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• W3003148624 abstract "The Balanced Anaesthesia Study was a large, multicentre, international randomised controlled trial (RCT) that posed the question: does light general anaesthesia (defined as a bispectral index [BIS] target of 50) improve survival at 1 yr after surgery in patients over 60 yr of age having major surgery when compared with deep general anaesthesia (defined as a BIS target of 35)? Median volatile anaesthetic administration was decreased by 30% from 1.10 age-adjusted minimum alveolar concentration (MAC) in the deep anaesthesia group to 0.78 age-adjusted MAC in the light anaesthesia group.1Short T.G. Campbell D. Frampton C. et al.Anaesthetic depth and complications after major surgery: an international, randomised controlled trial.Lancet. 2019; 18 (Advance Access published on October)https://doi.org/10.1016/S0140-6736(19)32315-3Abstract Full Text Full Text PDF Scopus (78) Google Scholar One year mortality rate was 6.5% in the light anaesthesia group and 7.2% in the deep anaesthesia group (absolute difference=0.8%; 95% confidence interval −0.5% to 2.0%), and the incidence of major perioperative adverse events was similar in the two groups. The investigators concluded that light general anaesthesia was not associated with lower 1 yr postoperative mortality than deep general anaesthesia.1Short T.G. Campbell D. Frampton C. et al.Anaesthetic depth and complications after major surgery: an international, randomised controlled trial.Lancet. 2019; 18 (Advance Access published on October)https://doi.org/10.1016/S0140-6736(19)32315-3Abstract Full Text Full Text PDF Scopus (78) Google Scholar The Balanced Anaesthesia Study was by far the largest and most robust trial examining the impact of anaesthetic depth on intermediate-term postoperative mortality, enrolling 6644 patients from 73 centres in seven countries, and collecting multiple blinded endpoint assessments up to 1 yr after surgery. The investigators are to be lauded for the colossal effort involved in undertaking a trial of this magnitude and rigour. However, a key methodological consideration that limits interpretation and application of the trial's results is a lack of sufficient statistical power to detect differences in the primary outcome; the sample size was inadequate to answer the trial's primary question. This warrants further discussion to inform the design of clinical trials in perioperative medicine going forward. In most situations, there are four criteria that determine the sample size required for an RCT: (i) the threshold statistical significance level (type I error), (ii) the desired statistical power (i.e. the probability of detecting an effect, if a true effect is present), (iii) the incidence of the outcome of interest in the population being studied, and (iv) the anticipated treatment effect of the intervention being studied on the outcome of interest. The first two criteria are arbitrarily determined by convention, with usual parameters being 0.05 for type I error and 0.80 for power (type II error), respectively. The Balanced Anaesthesia Study's sample size was calculated using a threshold significance of 0.049 (after adjustment of 0.05 to account for one interim analysis), desired statistical power of 0.80, and anticipated loss to follow-up of 2%. However, these historically accepted conventions are today considered to be controversial, in that under these assumptions many false positive and unreproducible studies have been published.2Ioannidis J.P.A. Why most published research findings are false.PLoS Med. 2005; 2: e124Crossref PubMed Scopus (5866) Google Scholar It has been suggested instead that, in order to improve reliability and reproducibility in science, more stringent statistical approaches, such as substantially lowering the P-value threshold and increasing the statistical power, should be adopted.3Ioannidis J.P.A. The proposal to lower P value thresholds to .005.JAMA. 2018; 319: 1429-1430Crossref PubMed Scopus (426) Google Scholar,4Lamberink H.J. Otte W.M. Sinke M.R.T. et al.Statistical power of clinical trials increased while effect size remained stable: an empirical analysis of 136,212 clinical trials between 1975 and 2014.J Clin Epidemiol. 2018; 102: 123-128Abstract Full Text Full Text PDF PubMed Scopus (26) Google Scholar Empirically, using a P<0.005 threshold instead of P<0.05 may also better align with appraisals of the evidence leading to favourable recommendations for using an intervention.5Koletsi D. Solmi M. Pandis N. Fleming P.S. Correll C.U. Ioannidis J.P.A. Most recommended medical interventions reach P<0.005 for their primary outcomes in meta-analyses.Int J Epidemiol. 2019; 25 (Advance Access published on November)https://doi.org/10.1093/ije/dyz241Crossref Scopus (2) Google Scholar The latter two sample size criteria—outcome incidence and treatment effect size—should be less arbitrary and are typically based on clinical judgement and the available preliminary evidence. The Balanced Anaesthesia Study investigators anticipated an incidence of their primary outcome (all-cause mortality at 1 yr after surgery) of 10% in the control arm with a 20% relative treatment benefit from avoiding deep anaesthesia (resulting in an 8% incidence of the primary outcome in the intervention arm). However, the actual observed incidence of all-cause mortality 1 yr after surgery in the control arm was substantially lower (7.2%). The Balanced Anaesthesia Study selectively included higher risk patients: those aged 60 yr and older, with significant comorbidity, and having surgery with expected duration of more than 2 h. This was based on a desire to study the population most likely to benefit from the intervention: those who were at elevated risk of perioperative complications and mortality. Paradoxically, this may have diminished the observed treatment effect size, as many of these patients who died within a year of surgery may have died not from cardiovascular causes or other events that could plausibly be attributed to anaesthetic depth, but rather as a result of severe underlying pathology and necessarily invasive operations. Many of the patients who were enrolled—50% of whom had a history of malignancy—were at substantial risk of death within the subsequent year, regardless of anaesthetic management or even whether or not they had surgery. Thus, a proportion in both the intervention and control arms probably died as a result of their underlying disease, irrespective of the impact of their depth of anaesthesia. This phenomenon is similar to the statistical concept of competing risk: an event that precludes the observation of the primary outcome of interest in a survival analysis. The second issue leading to the Balanced Anaesthesia Study being underpowered stems from the choice of and assumptions made about the primary outcome, all-cause mortality 1 yr after surgery. Based on the increased risk of the population that was included in the trial, the Balanced Anaesthesia Study investigators opted to base their sample size calculation on an assumed 10% incidence of mortality 1 yr after surgery in the control group. Unfortunately, the observed incidence of the primary outcome in the control arm was 7.2% which, taken alone, would result in a sample size that was approximately 3000 patients too few to be able to detect differences between groups according to the a priori statistical significance and power thresholds that were selected (Table 1). This may, in part, be related to the fact that the trial population was lower risk than the population upon which this mortality estimate was based. The incidence of 1 yr mortality reported in other large, perioperative medicine trials in cardiac and noncardiac surgery populations of varying risk ranges from 4% to 10%,6Lindholm M.L. Traff S. Granath F. et al.Mortality within 2 years after surgery in relation to low intraoperative bispectral index values and preexisting malignant disease.Anesth Analg. 2009; 108: 508-512Crossref PubMed Scopus (157) Google Scholar, 7Leslie K. Myles P.S. Kasza J. et al.Nitrous oxide and serious long-term morbidity and mortality in the evaluation of Nitrous Oxide in the Gas Mixture for anaesthesia (ENIGMA)-II trial.Anesthesiology. 2015; 123: 1267-1280Crossref PubMed Scopus (40) Google Scholar, 8Conen D. Alonso-Coello P. Douketis J. et al.Risk of stroke and other adverse outcomes in patients with perioperative atrial fibrillation 1 year after non-cardiac surgery.Eur Heart J. 2019; 25 (Advance Access published on June)https://doi.org/10.1093/eurheartj/ehz431Crossref Scopus (35) Google Scholar, 9Mrkobrada M. Chan M.T.V. Cowan D. et al.Perioperative covert stroke in patients undergoing non-cardiac surgery (NeuroVISION): a prospective cohort study.Lancet. 2019; 394: 1022-1029Abstract Full Text Full Text PDF PubMed Scopus (101) Google Scholar, 10Lamy A. Devereaux P.J. Prabhakaran D. et al.Effects of off-pump and on-pump coronary-artery bypass grafting at 1 year.N Engl J Med. 2013; 368: 1179-1188Crossref PubMed Scopus (330) Google Scholar, 11Monk T.G. Saini V. Weldon B.C. Sigl J.C. Anesthetic management and one-year mortality after noncardiac surgery.Anesth Analg. 2005; 100: 4-10Crossref PubMed Scopus (679) Google Scholar a range more consistent with the observed incidence of 1 yr mortality in the Balanced Anaesthesia Study.Table 1Sample size requirements for the Balanced Anaesthesia Study based on varying incidence of 1 yr mortality and treatment effect size given a threshold P-value of 0.049, power = 0.8, and 2% loss to follow-up.Incidence of 1 yr mortalityTreatment relative effect size5%10%15%20% 5%239 17058 31225 26613 846 7%167 26440 819∗Sample size required based on observed incidence of mortality and likely effect size.17 6979703†Sample size required based on observed incidence of mortality and anticipated effect size of 20%. 10%113 40827 70212 0206595‡Sample size based on assumptions made in the Balanced Anaesthesia Study.∗ Sample size required based on observed incidence of mortality and likely effect size.† Sample size required based on observed incidence of mortality and anticipated effect size of 20%.‡ Sample size based on assumptions made in the Balanced Anaesthesia Study. Open table in a new tab As time elapses from the initial surgical procedure, additional unrelated exposures occur, and are superimposed upon a patient's baseline risk of mortality from their underlying disease. Many of these exposures may have nothing to do with the details of the original anaesthetic. The multiple (and multiplying) causal pathways that can lead to death 1 yr after surgery gives rise to the question: to what extent might interventions applied by anaesthesiologists during the intraoperative period be expected to impact mortality 1 yr later? Realistically, probably not much. Thus, researchers in anaesthesiology evaluating the impact of intraoperative interventions (which typically target a single causal mechanism) on long-term patient-important outcomes such as major morbidity and mortality should anticipate relative treatment effect sizes on the order of at most 5–15%, depending on the outcome evaluated and time elapsed since surgery. One could also argue that the very large number of protocol violations in the intention to treat population (2566/6644; 38.6%) dampened the observed treatment effect. Furthermore, a possible implication of these many violations is that an adequately powered trial must take into account an anticipated 40% protocol violation rate. Nevertheless, the per protocol analysis found a similar, but still not statistically significant magnitude of effect. Perhaps, if there is a mortality benefit from lighter anaesthesia, it arises as a result of a general approach to intraoperative avoidance of deep anaesthesia, and not the minute-to-minute details of anaesthetic management. A final issue to consider is the unreliability of BIS as a monitor of hypnotic depth during general anaesthesia. BIS readings are obtained using a proprietary algorithm that converts electrical activity from forehead electrodes into a number from 100 to 0, which is meant to correspond to the depth of hypnosis. The electrical signals measured at the forehead originate from various sources, including the brain, muscles, the heart, and possibly external contaminants (e.g. forced air warmers).12Kertai M.D. Whitlock E.L. Avidan M.S. Brain monitoring with electroencephalography and the electroencephalogram-derived bispectral index during cardiac surgery.Anesth Analg. 2012; 114: 533-546Crossref PubMed Scopus (60) Google Scholar It is difficult to disambiguate brain electrical activity from these confounding sources. Therefore, if two patients have a BIS reading of 44, this does not necessarily mean that they have comparable hypnotic depth. Of greatest concern regarding the unreliability of the BIS as a measure of hypnotic depth are the findings of a study conducted by Schuller and colleagues13Schuller P.J. Newell S. Strickland P.A. Barry J.J. Response of bispectral index to neuromuscular block in awake volunteers.Br J Anaesth. 2015; 115: i95-i103Abstract Full Text Full Text PDF PubMed Scopus (137) Google Scholar in awake volunteers who received either rocuronium or succinylcholine with no hypnotic agents. In some of these volunteers, BIS readings as low as the 40s were displayed, suggesting that they were deeply anaesthetised, whereas they were in fact wide awake. Moreover, BIS lacks intra-patient reproducibility; two concurrent BIS readings in the same patient during surgery can be very discrepant.14Niedhart D.J. Kaiser H.A. Jacobsohn E. Hantler C.B. Evers A.S. Avidan M.S. Intrapatient reproducibility of the BISxp monitor.Anesthesiology. 2006; 104: 242-248Crossref PubMed Scopus (52) Google Scholar Therefore, using BIS in the Balanced Anaesthesia trial may have provided inaccurate information regarding hypnotic depth that may in turn have contributed to the many protocol violations, prevented the two compared groups from achieving target differentiation in actual hypnotic depth, and ultimately eroded the magnitude of a potential treatment effect. The unrealistic assumptions that were made in the design of the Balanced Anaesthesia Study, regarding 1 year mortality incidence and plausible effect size of hypnotic depth on mortality, limited the conclusions that could reasonably be drawn from its findings. Considering the actual incidence of mortality and more plausible treatment effect sizes than were assumed in the sample size calculation, it is apparent that the Balanced Anaesthesia Study could not, by design, provide strong evidence to support or refute the hypothesis that the avoidance of deep anaesthesia results in decreased mortality 1 yr after surgery. Table 1 summarises what the sample size requirements would be based on varying incidences of 1 yr mortality and treatment effect sizes. Considering the observed (rather than the anticipated) incidence of mortality alone, the sample size required would range from 9703 to 167 264 patients. Given the observed incidence of 1 yr mortality, and a more modest relative treatment effect size of 10%, the required sample size to demonstrate a 1 yr mortality benefit from the avoidance of deep anaesthesia would be 40 819 patients. Using the same assumptions but increasing the power to 0.90—as is now required by many peer-reviewed funders—the required sample size would further increase to 54 309 patients. Given current limitations in public research funding and the time-intensive nature of traditional individual patient RCTs, an adequately powered trial addressing this question may never be done using traditional approaches to the design of RCTs. To make it feasible, such a randomised trial would probably have to use some real-world pragmatic design (e.g. linking both patient recruitment and outcome collection to existing routinely collected data and thus keeping cost within reasonable limits).15Lauer M.S. D'Agostino R.B. Sr The randomized registry trial--the next disruptive technology in clinical research?.N Engl J Med. 2013; 369: 1579-1581Crossref PubMed Scopus (456) Google Scholar,16McCord K.A. Al-Shahi Salman R. Treweek S. et al.Routinely collected data for randomized trials: promises, barriers, and implications.Trials. 2018; 19: 29Crossref PubMed Scopus (59) Google Scholar Given what is probably a limited benefit from avoiding deep anaesthesia on 1 yr mortality and the massive number of patients required to strongly suggest the existence of benefit, should researchers in perioperative medicine even try to answer this question, or, for that matter, similar questions examining the impact of intraoperative interventions on long-term morbidity and mortality? When one takes into account the scope of the problem, the answer is absolutely yes. More than 300 million people undergo inpatient surgery globally each year.17Weiser T.G. Haynes A.B. Molina G. et al.Estimate of the global volume of surgery in 2012: an assessment supporting improved health outcomes.Lancet. 2015; 385: S11Abstract Full Text Full Text PDF PubMed Google Scholar Based on 1 yr mortality rates ranging from 4% to 10%,6Lindholm M.L. Traff S. Granath F. et al.Mortality within 2 years after surgery in relation to low intraoperative bispectral index values and preexisting malignant disease.Anesth Analg. 2009; 108: 508-512Crossref PubMed Scopus (157) Google Scholar, 7Leslie K. Myles P.S. Kasza J. et al.Nitrous oxide and serious long-term morbidity and mortality in the evaluation of Nitrous Oxide in the Gas Mixture for anaesthesia (ENIGMA)-II trial.Anesthesiology. 2015; 123: 1267-1280Crossref PubMed Scopus (40) Google Scholar, 8Conen D. Alonso-Coello P. Douketis J. et al.Risk of stroke and other adverse outcomes in patients with perioperative atrial fibrillation 1 year after non-cardiac surgery.Eur Heart J. 2019; 25 (Advance Access published on June)https://doi.org/10.1093/eurheartj/ehz431Crossref Scopus (35) Google Scholar, 9Mrkobrada M. Chan M.T.V. Cowan D. et al.Perioperative covert stroke in patients undergoing non-cardiac surgery (NeuroVISION): a prospective cohort study.Lancet. 2019; 394: 1022-1029Abstract Full Text Full Text PDF PubMed Scopus (101) Google Scholar, 10Lamy A. Devereaux P.J. Prabhakaran D. et al.Effects of off-pump and on-pump coronary-artery bypass grafting at 1 year.N Engl J Med. 2013; 368: 1179-1188Crossref PubMed Scopus (330) Google Scholar, 11Monk T.G. Saini V. Weldon B.C. Sigl J.C. Anesthetic management and one-year mortality after noncardiac surgery.Anesth Analg. 2005; 100: 4-10Crossref PubMed Scopus (679) Google Scholar 12–30 million people die within a year of surgery annually. The magnitude of the problem means that even very small reductions in mortality owing to changes in anaesthetic technique—on the order of 5–10% relative reduction—would result in 600 000–3 000 000 lives saved each year. However, there are now numerous examples in the critical care and anaesthesiology literature of purportedly ‘negative’ trials that either lack a physiologic rationale or—likely because of issues related to statistical power—failed to give a conclusive answer to the question that the trial sought to answer. How then to address these questions of utmost importance? Very large, pragmatic randomised trials, which evaluate the impact of general approaches to anaesthesia care in broad populations when they are incorporated into everyday practice, are already starting to be done.18Spence J. Belley-Cote E. Lee S.F. et al.The role of randomized cluster crossover trials for comparative effectiveness testing in anesthesia: design of the Benzodiazepine-Free Cardiac Anesthesia for Reduction in Postoperative Delirium (B-Free) trial.Can J Anesth. 2018; 65: 813-821Crossref PubMed Scopus (14) Google Scholar Experience from other fields suggests that they can become more common and should be possible to scale up once introduced as a standard of testing.19Mathes T. Buehn S. Prengel P. Pieper D. Registry-based randomized controlled trials merged the strength of randomized controlled trails and observational studies and give rise to more pragmatic trials.J Clin Epidemiol. 2018; 93: 120-127Abstract Full Text Full Text PDF PubMed Scopus (40) Google Scholar, 20Lund L.H. Oldgren J. James S. Registry-based pragmatic trials in heart failure: current experience and future directions.Curr Heart Fail Rep. 2017; 14: 59-70Crossref PubMed Scopus (56) Google Scholar, 21Choudhry N.K. Randomized, controlled trials in health insurance systems.N Engl J Med. 2017; 377: 957-964Crossref PubMed Scopus (30) Google Scholar Trials such as these occasionally willfully diminish the observed effect size by studying broad populations (some of whom may have limited benefit from an intervention), but overcome this noise by including very large numbers of patients. Moreover, in most circumstances our ability to speculate and predict who exactly may or may not benefit from an intervention is unlikely to be well informed. Therefore, broad, all-inclusive recruitment may be the best solution. Furthermore, when there is strong evidence to suggest that some types of patients may not benefit from an intervention, it is still possible to run large pragmatic trials excluding them with a simple process (e.g. having a point-of-care system that eliminates all those patients from consideration and allows all others to be considered for randomisation). Another approach that has been taken to increase power in clinical trials has been to choose a composite primary outcome, which increases the signal strength (number of outcomes), and therefore can improve the chance of detecting an effect of an intervention.22Freemantle N. Calvert M. Wood J. Eastaugh J. Griffin C. Composite outcomes in randomized trials: greater precision but with greater uncertainty?.JAMA. 2003; 289: 2554-2559Crossref PubMed Scopus (534) Google Scholar Notably, for the Balanced Anaesthesia Study, there were no significant differences between the study groups with respect to the following composite outcomes: (i) death plus cardiovascular complications, (ii) infectious complications, (iii) grade 3 adverse events, and (iv) grade 4 (life-threatening) adverse events. Nonetheless, composite outcome reporting is controversial, and there are important pros and cons that need to be considered before selecting a primary outcome that is a composite.23Myles P.S. Devereaux P.J. Pros and cons of composite endpoints in anesthesia trials.Anesthesiology. 2010; 113: 776-778Crossref PubMed Scopus (30) Google Scholar Of central concern is the fact that there is typically a gradient of importance to patients among the outcomes included in a composite, and those of lesser importance—for example angina as opposed to death—are typically more common, which may lead to misleading impressions of the true clinical value of a treatment.23Myles P.S. Devereaux P.J. Pros and cons of composite endpoints in anesthesia trials.Anesthesiology. 2010; 113: 776-778Crossref PubMed Scopus (30) Google Scholar,24Ferreira-Gonzalez I. Busse J.W. Heels-Ansdell D. et al.Problems with use of composite end points in cardiovascular trials: systematic review of randomised controlled trials.BMJ. 2007; 334: 786Crossref PubMed Scopus (315) Google Scholar Therefore, although the congruent findings with respect to other postoperative complications somewhat bolsters the ‘null’ finding of the Balanced Anaesthesia Study in relation to mortality, we are still left with uncertainty. Alternatively, consideration could be given to increasing the observed treatment effect by focusing more closely on the population most likely to benefit from this intervention. This presupposes that we either know well which patients are most likely to benefit, or substantial information about this privileged set emerges during the conduct of a trial. Bayesian or adaptive designs are an innovation in individual patient RCT design that allow continual modifications to key aspects of the trial design while the trial is ongoing. As patients are enrolled in a trial utilising an adaptive design, information accumulates about their outcomes, which reduces the uncertainty regarding the true efficacy of the intervention being studied.25Pallmann P. Bedding A.W. Choodari-Oskooei B. et al.Adaptive designs in clinical trials: why use them, and how to run and report them.BMC Med. 2018; 16: 29Crossref PubMed Scopus (256) Google Scholar Adaptive clinical trials take advantage of this accumulating information by modifying key trial parameters based on data as it is collected and according to a priori rules, such that the population most likely to benefit is selectively recruited as information about what characterises this population is accrued. As an example, the recently conducted Restrictive or Liberal Red-Cell Transfusion for Cardiac Surgery trial (TRICS III) showed that in 5243 moderate-risk adult cardiac surgery patients, a restrictive red cell transfusion strategy (haemoglobin threshold of <7.5 g dl−1) was non-inferior to a liberal strategy (haemoglobin threshold of <9.5 g dl−1) with regard to death or major disability.26Mazer C.D. Whitlock R.P. Fergusson D.A. et al.Restrictive or liberal red-cell transfusion for cardiac surgery.N Engl J Med. 2017; 377: 2133-2144Crossref PubMed Scopus (389) Google Scholar In hypothesis-generating prespecified subgroup analyses, the restrictive strategy appeared to be superior to the liberal strategy in patients 75 yr or older; this finding was initially observed 28 days after surgery and was still present at 6 months.26Mazer C.D. Whitlock R.P. Fergusson D.A. et al.Restrictive or liberal red-cell transfusion for cardiac surgery.N Engl J Med. 2017; 377: 2133-2144Crossref PubMed Scopus (389) Google Scholar,27Mazer C.D. Whitlock R.P. Fergusson D.A. et al.Six-month outcomes after restrictive or liberal transfusion for cardiac surgery.N Engl J Med. 2018; 379: 1224-1233Crossref PubMed Scopus (134) Google Scholar However, as older adults were not selectively recruited, the results of TRICS III were only hypothesis-generating and provide the basis for a follow-up trial focusing on the older population. Had it been appreciated while TRICS III was underway that older adults may benefit more from a restrictive transfusion threshold, the trial could have adapted to focus on this population, substantially improving efficiency and, possibly, generating more definitive results. Unfortunately, in most areas of research in anaesthesiology, the lack of a mechanistic understanding or knowledge of populations more likely to benefit limits the current opportunities to use this approach. The Balanced Anaesthesia Study is an example of one of the most impressive international perioperative clinical trials ever conducted. It represents by far the largest and most rigorously conducted RCT examining the impact of deep anaesthesia on mortality one year after surgery. However, the pre-study probability that avoiding deep anaesthesia would result in a 20% relative reduction in 1 yr mortality was low.28Vlisides P.E. Ioannidis J.P.A. Avidan M.S. Hypnotic depth and postoperative death: a Bayesian perspective and an Independent Discussion of a clinical trial.Br J Anaesth. 2019; 122: 421-427Abstract Full Text Full Text PDF PubMed Scopus (9) Google Scholar The information generated by the Balanced Anaesthesia Study was inconclusive. Its results make a 2% absolute gain in survival unlikely, but 0.5% or 1% absolute gains in survival are still compatible with what was observed in this trial and thus cannot be excluded. Going forward, if we hope to answer important clinical questions where effect sizes might be very small (e.g. absolute differences of <1% or relative differences of <10%), researchers in anaesthesiology may have to accept that conventional adequately powered randomised trials are simply too expensive and impractical. Ultimately, one of the greatest benefits resulting from the Balanced Anaesthesia Study might be its clear demonstration that there is a need for new approaches to designing clinical trials in anaesthesia and perioperative medicine. Wrote the first draft of the manuscript: JS. Provided critical feedback on the manuscript; approved the final version of the manuscript: all authors. None of the authors has a financial conflict of interests to declare. MSA is an editor of the British Journal of Anaesthesia." @default.
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