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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.

Introduction: The target concentration strategy uses PKPD information for dose determination. Models have also quantified exposure-response relationships, improved understanding of developmental pharmacokinetics, rationalized dose prescription, provided insight into the importance of covariate information, explained drug interactions and driven decision-making and learning during drug development.Areas covered: The prime PKPD consideration is parameter estimation and quantification of variability. The main sources of variability in children are age (maturation) and weight (size). Model use is mostly confined to pharmacokinetics, partly because anesthesia effect models in the young are imprecise. Exploration of PK and PD covariates and their variability hold potential to better individualize treatment.Expert opinion: The ability to model drugs using computer-based technology is hindered because covariate data required to individualize treatment using these programs remain lacking. Target concentration intervention strategies remain incomplete because covariate information that might better predict individualization of dose is absent. Pharmacogenomics appear a valuable area for investigation for pharmacodynamics and pharmacodynamics. Effect measures in the very young are imprecise. Assessment of the analgesic component of anesthesia is crude. While neuromuscular monitoring is satisfactory, depth of anaesthesia EEG interpretation is inadequate. Closed loop anesthesia is possible with better understanding of EEG changes.

Background Consistent measurement and reporting of outcomes, including adequately defined complications, is important for the evaluation of surgical care and the appraisal of new surgical techniques. The range of complications reported after LC has not been evaluated. This study aimed to identify the range of complications currently reported for laparoscopic cholecystectomy (LC), and the adequacy of their definitions. Methods MEDLINE, EMBASE, and the Cochrane Central Register of Controlled Trials were searched for prospective studies reporting clinical outcomes of LC, between 2013 and 2016. Results In total 233 studies were included, reporting 967 complications, of which 204 (21%) were defined. One hundred and twenty-two studies (52%) did not provide definitions for any of the complications reported. Conversion to open cholecystectomy was the most commonly reported complication, reported in 135 (58%) studies, followed by bile leak in 89 (38%) and bile duct injury in 75 (32%). Mortality was reported in 89 studies (38%). Conclusion Considerable variation was identified between studies in the choice of measures used to evaluate the complications of LC, and in their definitions. A standardised set of core outcomes of LC should be developed for use in clinical trials and in evaluating the performance of surgical units.

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.

Background Postoperative infection is a serious problem in New Zealand and internationally with considerable human and financial costs. Also, in New Zealand, certain factors that contribute to postoperative infection are more common in Māori and Pacific populations. To date, most efforts to reduce postoperative infection have focussed on surgical aspects of care and on antibiotic prophylaxis, but recent research shows that anaesthesia providers may also have an impact on infection transmission. These providers sometimes exhibit imperfect hand hygiene and frequently transfer the blood or saliva of their patients to their work environment. In addition, intravenous medications may become contaminated whilst being drawn up and administered to patients. Working with relevant practitioners and other experts, we have developed an evidence-informed bundle to improve key aseptic practices by anaesthetists with the aim of reducing postoperative infection. The key elements of the bundle are the filtering of compatible drugs, context-relevant hand hygiene practices and enhanced maintenance of clean work surfaces. Methods We will seek support for implementation of the bundle from senior anaesthesia and hospital leadership and departmental “champions”. Anaesthetic teams and recovery room staff will be educated about the bundle and its potential benefits through presentations, written material and illustrative videos. We will implement the bundle in operating rooms where hip or knee arthroplasty or cardiac surgery procedures are undertaken in a five-site, stepped wedge, cluster randomised, quality improvement design. We will compare outcomes between approximately 5000 cases before and 5000 cases after implementation of our bundle. Outcome data will be collected from existing national and hospital databases. Our primary outcome will be days alive and out of hospital to 90 days, which is expected to reflect all serious postoperative infections. Our secondary outcome will be the rate of surgical site infection. Aseptic practice will be observed in sampled cases in each cluster before and after implementation of the bundle. Discussion If effective, our bundle may offer a practical clinical intervention to reduce postoperative infection and its associated substantial human and financial costs. Trial registration Australian New Zealand Clinical Trials Registry, ACTRN12618000407291. Registered on 21 March 2018. Electronic supplementary material The online version of this article (10.1186/s13063-019-3402-8) contains supplementary material, which is available to authorized users.

We read with interest the recent article by Suvikas-Peltonen et al 1 reviewing 26 studies of which 12 concerned incorrect practices that led to microbial contamination. Our study ‘Anaesthetic drug administration as a potential contributor to healthcare-associated infections: a prospective simulation-based evaluation of aseptic techniques in the administration of anaesthetic drugs’2 was one of the 12 reviewed articles. We would like to clarify …

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.

Appropriate management of post-operative pain is an ongoing challenge in surgical practice. At present, systemic opioid administration is routinely used for analgesia in the post-operative setting. However, due to significant adverse effects and potential for misuse, there is a perceived need for the development of alternative, opioid-sparing treatment modalities. Continuous infusion of local anesthetic into the peritoneum after major abdominal surgery reduces pain and opioid consumption, and enhances recovery from surgery. Here we describe a non-opioid, poly(ethylene-co-vinyl-acetate) intraperitoneal implant for the sustained delivery of local anesthetic following major abdominal surgery. A radio-opaque core had the required mechanical strength to facilitate placement and removal procedures. This core was enclosed by an outer shell containing an evenly dispersed local anesthetic, lidocaine. Sustained release of lidocaine was observed in an ovine model over days and the movement modelled between peritoneal fluid and circulating plasma. While desirably high levels of lidocaine were achieved in the peritoneal space these were several orders of magnitude higher than blood levels, which remained well below toxic levels. A pharmacokinetic model is presented that incorporates in vitro release data to describe lidocaine concentrations in both peritoneal and plasma compartments, predicting similar release to that suggested by lidocaine concentrations remaining in the device after 3 and 7 days in situ. Histological analysis revealed similar inflammatory responses following implantation of the co-extruded implant and a commercially used silicone drain after three days. This non-opioid analgesic implant provides sustained release of lidocaine in an ovine model and is suitable for moving onto first in human trials.

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

While the WHO Surgical Safety Checklist (the Checklist) can improve patient outcomes, variable administration can erode benefits. We sought to understand and improve how operating room (OR) staff use the Checklist. Our specific aims were to: determine if OR staff can discriminate between good and poor quality of Checklist administration using a validated audit tool (WHOBARS); to determine reliability and accuracy of WHOBARS self-ratings; determine the influence of demographic variables on ratings and explore OR staff attitudes to Checklist administration.DesignMixed methods study using WHOBARS ratings of surgical cases by OR staff and two independent observers, thematic analysis of staff interviews.ParticipantsOR staff in three New Zealand hospitals.Outcome measuresReliability of WHOBARS for self-audit; staff attitudes to Checklist administration.ResultsAnalysis of scores (243 participants, 2 observers, 59 cases) supported tool reliability, with 87% of WHOBARS score variance attributable to differences in Checklist administration between cases. Self-ratings were significantly higher than observer ratings, with some differences between professional groups but error variance from all raters was less than 10%. Key interview themes (33 interviewees) were: Team culture and embedding the Checklist, Information transfer and obstacles, Raising concerns and ‘A tick-box exercise’. Interviewees felt the Checklist could promote teamwork and a safety culture, particularly enabling speaking up. Senior staff were of key importance in setting the appropriate tone.ConclusionsThe WHOBARS tool could be useful for self-audit and quality improvement as OR staff can reliably discriminate between good and poor Checklist administration. OR staff self-ratings were lenient compared with external observers suggesting the value of external audit for benchmarking. Small differences between ratings from professional groups underpin the value of including all members of the team in scoring. We identified factors explaining staff perceptions of the Checklist that should inform quality improvement interventions.

AIMS: Early pain after laparoscopy is often severe. Oxycodone is a feasible analgesic option after laparoscopy, but there are sparse data on epidural administration. The aim was to evaluate the analgesic efficacy and pharmacokinetics of a single dose of epidural oxycodone as a part of multimodal analgesia after gynaecological laparoscopy. METHODS: Women (n = 60), aged 23–71 years, undergoing elective gynaecological laparoscopy, were administrated either epidural oxycodone 0.1 mg kg(−1) and intravenous (i.v.) saline (EPI‐group n = 31), or epidural saline and i.v. oxycodone 0.1 mg kg(−1) (IV‐group = 29) in a randomised, double blind, active control, double dummy clinical trial. A pharmacokinetic model was developed using population modelling of plasma and cerebrospinal fluid (CSF) concentrations obtained in these patients and data of 2 published studies. The primary outcome was the amount of i.v. fentanyl for rescue analgesia during the first 4 hours. RESULTS: Twenty of the 31 patients in the EPI‐group and 26 of the 29 patients in the IV‐group needed i.v. fentanyl for rescue analgesia, P = .021. The median (interquartile range) number of fentanyl doses were 1.0 (1.0–3.0) in the EPI‐group and 2.5 (1.0–4.0) doses in the IV‐group, P = .008. Plasma concentrations were similar, but CSF concentrations were 100‐fold higher in the EPI‐group. The population model indicated that 60% of oxycodone injected into the epidural space enters into CSF and 40% is absorbed into the systemic circulation. CONCLUSIONS: The data support superiority of epidural administration of oxycodone compared to i.v. administration during the first hours after laparoscopic surgery. This is likely to be based on enhanced permeation into the central nervous system after epidural administration.

Patient-reported outcome (PRO) measures (PROMs) are increasingly used as endpoints in surgical trials. PROs need to be consistently measured and reported to accurately evaluate surgical care. Laparoscopic cholecystectomy (LC) is a commonly performed procedure which may be evaluated by PROs. We aimed to evaluate the frequency and consistency of PRO measurement and reporting after LC. MEDLINE, EMBASE, and the Cochrane Central Register of Controlled Trials were searched for prospective studies reporting PROs of LC, between 2013 and 2016. Data on the measurement and reporting of PROs were extracted. A total of 281 studies were evaluated. Forty-five unique multi-item questionnaires were identified, most of which were used in single studies (n = 35). One hundred and ten unique rating scales were used to assess 358 PROs. The visual analogue scale was used to assess 24 different PROs, 17 of which were only reported in single studies. Details about the type of rating scale used were not given for 72 scales. Three hundred and twenty-three PROs were reported in 162 studies without details given about the scale or questionnaire used to evaluate them. Considerable variation was identified in the choice of PROs reported after LC, and in how they were measured. PRO measurement for LC is focused on short-term outcomes, such as post-operative pain, rather than longer-term outcomes. Consideration should be given towards the development of a core outcome set for LC which incorporates PROs.

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.

Respiratory depression is a common adverse effect of propofol and remifentanil. We aimed to develop a model for respiratory depressant effects of propofol with remifentanil in patients undergoing endoscopy with sedation. Data were available for 136 patients undergoing endoscopy with sedation. Participants randomly received infusions of propofol and remifentanil. Predicted plasma concentrations, outputted by infusion pumps, were available. Transcutaneous arterial pressure of carbon dioxide (pCO2) was measured. Data were analyzed using nonlinear mixed-effects modeling methods. Covariate relationships were investigated for age, noxious stimuli (endoscopy tube insertion), and A118G genotype for the µ-opioid receptor (OPRM1). Participants had a median (range) age of 64.0 (25.0-88.0) years, weight of 70.0 (35.0-98.0) kg, and height of 164.0 (147.0-190.0) cm. Seven percent were recessive homozygous for OPRM1 polymorphism. An indirect-effect model with a "modulator" compartment best described pCO2 data (P < 0.001) over a direct-effect model. Remifentanil inhibited pCO2 removal with an IC50 of 1.13 ng/ml and first-order rate constant (ke 0) of 0.28 minute(-1). Propofol affected the modulator compartment with an IC50 of 4.97 µg/ml (no effect-site compartment). Propofol IC50 and remifentanil ke 0 were reduced with increasing age. Noxious stimuli and genotype were not significant covariates. An indirect-effect model with a rebound mechanism can describe remifentanil- and propofol-induced changes in pCO2 in patients undergoing noxious procedures. The model may be useful for identifying optimal dosing schedules for these drugs in a combination that provides adequate sedation but avoids respiratory depression.

Background Outcome benefits of using the WHO Surgical Safety Checklist rely on compliance with checklist administration. Objective To evaluate engagement of operating room (OR) subteams (anaesthesia, surgery and nursing), and compliance with administering checklist domains (Sign In, Time Out and Sign Out) and checklist items, after introducing a wall-mounted paperless checklist with migration of process leadership (Sign In, Time Out and Sign Out led by anaesthesia, surgery and nursing, respectively). Methods This was a pre-post observational study in which 261 checklist domains in 111 operations were observed 2 months after changing the checklist administration paradigm. Compliance with administration of the checklist domains and individual checklist items was recorded, as was the number of OR subteams engaged. Comparison was made with 2013 data from the same OR suite prior to the paradigm change. Results Data are presented as 2013 versus the present study. The Sign In, Time Out and Sign Out domains were administered in 96% vs 98% (p=0.69), 99% vs 99% (p=1.00) and 22% vs 84% (p