-kg healthy child. Results The addition of ketamine to propofol infused using a manual infusion regimen (loading dose 3 mg·kg(-1), then 15 mg·kg(-1) ·h(-1) for 15 min, 13 mg·kg(-1) ·h(-1) for 15 min, 11 mg·kg(-1) ·h(-1) for 30 min, and 10 mg·kg(-1) ·h(-1) for 1-2 h) caused prolonged postoperative sedation. The P(50) after a 1.5-h infusion using a 1 : 1 mixture was 4.5 h, 2 : 1 mixture was 3.25 h, 5 : 1 mixture was 1.6 h, and 10 : 1 mixture was 40 min. These P(50) estimates could be reduced by slowing administration infusion rates to 20%, 33%, 50%, 67%, 80%, and 90% for mixtures 1 : 1, 2 : 1, 3 : 1, 5 : 1, 6.7 : 1, and 10 : 1, respectively. These rates achieve a P(50) of approximately 20 min for 30-min duration anesthesia and 60 min for 1.5-h duration anesthesia. Conclusions The addition of ketamine to propofol infusion will prolong recovery unless infusion rates are decreased. We suggest an optimal ratio of racemic ketamine to propofol of 1 : 5 for 30-min anesthesia and 1 : 6.7 for 90-min anesthesia. Delivery of these ratios achieves propofol concentrations above an antiemetic threshold for longer than the ketamine concentration above the analgesic threshold during, potentially reducing postoperative nausea incidence.

A morphine plasma concentration/respiratory rate relationship has been described for both adults and children although that of its metabolite, morphine-6-glucuronide, remains uncertain. We describe this relationship in a child with end-stage renal failure who received repeat morphine administration over two days. An EMAX model for additive morphine and morphine-6-glucuronide respiratory effects described respiratory rate better than models describing either alone. Failure to clear morphine-6-glucuronide renally led to respiratory depression episodes occurring later than those predicted by modelling morphine levels only. These findings support the use of alternative analgesics (e.g. fentanyl) that are cleared by non-renal pathways and have no active metabolites in patients with end-stage renal disease.

Summary Background: The value of acetaminophen–ibuprofen combination therapy over single therapy is uncertain in acute pediatric pain management. A model describing the interaction between these two drugs would be useful both for understanding current literature and for future study design. Methods: Published pooled time–effect profiles in adults given combination or single therapy after dental extraction were used to construct an interaction model. Pain was measured using pain intensity differences (PRID, 0–10) from zero to eight hours postoperatively. Pharmacodynamic parameter estimates were assumed the same in adults as children. Pediatric pharmacokinetic estimates were scaled using allometric theory. Curve fitting was performed using nonlinear mixed effects models. Results: Pooled data were available in adults given eight single and multiple dose combinations as well as placebo. The ibuprofen dose range was 100–400 mg, and acetaminophen dose range was 500–1000 mg. Pharmacodynamic parameter estimates, expressed using the Hill equation, were maximum effect (EMAX) 4.06 (95% CI: 3.24, 5.51), the concentration of acetaminophen associated with 50% of the maximal drug effect (EC50,ACET) 11.9 (95% CI: 6.0, 49.5) mg·l−1, the ibuprofen EC50 (EC50,IBU) 5.07 (95% CI: 3.50, 8.26) mg·l−1, and Hill coefficient 2 (95% CI: 1.3, 2.8). An interaction term was fixed at zero (additive interaction). Simulation showed that the addition of acetaminophen to ibuprofen when less than 5 mg·kg−1 was effective; acetaminophen had minimal effect when given with ibuprofen at doses greater than 5 mg·kg−1 in the immediate postoperative period. A more sustained analgesic effect was noted at 4–8 h after combination dosing. Conclusions: This drug interaction modeling example is useful to explain combination therapy nuances and impacts on study design. Differences in effect between single drug therapy and combination therapy should be sought at lower doses and beyond the immediate postoperative period. Combination therapy may prolong the duration of analgesia. The maximum effect (EMAX) limits the early additional analgesic gain from combination therapy beyond commonly used doses.

We conducted a prospective observational study to assess the incidence of residual neuromuscular blockade (RNMB) in a post-anaesthetic care unit (PACU) of a tertiary hospital. The subjects were 102 patients undergoing general anaesthesia with neuromuscular blockade (NMB). The procedural anaesthetists were unaware of their patients’ inclusion in the study, and the choice of muscle relaxant and use of reversal agents were at the anaesthetists’ discretion. On arrival to the PACU, the train-of-four ratio was assessed using electromyography, repeated every five minutes until the train-of-four ratio exceeded 0.9. RNMB was defined as a train-of-four ratio < 0.9. The requirement for airway support, incidence of desaturation while in the PACU and time to eligibility for PACU discharge were recorded. The mean interval between the last dose of relaxant and arrival in the PACU for patients with RNMB was 81 minutes. An intermediate-acting muscle relaxant had been used for most patients. Despite this, RNMB was observed in 31% (95% confidence interval 25 to 47%) of patients. Our findings suggest that RNMB in the PACU is common. As RNMB may predispose to postoperative complications, anaesthetists should utilise quantitative monitoring to assess neuromuscular blockade and optimise reversal use. Anaesthetists should be aware that intervals between the last dose of relaxant of well over one hour do not exclude the possibility of RNMB, even when using intermediate-acting neuromuscular blockade agents.

Pharmacokinetic (PK) and pharmacodynamic (PD) models are important tools for summarizing drug dose, concentration, and effect relationships. Co-administration of drugs may alter PK and PD relationships. Traditional methods of evaluating PD interactions include using isoboles, shifts in dose-response curves, or interaction indices based on parameters of potency derived from separate monotherapy and combination therapy analyses. These methods provide an estimation of the magnitude of effect for dose or concentration combinations, but they do not inform us on the time course of that effect, or its associated variability. A better way to investigate PD interactions is to use modeling, and to take advantage of the benefits of population analyses. A population analysis is a statistical method in which a model describing the typical (or population) response, and the variability between individuals within that population, is developed. Models for monotherapy, derived using a population approach, can be combined and extended to incorporate PD interactions between two or more drugs. The purpose of this article was to provide a general road map for understanding and interpreting PD interaction models, including the 'response surface' models. Several types of response surface models exist, and here we review these with examples taken from the literature. We also consider current and future applications for this type of analysis for clinical anesthesia and pediatrics.

Background Bispectral index (BIS) monitoring is commonly used to decrease the risk of awareness during anaesthesia. We aimed to determine the relationship between blood alcohol concentration and brain function (as measured by BIS) in healthy adults. Methods In this prospective observational study, 21 anaesthetic registrars self-regulated alcohol consumption over a 3-h period. Expired alcohol concentration (breathalyser) and BIS measurements were performed hourly for 4 h. A venous blood alcohol sample was taken at the conclusion of the study period. Results The main outcome measures were the correlation between blood alcohol and brain function as measured by BIS and the change in BIS from baseline (∆BIS) at 4 h. The median number of standard drinks consumed was 9.1 (IQR 7.7–12.3), range 5.4–17. At 4 h, there was a moderate inverse correlation between BIS and blood alcohol (r = −0.49, P = 0.029) and between ∆BIS and blood alcohol (r = −0.46, P =0.043). Conclusion In healthy young adults, we found a moderate correlation between venous blood alcohol concentration and BIS. This suggests that acute alcohol consumption can decrease BIS. This information may be relevant when providing anaesthesia to intoxicated patients who require urgent or time-critical surgery, although certain limitations of this study should be kept in mind.

Anesthesia information management system (AIMS) technology is designed to facilitate high-quality anesthetic recordkeeping. We examined the hypothesis that no difference exists between AIMS and handwritten anesthetic records in regard to the completeness of important information contained as text data. We also investigated the effect of observational research on the completeness of anesthesiologists’ recordkeeping. As part of a larger randomized controlled trial, participants were randomized to produce 400 anesthetic records, either handwritten (n = 200) or using an AIMS (n = 200). Records were assessed against a 32-item checklist modified from a clinical guideline. Intravenous agent and bolus recordings were quantified, and data were compared between handwritten and AIMS records. Records produced with intensive research observation during the initial phase of the study (n = 200) were compared with records produced with reduced intensity observation during the final phase of the study (n = 200). The AIMS records were more complete than the handwritten records (mean difference 7.1%; 95% confidence interval [CI] 5.6 to 8.6%; P