Postoperative Delirium in a Substudy of Cardiothoracic Surgical Patients in the BAG-RECALL Clinical Trial

Whitlock, Elizabeth L. MD, MSc*; Torres, Brian A. CRNA*; Lin, Nan PhD; Helsten, Daniel L. MD*; Nadelson, Molly R. MD*; Mashour, George A. MD, PhD; Avidan, Michael S. MB, BCh, FCASA*

doi: 10.1213/ANE.0000000000000028
Neuroscience in Anesthesiology and Perioperative Medicine: Research Report

BACKGROUND: Postoperative delirium in the intensive care unit (ICU) is a frequent complication after cardiac or thoracic surgery and is associated with increased morbidity and mortality.

METHODS: In this single-center substudy of the BAG-RECALL trial (NCT00682825), we screened patients after cardiac or thoracic surgery in the ICU twice daily for delirium using the Confusion Assessment Method for the ICU. The primary outcome was the incidence of delirium in patients who had been randomized to intraoperative Bispectral Index (BIS)-guided and end-tidal anesthetic concentration-guided depth of anesthesia protocols. As a secondary analysis, a Bayesian stochastic search variable selection strategy was used to rank a field of candidate risk factors for delirium, followed by binary logistic regression.

RESULTS: Of 310 patients assessed, 28 of 149 (18.8%) in the BIS group and 45 of 161 (28.0%) in the end-tidal anesthetic concentration group developed postoperative delirium in the ICU (odds ratio 0.60, 95% confidence interval, 0.35–1.02, P= 0.058). Low average volatile anesthetic dose, intraoperative transfusion, ASA physical status, and European System for Cardiac Operative Risk Evaluation were identified as independent predictors of delirium.

CONCLUSIONS: A larger randomized study should determine whether brain monitoring with BIS or an alternative method decreases delirium after cardiac or thoracic surgery. The association between low anesthetic concentration and delirium is a surprising finding and could reflect that patients with poor health are both more sensitive to the effects of volatile anesthetic drugs and are also more likely to develop postoperative delirium. Investigation of candidate methods to prevent delirium should be prioritized in view of the established association between postoperative delirium and adverse patient outcomes.

Published ahead of print January 1, 2014

From the *Department of Anesthesiology, Washington University School of Medicine; Department of Mathematics, Washington University in Saint Louis, Saint Louis, Missouri; and Department of Anesthesiology, University of Michigan Medical School, Ann Arbor, Michigan.

Elizabeth L. Whitlock, MD, MSc, is currently affiliated with the Department of Anesthesiology and Perioperative Care, University of California, San Francisco, San Francisco, California.

Accepted for publication October 1, 2013.

Published ahead of print January 1, 2014

Funding: The BAG-RECALL trial was supported by grants from the Foundation for Anesthesia Education and Research and the American Society of Anesthesiologists (CFM-08/15/2007 to M. Avidan). The funding agencies had no role in the design, conduct, or reporting of the study. E. Whitlock was a predoctoral research trainee under grant number UL1 RR024992 and subaward number TL1 RR024995 from the National Center for Research Resources (NCRR), a component of the National Institutes of Health (NIH) and the NIH Roadmap for Medical Research. The contents of this manuscript are solely the responsibility of the authors and do not necessarily represent the official view of NCRR or NIH.

This report was previously presented, in part, at the Association of University Anesthesiologists’ Annual Meeting, May 2011, Philadelphia, PA.

The authors declare no conflicts of interest.

Reprints will not be available from the authors.

Address correspondence to Elizabeth L. Whitlock, MD, MSc, Department of Anesthesia and Perioperative Care University of California, 513 Parnassus Ave., Room S436, San Francisco, CA 94143. Address e-mail to

Article Outline

Delirium is an acute change in cognition and concentration that complicates the postoperative course of 10% to 40% of cardiothoracic surgical patients. Patients who suffer delirium after cardiac surgery are at increased risk of persistent cognitive impairment,1 functional decline,2 and death,3 and postoperative delirium is associated with increased hospital length of stay and higher costs.4 Many risk factors for postoperative delirium have been identified, such as those in the review by Marcantonio5; variables such as patient age, preexisting cognitive impairment or dementia, and duration and invasiveness of operation are commonly cited.

An association between postoperative delirium and excessive intraoperative anesthetic exposure has been hypothesized. Studies have investigated the use of brain monitoring, such as the Bispectral Index (BIS)® (Covidien, Boulder, CO) monitor, to guide anesthetic titration to decrease postoperative delirium. Three randomized studies in noncardiac and nonthoracic surgical populations have found a decrease in delirium with BIS-guided anesthesia.6–8 It is unknown whether BIS guidance decreases delirium after cardiac and thoracic surgery.

There has been little inquiry into associations between postoperative delirium and intraoperative variables, such as arterial blood pressure, total anesthetic dose, and depth of anesthesia. A small study of cardiac surgery patients suggested that targeting higher arterial blood pressure during cardiopulmonary bypass was associated with decreased postoperative delirium.9 Patients undergoing cardiac and thoracic surgery are particularly vulnerable to physiologically significant intraoperative and postoperative derangements in perfusion and oxygenation and receive postoperative care in a single specialized intensive care unit (ICU) at our institution.

We therefore performed this predetermined single-site substudy of the BAG-RECALL clinical trial (NCT00682825) to determine whether there was a difference in postoperative delirium between patients randomized to BIS-guided or end-tidal anesthetic concentration (ETAC)-guided protocols. Secondarily, we assessed the contribution of patient and intraoperative variables to postoperative delirium in the ICU after major cardiac and/or thoracic surgery.

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Ethics Committee Approval and Study Design

This was a prespecified single-site substudy of the BAG-RECALL multicenter clinical trial.10 Approval was granted by the Washington University Human Research Protection Office, and all participants gave written consent for participation in the BAG-RECALL trial, which assessed patients for intraoperative awareness, as well as for this substudy, which assessed patients for postoperative delirium. Patients receiving care in the cardiothoracic ICU after major cardiac and/or thoracic surgery at a quaternary care center were screened twice daily for delirium using the Confusion Assessment Method for the ICU (CAM-ICU). Data on preoperative comorbidities, intraoperative vital signs, and drug administration were collected to investigate risk factors for developing postoperative delirium.

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Patient Population

The BAG-RECALL trial enrolled 6100 patients undergoing general anesthesia at 3 international centers. Enrolled patients were at increased risk for intraoperative awareness based on published risk factors for that complication; major criteria included planned open heart surgery, ejection fraction (EF) <40%, history of intraoperative awareness, history of or anticipated difficult intubation, ASA physical status (PS) 4 or 5, aortic stenosis, end-stage lung disease, pulmonary hypertension, marginal exercise tolerance, or daily use of certain neuroactive medications or alcohol. Patients were randomized to either an ETAC-guided (alerts for <0.7 or >1.3 age-adjusted minimum alveolar concentration [MAC]) or BIS-guided (alerts for BIS >60 or BIS <40) protocol. The primary outcome of that trial was the incidence of intraoperative awareness in the 2 groups. This substudy included consecutive patients enrolled in the BAG-RECALL trial who received care in the cardiothoracic ICU at Barnes-Jewish Hospital in St. Louis from August 20, 2009 through April 19, 2010.

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Delirium Assessments

Delirium assessments were performed twice daily until postoperative day 10 or ICU discharge, whichever occurred first, using the CAM-ICU.11 A single critical care nurse (Brian A. Torres) performed most assessments and abstracted documented CAM-ICU assessments performed by other nursing staff from patient charts when necessary. All staff performing CAM-ICU assessments had the same standardized institutional training on the proper procedures for conducting the examination. ICU staff, including nurses, physicians, and nurse Torres, were all blinded to BIS or ETAC group assignment. The Richmond Agitation and Sedation Scale12 grading was used to determine whether the delirium was hyperactive or hypoactive.

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Collection of Other Data

Patient demographics and comorbidities were documented as part of the BAG-RECALL trial and were used to conduct a modified European System for Cardiac Operative Risk Evaluation (EuroSCORE) as a measure of perioperative mortality risk.13 Some comorbidities included in EuroSCORE calculation were not collected for the BAG-RECALL population. A history of cardiac surgery and presence of extracardiac arteriopathy were not documented for our population. Preoperative tests of neurologic function were not performed; however, all patients met criteria for inclusion in BAG-RECALL, which excluded patients with significant neurological disease, and enrolled only those presenting for elective surgery. In addition, while the EuroSCORE stratifies patients with congestive heart failure into those with a cardiac EF between 30% and 50%, which is worth 1 EuroSCORE point, and those with an EF below 30%, which is worth 2 EuroSCORE points, patients in BAG-RECALL were stratified by whether their EF was above or below 40%. To address this, patients with an EF <40% were given 1.5 points for the purposes of calculating EuroSCORE and those with an EF ≥40% were given no additional points.

Intraoperative monitoring data, including vital signs, BIS values, and ETAC, were automatically archived every minute by our intraoperative anesthetic record documentation system (Metavision, iMDsoft, Needham, MA). All patients received invasive arterial blood pressure monitoring. Volatile anesthetic concentration was converted into age-adjusted MAC equivalents, summed across all volatile anesthetic drugs being delivered.14

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Statistical Analysis

Statistical analyses were performed in PASW Statistics version 18 (SPSS Statistics, IBM Corporation, Somers, NY) when not specifically stated. The primary outcome, comparison in delirium incidence between patients randomized to BIS-guided and ETAC-guided protocols, was assessed with a χ2 test. As enrollment to this substudy commenced toward the end of the BAG-RECALL trial, we were limited in recruitment number accordingly. We estimated that 300 patients could be enrolled in this substudy, which would provide 84% power with a 2-sided P value of 0.05 to detect an absolute reduction of 15% in delirium incidence between the 2 groups, assuming an incidence of 30% in 1 group.

The second aim of the study was to evaluate candidate variables for association with postoperative delirium. To reduce the probability of type 1 error, only 14 independent variables were considered, selected on the basis of a literature search and hypotheses generated by the study group. Continuous predictors were EuroSCORE, preoperative hemoglobin, duration of cardiopulmonary bypass, duration of mean arterial blood pressure < 75 mm Hg, duration of BIS <45, duration of concurrent mean arterial blood pressure <75 mm Hg, BIS <45, and ETAC <0.7 age-adjusted MAC, total midazolam dose (mcg/kg/hr of operation), total fentanyl dose (mcg/kg/hr of operation), total norepinephrine dose (mcg/kg/min), average ETAC during anesthetic maintenance, and number of units of donor packed red blood cells (pRBCs) administered intraoperatively. Dichotomous variables were whether the patient consumed ethanol daily,15 whether the ASA PS was >3, and whether the patient was allocated to the BIS or the ETAC group in the BAG-RECALL trial. Candidate variable data were complete for all participants.

The commonly used technique of establishing univariate relationships between predictors and the outcome of interest is flawed from a statistical perspective, resulting in unnecessary expansion of α error. The relatively small size of our dataset made it unlikely that, using typical stepwise binary logistic regression techniques, we would appropriately identify 1 single “best” model; small study populations with a large number of covariates are vulnerable to “overfitting,” or fitting to idiosyncrasies in the data rather than true population relationships.16 Thus, we used a Bayesian stochastic search variable selection (SSVS) approach17,18 to search over all possible main effect models (i.e., 214 = 16,384) and obtained posterior probability for each model to be the “true” model. SSVS was done with WinBUGS 1.4.3 ( This method also produces estimates of the probability for each independent variable to be in the “true” model, which we can use to rank the importance of independent variables. The SSVS method is an iterative algorithm using the Gibbs sampler that can be easily implemented in WinBUGS. O’Hara and Sillanpää19 discussed Bayesian variable selection techniques in their review.

After individual predictors were ranked according to their posterior probabilities, we conducted binary logistic regression with the top 5 predictors (all with posterior probability greater than 0.5). The model was used to generate predicted probabilities for calculation of a c-statistic to assess model fit, as well as to provide odds ratios associated with the candidate predictors.

A P value of <0.05 was considered to indicate statistical significance.

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Exploratory Post Hoc Meta-Analysis

Based on an approach suggested in The Lancet,20,21 we conducted a post hoc meta-analysis in which the findings of the current trial were combined meta-analytically with the 3 other randomized studies in noncardiac and nonthoracic surgical populations that have incorporated BIS-guided care as an intervention and have evaluated postoperative delirium as the primary outcome.6–8 A DerSimonian-Laird random effects meta-analysis was conducted using the R statistical environment (R Foundation for Statistical Computing, Vienna, Austria).

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From August 8, 2009 to April 19, 2010, 337 consecutive patients enrolled in the BAG-RECALL trial received treatment in the cardiothoracic ICU of our institution and were considered for inclusion in this substudy. Of those 337 patients, 13 (3.8%) had no documented delirium screens, 2 (0.6%) did not receive cardiac or thoracic surgery, and 12 (3.6%) had an incomplete electronic intraoperative record. Thus, 310 patients, all with at least 1 CAM-ICU assessment, are included in this substudy. (Fig. 1) Characteristics of the study group are in Appendix 1. Excluded patients were significantly younger than, but otherwise similar to, included patients.

Of the 310 patients in the substudy, 73 (23.5%) had a positive CAM-ICU assessment for delirium at least once during their care in the ICU. One hundred four patients (33.5%) were missing at least 1 documented CAM-ICU assessment within the first 3 days after surgery. Patients with missing data were no more or less likely to have had delirium (χ2 P = 0.394).

Of the 73 patients who were delirious during the study, 56 (76.7%) experienced only hypoactive delirium, 8 (11.0%) had both hyper- and hypoactive delirium (i.e., a mixed phenotype), and 5 (6.8%) had only hyperactive delirium. Another 4 patients did not have a documented Richmond Agitation and Sedation Scale score at the time of at least 1 episode of delirium, and their phenotype could not be conclusively determined.

A diagnosis of delirium in the ICU was associated with increased ICU and hospital length of stay and increased rates of mortality. ICU discharge occurred at a median of 2.0 days (95% confidence interval [CI], 1.7–2.3) postoperatively for those without delirium, and at 8.0 (95% CI, 7.1–8.9) days for those with delirium (P < 0.001). Hospital discharge occurred at a median of 7.0 days (95% CI, 6.4–7.6) vs 17.0 (95% CI, 14.3–19.7) days for those without and with delirium, respectively (P < 0.001). Excluding patients who died in hospital, patients without delirium were more likely to be alive at last follow-up (94.3% vs 84.1% for those who were nondelirious and delirious, respectively; P = 0.008).

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Incidence of Delirium in the BIS and ETAC Groups

Table 1 shows comparisons between patients in BIS and ETAC groups and suggests that randomization did result in balanced groups in this substudy. Of the 310 patients assessed, 28 of 149 (18.8%) in the BIS group and 45 of 161 (28.0%) in the ETAC group developed postoperative delirium in the ICU (odds ratio 0.60, 95% CI, 0.35–1.02, P = 0.058). Table 1 shows that patients in the BIS group also had a significantly shorter stay in the ICU.

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Delirium Prediction Model

Table 2 shows the characteristics of patients with and without delirium. The SSVS approach returned probabilities of the 14 candidate predictors for inclusion in the “true” model (Table 3). In order of importance to the model, those variables with >0.5 probability of inclusion, followed parenthetically by their exact probability of inclusion, were average maintenance ETAC (0.97), units of pRBCs (0.92), ASA PS 4 (vs 1, 2, or 3) (0.71), EuroSCORE (0.58), and norepinephrine dose in mcg/kg/min (0.56). In other words, ETAC and pRBCs were in nearly all of the SSVS models; EuroSCORE and norepinephrine dose were in approximately half the SSVS models.

A generalized additive logistic regression model analysis indicated that no transformations were necessary for those variables to achieve linearity with the logit (not shown). The 5 predictors together with randomization group (BIS or ETAC) were entered into binary logistic regression. The overall model was significant (P < 0.001), with a Nagelkerke R-square of 0.294. The Hosmer and Lemeshow lack-of-fit test was nonsignificant (P = 0.40), indicating appropriate model fit. Variance inflation factors (VIFs) were all <1.5; the average variance inflation factors was 1.16, indicating absence of substantive collinearity among the predictors. Independent predictors of postoperative delirium are in Table 4. Norepinephrine dose and randomization group were not significant in the model; however, average ETAC, units of pRBCs, ASA PS, and EuroSCORE were significant. A sensitivity analysis excluding patients undergoing thoracic surgery found substantively identical results (not shown).

A receiver operator characteristic curve was constructed using predicted probability of developing delirium as estimated by the binary logistic regression model. The c-statistic of the curve was 0.79 (95% CI, 0.74–0.85; P < 0.001), indicating a significant improvement in predictive power over chance.

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Exploratory Meta-Analysis

Meta-analysis of data from the 3 published trials and the present study (Table 5) demonstrates that BIS-guided anesthesia is associated with less risk of postoperative delirium (Fig. 2), with a summary odds ratio of 0.56 (95% CI, 0.42–0.73, heterogeneity P value = 0.54).

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We found a 9.2% nonsignificant reduction in postoperative delirium in the BIS-guided group, with both a raw and adjusted odds ratio of approximately 0.6 (Table 2, Table 4). This is consistent with other published trials (Table 5)6–8 which, taken together, demonstrate an odds ratio of 0.56 for BIS-guided anesthesia (Fig. 2). Because of the exploratory nature of the meta-analysis presented here, this finding must be viewed as preliminary. However, it does lend support to the need for a large trial to confirm or refute the effectiveness of BIS guidance in preventing delirium.

There are several plausible mechanisms by which BIS guidance could decrease postoperative delirium. One hypothesis is that electroencephalogram (EEG) or BIS guidance leads to avoidance or minimization of periods of EEG burst suppression or persistent suppression. These EEG patterns are not seen during physiological sleep and have been associated with adverse outcomes in ICU patients.22 Results from the SuDoCo clinical trial (ISRCTN36437985) suggested that percentage of time with an intraoperative burst suppression ratio higher than zero was an independent risk factor for postoperative delirium with an estimated hazard ratio of 2.5 (95% CI, 1.23–4.91, P value =0.01).8 When BIS values are below 20 to 30, the EEG burst suppression ratio is inversely correlated with the BIS and is probably a major determinant of the BIS.23 In the current trial, however, the patients randomized to the ETAC group and the patients who were delirious in the ICU did not have an increased proportion of intraoperative time with BIS <20 (Tables 1 and 2). Future research should attempt to clarify how intraoperative EEG-based monitoring could decrease postoperative delirium.

Four independent predictors of postoperative delirium were identified in this study: number of units of pRBCs administered intraoperatively, ASA PS, EuroSCORE, and average ETAC. ASA PS is a subjective measure of preoperative comorbidities and patient condition, while EuroSCORE is an objective measure of comorbidities and surgical risk. EuroSCORE has been identified as a significant, independent predictor of delirium risk in a cardiac surgical population, though neither study considered ASA PS.24,25 While some features of the EuroSCORE had to be estimated in our population, composite metrics reduce the risk of a type 1 error compared with including individual characteristics. EuroSCORE is a significant predictor of other adverse outcomes in cardiac surgical patients, including prolonged ICU length of stay26 and mortality, both in a large multicenter population27 and in a population from our institution.28 While the association between ASA PS and postoperative delirium has been better studied in noncardiac surgical populations,29,30 it is not surprising that ASA PS is related to postoperative delirium in this cardiothoracic surgical population as well. Furthermore, red blood cell transfusion has also been identified as a risk factor for postoperative delirium in cardiac surgical patients25,31 and was confirmed to be associated with delirium risk in our population.

One of the most interesting findings of this analysis was the association between average ETAC and postoperative delirium. There are 3 potential explanations for this finding. First, the simple interpretation is that administering increased volatile anesthetic concentration results in protection against delirium. A second, and in our view more likely, explanation is that there may be an epiphenomenal association, whereby patients who are at risk for delirium are also treated differently intraoperatively by the anesthesia professional providing their care, as manifested by relatively lower concentrations of administered anesthetic. Our findings are consistent with a third explanation that vulnerable patients receive a relative overdose of anesthetic drug and develop delirium. Although the dose they receive is less than that of patients who do not develop delirium, given the underlying susceptibility, it is nonetheless a relative overdose. However, if a relative overdose in vulnerable surgical patients were to increase the risk of postoperative delirium, we would expect regional anesthesia to be associated with a lower incidence of postoperative delirium than general anesthesia. A meta-analysis of small trials that randomized surgical patients to regional or general anesthesia surprisingly found no change in risk for delirium with general anesthesia (odds ratio, 0.88; 95% CI, 0.51–1.51).32

Patients with a high EuroSCORE, who were ASA PS 4, and who received more intraoperative blood transfusions, were more likely to become delirious, suggesting that delirious patients were more vulnerable to cardiovascular instability. We hypothesize that frailty is reflected in both the cardiovascular system and the brain as reduced “cognitive reserve,” which has been advanced as an encompassing theme common to many nonmodifiable risk factors for postoperative delirium.33 Thus, cardiovascular sensitivity to anesthesia, a situation in which anesthesia professionals may therapeutically decrease volatile anesthetic delivery rates, may characterize patients at particular risk for postoperative delirium because of concomitant cognitive vulnerability. This second hypothesis is not mutually exclusive with the third, wherein vulnerable patients receive a relative overdose of anesthesia even at concentrations much lower than those without unusual vulnerability. Biochemically, the idea of precipitating factors (e.g., surgical inflammation, anesthetic drugs) acting on a vulnerable substrate has been explored by Maclullich et al.34 as “maladaptive sickness behavior,” where an insult to a vulnerable limbic-hypothalamic-pituitary axis induces an inappropriate or uncontrolled stress response, manifested as delirium. Thus, patients with maladaptive stress responses may be those who are less likely to receive high concentrations of volatile anesthetics because of concomitant cardiovascular frailty.

The major limitation of this study is its small sample size, rendering it vulnerable to imprecise findings and type II error. Also, no baseline formal assessment for preexisting delirium or other cognitive screening was performed; however, patients enrolling in the BAG-RECALL trial participated in an informed consent discussion before their surgery and were deemed able to consent. Recent studies comparing CAM-ICU diagnoses of delirium with those made with DSM-IV criteria,35 the nursing delirium screen (Nu-DeSc),36 and even unstructured bedside nursing evaluation37 have found lower sensitivity than previously reported, particularly in verbal patients; thus, this study may tend to underestimate delirium rates. Missing CAM-ICU assessments in our study population also may have resulted in an underestimate of delirium rates. Liberal inclusion of candidate predictors in statistical models is also subject to criticism;16 however, we attempted to mitigate that effect by pursuing a SSVS strategy, avoiding the use of iterative logistic regression and using composite metrics when possible. Although our variables of interest were selected a priori, this statistically permissive approach produces a model which should be taken as hypothesis generating only. This was also a single-center study conducted at a quaternary care center, and our findings might not be readily generalizable to a lower-acuity cardiothoracic surgical population.

In summary, we did not find that randomization to the BIS or ETAC-guided protocols decreased postoperative delirium in this patient population, but the results remain consistent with previous findings suggesting that BIS guidance decreases delirium after major surgery. There is therefore a need for a large randomized study to clarify whether or not EEG-guided anesthesia, with BIS or an alternative method, decreases postoperative delirium, specifically after cardiac or thoracic surgery. Furthermore, the mechanism by which EEG guidance could decrease delirium requires elucidation. The average ETAC during anesthetic maintenance, intraoperative units of pRBCs administered, EuroSCORE, and ASA PS are significant independent predictors of postoperative delirium in a cardiothoracic surgical population. Some of these factors may be modifiable, and they may be usefully incorporated into clinical screens to identify patients who are at increased risk of delirium after cardiac and thoracic surgery.

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Name: Elizabeth L. Whitlock, MD, MSc.

Contribution: This author helped design and conduct the study, analyze the data, and write the manuscript.

Attestation: Elizabeth L. Whitlock has seen the original study data, reviewed the analysis of the data, approved the final manuscript, and is the author responsible for archiving the study files.

Name: Brian A. Torres, CRNA.

Contribution: This author helped design the study and conduct the study.

Attestation: Brian A. Torres has seen the original study data and approved the final manuscript.

Name: Nan Lin, PhD.

Contribution: This author helped design the study and analyze the data.

Attestation: Nan Lin has seen the original study data, reviewed the analysis of the data, and approved the final manuscript.

Name: Daniel L. Helsten, MD.

Contribution: This author helped design and conduct the study and analyze the data.

Attestation: Daniel L. Helsten has seen the original study data, reviewed the analysis of the data, and approved the final manuscript.

Name: Molly R. Nadelson, MD.

Role: This author helped write the manuscript.

Attestation: Molly R. Nadelson approved the final manuscript.

Name: George A. Mashour, MD, PhD.

Contribution: This author helped design the study, analyze the data, and write the manuscript.

Attestation: George A. Mashour has seen the original study data, reviewed the analysis of the data, and approved the final manuscript.

Name: Michael S. Avidan, MB, BCh, FCASA.

Contribution: This author helped design and conduct the study, analyze the data, and write the manuscript.

Attestation: Michael S. Avidan has seen the original study data, reviewed the analysis of the data, and approved the final manuscript.

This manuscript was handled by: Gregory J. Crosby, MD.

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The authors thank David Kao who performed the meta-analysis. ELW thanks Jay Piccirillo, MD, FACS, for his support and guidance.

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1. Saczynski JS, Marcantonio ER, Quach L, Fong TG, Gross A, Inouye SK, Jones RN. Cognitive trajectories after postoperative delirium. N Engl J Med. 2012;367:30–9
2. Rudolph JL, Inouye SK, Jones RN, Yang FM, Fong TG, Levkoff SE, Marcantonio ER. Delirium: an independent predictor of functional decline after cardiac surgery. J Am Geriatr Soc. 2010;58:643–9
3. Gottesman RF, Grega MA, Bailey MM, Pham LD, Zeger SL, Baumgartner WA, Selnes OA, McKhann GM. Delirium after coronary artery bypass graft surgery and late mortality. Ann Neurol. 2010;67:338–44
4. Franco K, Litaker D, Locala J, Bronson D. The cost of delirium in the surgical patient. Psychosomatics. 2001;42:68–73
5. Marcantonio ER. Postoperative delirium: a 76-year-old woman with delirium following surgery. JAMA. 2012;308:73–81
6. Chan MT, Cheng BC, Lee TM, Gin TCODA Trial Group. . BIS-guided anesthesia decreases postoperative delirium and cognitive decline. J Neurosurg Anesthesiol. 2013;25:33–42
7. Sieber FE, Zakriya KJ, Gottschalk A, Blute MR, Lee HB, Rosenberg PB, Mears SC. Sedation depth during spinal anesthesia and the development of postoperative delirium in elderly patients undergoing hip fracture repair. Mayo Clin Proc. 2010;85:18–26
8. Radtke FM, Franck M, Lendner J, Krüger S, Wernecke KD, Spies CD. Monitoring depth of anaesthesia in a randomized trial decreases the rate of postoperative delirium but not postoperative cognitive dysfunction. Br J Anaesth. 2013;110(Suppl 1):i98–105
9. Siepe M, Pfeiffer T, Gieringer A, Zemann S, Benk C, Schlensak C, Beyersdorf F. Increased systemic perfusion pressure during cardiopulmonary bypass is associated with less early postoperative cognitive dysfunction and delirium. Eur J Cardiothorac Surg. 2011;40:200–7
10. Avidan MS, Jacobsohn E, Glick D, Burnside BA, Zhang L, Villafranca A, Karl L, Kamal S, Torres B, O’Connor M, Evers AS, Gradwohl S, Lin N, Palanca BJ, Mashour GABAG-RECALL Research Group. . Prevention of intraoperative awareness in a high-risk surgical population. N Engl J Med. 2011;365:591–600
11. Ely EW, Inouye SK, Bernard GR, Gordon S, Francis J, May L, Truman B, Speroff T, Gautam S, Margolin R, Hart RP, Dittus R. Delirium in mechanically ventilated patients: validity and reliability of the confusion assessment method for the intensive care unit (CAM-ICU). JAMA. 2001;286:2703–10
12. Sessler CN, Gosnell MS, Grap MJ, Brophy GM, O’Neal PV, Keane KA, Tesoro EP, Elswick RK. The Richmond Agitation-Sedation Scale: validity and reliability in adult intensive care unit patients. Am J Respir Crit Care Med. 2002;166:1338–44
13. Roques F, Nashef SA, Michel P, Gauducheau E, de Vincentiis C, Baudet E, Cortina J, David M, Faichney A, Gabrielle F, Gams E, Harjula A, Jones MT, Pintor PP, Salamon R, Thulin L. Risk factors and outcome in European cardiac surgery: analysis of the EuroSCORE multinational database of 19030 patients. Eur J Cardiothorac Surg. 1999;15:816–22
14. Nickalls RW, Mapleson WW. Age-related iso-MAC charts for isoflurane, sevoflurane and desflurane in man. Br J Anaesth. 2003;91:170–4
15. Marcantonio ER, Goldman L, Mangione CM, Ludwig LE, Muraca B, Haslauer CM, Donaldson MC, Whittemore AD, Sugarbaker DJ, Poss R. A clinical prediction rule for delirium after elective noncardiac surgery. JAMA. 1994;271:134–9
16. Babyak MA. What you see may not be what you get: a brief, nontechnical introduction to overfitting in regression-type models. Psychosom Med. 2004;66:411–21
17. George EI, McCulloch RE. Variable selection via Gibbs sampling. J Am Stat Assoc. 1993;88:881––9
18. Kuo L, Mallick B. Variable selection for regression models. Sankhya: the Indian Journal of Statistics. 1998;60:65–81
19. O’Hara RB, Sillanpää MJ. A review of Bayesian variable selection methods: what, how and which. Bayesian Analysis. 2009;4:85–118
20. Clark S, Horton R. Putting research into context–revisited. Lancet. 2010;376:10–1
21. Ellis P, Barrett-Lee P, Johnson L, Cameron D, Wardley A, O’Reilly S, Verrill M, Smith I, Yarnold J, Coleman R, Earl H, Canney P, Twelves C, Poole C, Bloomfield D, Hopwood P, Johnston S, Dowsett M, Bartlett JM, Ellis I, Peckitt C, Hall E, Bliss JMTACT Trial Management Group; TACT Trialists. . Sequential docetaxel as adjuvant chemotherapy for early breast cancer (TACT): an open-label, phase III, randomised controlled trial. Lancet. 2009;373:1681–92
22. Watson PL, Shintani AK, Tyson R, Pandharipande PP, Pun BT, Ely EW. Presence of electroencephalogram burst suppression in sedated, critically ill patients is associated with increased mortality. Crit Care Med. 2008;36:3171–7
23. Morimoto Y, Hagihira S, Koizumi Y, Ishida K, Matsumoto M, Sakabe T. The relationship between bispectral index and electroencephalographic parameters during isoflurane anesthesia. Anesth Analg. 2004;98:1336–40
24. Koster S, Oosterveld FG, Hensens AG, Wijma A, van der Palen J. Delirium after cardiac surgery and predictive validity of a risk checklist. Ann Thorac Surg. 2008;86:1883–7
25. Norkiene I, Ringaitiene D, Misiuriene I, Samalavicius R, Bubulis R, Baublys A, Uzdavinys G. Incidence and precipitating factors of delirium after coronary artery bypass grafting. Scand Cardiovasc J. 2007;41:180–5
26. Ettema RG, Peelen LM, Schuurmans MJ, Nierich AP, Kalkman CJ, Moons KG. Prediction models for prolonged intensive care unit stay after cardiac surgery: systematic review and validation study. Circulation. 2010;122:682–9
27. Nashef SA, Roques F, Michel P, Gauducheau E, Lemeshow S, Salamon R. European system for cardiac operative risk evaluation (EuroSCORE). Eur J Cardiothorac Surg. 1999;16:9–13
28. Kertai MD, Pal N, Palanca BJ, Lin N, Searleman SA, Zhang L, Burnside BA, Finkel KJ, Avidan MSB-Unaware Study Group. . Association of perioperative risk factors and cumulative duration of low bispectral index with intermediate-term mortality after cardiac surgery in the B-Unaware Trial. Anesthesiology. 2010;112:1116–27
29. Brouquet A, Cudennec T, Benoist S, Moulias S, Beauchet A, Penna C, Teillet L, Nordlinger B. Impaired mobility, ASA status and administration of tramadol are risk factors for postoperative delirium in patients aged 75 years or more after major abdominal surgery. Ann Surg. 2010;251:759–65
30. Zakriya KJ, Christmas C, Wenz JF Sr, Franckowiak S, Anderson R, Sieber FE. Preoperative factors associated with postoperative change in confusion assessment method score in hip fracture patients. Anesth Analg. 2002;94:1628–32
31. Bucerius J, Gummert JF, Walther T, Schmitt DV, Doll N, Falk V, Mohr FW. On-pump versus off-pump coronary artery bypass grafting: impact on postoperative renal failure requiring renal replacement therapy. Ann Thorac Surg. 2004;77:1250–6
32. Mason SE, Noel-Storr A, Ritchie CW. The impact of general and regional anesthesia on the incidence of post-operative cognitive dysfunction and post-operative delirium: a systematic review with meta-analysis. J Alzheimers Dis. 2010;22(Suppl 3):67–79
33. Jones RN, Fong TG, Metzger E, Tulebaev S, Yang FM, Alsop DC, Marcantonio ER, Cupples LA, Gottlieb G, Inouye SK. Aging, brain disease, and reserve: implications for delirium. Am J Geriatr Psychiatry. 2010;18:117–27
34. Maclullich AM, Ferguson KJ, Miller T, de Rooij SE, Cunningham C. Unravelling the pathophysiology of delirium: a focus on the role of aberrant stress responses. J Psychosom Res. 2008;65:229–38
35. van Eijk MM, van den Boogaard M, van Marum RJ, Benner P, Eikelenboom P, Honing ML, van der Hoven B, Horn J, Izaks GJ, Kalf A, Karakus A, Klijn IA, Kuiper MA, de Leeuw FE, de Man T, van der Mast RC, Osse RJ, de Rooij SE, Spronk PE, van der Voort PH, van Gool WA, Slooter AJ. Routine use of the confusion assessment method for the intensive care unit: a multicenter study. Am J Respir Crit Care Med. 2011;184:340–4
36. Neufeld KJ, Leoutsakos JS, Sieber FE, Joshi D, Wanamaker BL, Rios-Robles J, Needham DM. Evaluation of two delirium screening tools for detecting post-operative delirium in the elderly. Br J Anaesth. 2013;111:612–8
37. Reade MC, Eastwood GM, Peck L, Bellomo R, Baldwin I. Routine use of the confusion assessment method for the intensive care unit (CAM-ICU) by bedside nurses may underdiagnose delirium. Crit Care Resusc. 2011;13:217–24
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