PMCCPMCCPMCC

Search tips
Search criteria 

Advanced

 
Logo of nihpaAbout Author manuscriptsSubmit a manuscriptHHS Public Access; Author Manuscript; Accepted for publication in peer reviewed journal;
 
Anesthesiology. Author manuscript; available in PMC 2010 April 1.
Published in final edited form as:
Anesthesiology. 2009 April; 110(4): 781–787.
PMCID: PMC2757787
NIHMSID: NIHMS131214

Executive Function and Depression as Independent Risk Factors for Postoperative Delirium

Patrick J. Smith, MA, Graduate Student,a Deborah K. Attix, PhD, Associate Professor,a,b B. Craig Weldon, MD, Associate Professor,c,d Nathaniel H. Greene, BS, Medical Student,c and Terri G. Monk, MD, MS, Professord,e

Abstract

Background

Postoperative delirium has been associated with greater complications, medical cost, and increased mortality during hospitalization. Recent evidence suggests that preoperative executive dysfunction and depression may predict postoperative delirium; however, the combined effect of these risk factors remains unknown. We therefore examined the association between preoperative executive function, depressive symptoms, and established clinical predictors of postoperative delirium among 998 consecutive patients undergoing major non-cardiac surgery.

Methods

Nine hundred ninety eight patients were screened for postoperative delirium (n = 998) using the Confusion Assessment Method as well as through retrospective chart review. Patients underwent cognitive, psychosocial, and medical assessments preoperatively. Executive function was assessed using the Concept Shifting Task, Letter-Digit Coding, and a modified Stroop Color Word Interference Test. Depression was assessed by the Beck Depression Inventory.

Results

Preoperative executive dysfunction (P = .007) and greater levels of depressive symptoms (P = .049) were associated with a greater incidence of postoperative delirium, independent of other risk factors. Secondary analyses of cognitive performance demonstrated that the Stroop Color Word Interference Test, the executive task with the greatest complexity in this battery, was more strongly associated with postoperative delirium than simpler tests of executive function. Furthermore, patients exhibiting both executive dysfunction and clinically significant levels of depression were at greatest risk for developing delirium postoperatively.

Conclusions

Preoperative executive dysfunction and depressive symptoms were predictive of postoperative delirium among non-cardiac surgical patients. Executive tasks with greater complexity are more strongly associated with postoperative delirium relative to tests of basic sequencing.

Introduction

Postoperative delirium occurs in 5-15% of patients following noncardiac surgery1,2 and is associated with a 3- to 11-fold increase in mortality during the subsequent 6 months3-5. Accordingly, there is an increasing need to examine clinical risk factors of delirium in order to identify individuals in need of prophylactic intervention 2. Although risk factors for postoperative delirium vary between studies, preoperative age, depression, alcohol use, medical co-morbidities, and cognitive impairment appear to confer a greater risk of postoperative delirium6.

Recent evidence suggests that preoperative cognitive and psychosocial dysfunction may predict postoperative delirium among individuals without clinically significant impairments 7,8. Although it is well recognized that individuals with compromised cognitive ability preoperatively (e.g. dementia) 9,10 are at greater risk of delirium, recent evidence suggests that decrements in higher-order cognitive functions, such as executive function, may predict postoperative delirium in the absence of frank cognitive impairment 7. Similarly, subclinical levels of depression may predict delirium following major noncardiac surgery, independent of traditional risk factors 8. A companion article in this issue by Greene and colleagues suggests that the combination of preoperative depression and executive dysfunction has the highest positive predictive value for postoperative delirium, relative to the presence of either risk factor by itself 11.

Executive dysfunction has been variably defined as difficulty carrying out complex tasks, inability to successfully engage in problem-solving behaviors, and difficulty engaging in independent, purposeful actions 12. Compromises in processing speed, and in complex sequencing and reasoning, are common among those with executive deficits. Executive dysfunction is common among individuals with depression 13,14 and is associated with greater cardiovascular risk factors 14 regardless of cardiac acuity 15,16. In addition, white matter degradation has been prospectively associated with greater severity of executive dysfunction 17,18 and depressive symptoms 19. Furthermore, recent studies reporting that depression predicts postoperative delirium have demonstrated that the severity of executive dysfunction parallels depression severity, underscoring the need to clarify this potentially confounding relationship 8. Despite recent findings demonstrating a relationship between executive dysfunction, depression, and delirium, few studies have examined the independent predictive abilities of these interrelated factors on delirium, or considered them along with clinical variables known to increase delirium risk.

Materials and Methods

Patient Sample

After approval by the University of Florida Institutional Review Board in Gainesville, Florida, patients were enrolled in a previous reported trial examining predictors of postoperative cognitive decline 20. Patients were approached for participation at Shands Hospital (Gainesville, Florida) between February 1, 1999, and January 31, 2002, and gave written informed consent prior to participation. Inclusion criteria included adult age (≥ 18 years) and a scheduled hospital admission as an inpatient for a minimum of 2 days following noncardiac surgery. Notably, patients with a mini mental status exam score of 23 or less 21 or a history of dementia or any disease of the central nervous system were excluded. Patients with current or past history of psychiatric illness of thought disorders, bipolar disorder, or substance abuse disorders were also excluded as were patients with current major depression requiring psychiatric management or current or past electroconvulsive therapy. Individuals undergoing active pharmacologic management by a psychiatrist (including tranquilizers and/or anti-depressants) were also excluded.

Preoperative Evaluation

All subjects were interviewed within 14 days of surgery to obtain information regarding demographic status, medical history, education, and employment status 20. Current medications, alcohol use, smoking history, previous surgical and psychiatric histories were also recorded. Severity of postoperative pain was assessed using the numerical rating scale for pain, which rates pain on a 0-10 scale with 0 indicating no pain, and 10 indicating severe pain 22. Medical comorbidities were indexed using the Charlson comorbidity score, which provides a weighted index including both the number and the seriousness of co-morbid medical conditions 23.

Delirium

Delirium status was assessed with chart review and/or the Confusion Assessment Measure 24. Results did not differ substantively between delirium assessment methodologies. The Confusion Assessment Method diagnostic algorithm was used to define the presence or absence of delirium at each assessment, monitored up to eight days postoperatively. Delirium was defined as the presence of both 1) acute onset and fluctuating course, and 2) inattention, as well as either 3) disorganized thinking, or 4) altered level of consciousness.

Neuropsychological Performance

Neuropsychological performance was assessed using a standardized battery of cognitive measures that have been previously reported 20. The instruments used in this analysis were:

Concept Shifting Task 25 part C, based on the Trail Making Test. This task requires patients to draw consecutive lines alternating back and forth between the numbers 1 through 8 and the letters A through H. This task is simpler than the Trail Making Test, as the sequence involves fewer letters/numbers and the stimuli occur in a straightforward, circular array. The score is the time in seconds required for completion.

Letter-Digit Coding 26 based on the Digit-Symbol Substitution subtest of the Wechsler Adult Intelligence Scale III. This task requires rapid sequencing of digits and letters symbols. This task also is simpler than the Digit-Symbol Substitution subtest it is based upon, as the pairs of letters and numbers may be easier to encode than pairs of digits and abstract symbols. In this task, the subject is given a key grid of numbers and corresponding letters, and a test grid with letters and empty boxes. The subject fills in as many of the empty boxes with the numbers that correspond to the printed letters in one minute.

Modified Stroop Interference Task 27 is based on the Stroop Test. In the word trial, the subject reads words, all of which are colors (e.g., blue, green), printed in black ink. In the color trial, the subject next identifies colors than appear as colored rectangles. Finally, in the color/word trial, the subject must rapidly identify the printed color that the color words (e.g., blue, green) are printed in, which requires suppressing the reading of the color word. It is the time to complete this third response inhibition trial that is used for analysis.

Depression

Depressive symptoms were assessed using the Beck Depression Inventory (BDI) 28,29. The BDI is a standardized 21-item self-report questionnaire consisting of symptoms and attitudes related to depression, including items such as self-dislike, suicidal ideation, insomnia, and sadness. The items are summed with total scores ranging from 0 to 63, with higher scores indicating higher levels of depression. The BDI has been shown to be a valid and reliable measure of depression severity with robust psychometric properties among patient and normal populations, across a wide range of age groups 30.

Statistical Analysis

Data Reduction

In order to characterize the sample and those who did versus did not develop delirium, preoperative demographic and background differences between delirium groups were evaluated using t-tests for continuous variables and chi-square tests for categorical variables. For analysis of executive function as a potential predictor, a composite Z-score of executive function was created for each individual. Use of a composite minimized both the number of statistical tests in the present analysis and type-I error inflation due to significant intercorrelations between executive function measures (r's ≥ .56, P's <.0001) 31. First, subject scores for each measure were transformed to Z-scores using the sample mean and standard deviation. All three z-scores were then summed to form the executive function composite. Prior to calculating the Z-scores, we ensured that the direction of each individual test Z-scores reflected the same level of performance, i.e., the higher the Z-score the better the performance. The composite score is calculated as the sum of the Z-scores for each individual measure, combined within individuals. This unit-weighted composite was then used as a predictor variable in the primary logistic regression model described below.

Data Analysis

General linear modeling equations using SAS programming (Cary, NC) were used for all analyses. Sample size determination has been previously reported 20. Briefly, the present study from which this data was drawn was powered for the purposes of examining differences in postoperative cognitive decline between elderly and middle-aged / younger patients and data on delirium was collected as a secondary endpoint. Assuming a 40% rate of mild preoperative depressive symptoms among non-delirious patients 8 and a two-sided test at alpha=.05 for this secondary analysis, we determined that we would have a power of 80% to detect a difference of 24% in the proportion of delirious patients exhibiting mild preoperative depressive symptoms. Using Beck's criteria 28, we observed a 27.3% difference in the presence of mild depressive symptoms among individuals who developed delirium postoperatively.

The primary analysis consisted of a logistic regression. In order to avoid inflation of type-I error rates associated with step-wise regression, all covariates were selected a priori and were entered simultaneously 32. Covariates included age, years of education, Charlson co-morbidity scale, alcohol consumption (drinks per week), pain, and depressive symptoms. These covariates were chosen as they are empirically validated predictors of delirium 6. As a secondary analysis, the predictive ability of individual executive measures was examined in both unadjusted and adjusted analyses. Exploratory analyses were conducted to examine the additive effects of executive dysfunction and clinically significant depression. Continuous predictors were standardized using the sample standard deviation. This rescaling preserves the continuous nature of the predictor but places the regression coefficient on a clinically meaningful scale.

Results

Patient Characteristics

Complete patient data were available for 998 subjects. As previously reported 20, 1,496 were assessed for eligibility with 267 refusing to participate and 165 not meeting inclusion criteria. Additionally, 66 patients did not have complete delirium data. Participants in the final sample ranged in age from 18 to 90 (mean age = 51.0 years, SD = 17.0), reported 13.5 years of education (SD = 2.6), and the majority of participants were female (63.4%) and Caucasian (89.3%). Consistent with inclusion criteria, patients in our sample exhibited minimal levels of depressive symptoms (mean BDI = 6.9, SD = 6.6). Based on the level of depressive symptomatology endorsed (using Beck's criteria 28), 74.4% of the patients endorsed minimal, 19.7% endorsed mild, 4.6% endorsed moderated, and 1.3% endorsed severe symptoms of depression. Delirium occurred in 3.5% of patients and was more common among individuals ≥ 65 years of age (n = 21, 8.0%; χ2 = 21.24, P <.001). We did not observe any differences in rate of postoperative delirium between inhalational vs. intravenous anesthesia (P = .457), intraoperative use of nitrous oxide (P = .539), or body mass index (P = .138).

As shown in Table 1, patients who developed delirium were older (P < .001), exhibited greater medical co-morbidities (P < .001), had a greater prevalence of heart disease (P < .001), and had a higher rate of Benzodiazepine use (P = .009) relative to their non-delirious counterparts. Patients were also assessed specifically for a history of depression. Patients who developed postoperative delirium were also more likely to report a history of depression (P = .007). Patients developing postoperative delirium exhibited poorer performance on all executive function tasks at baseline: Concept Shifting (P = .013), Letter-Digit Coding (P < .001), and Stroop (P < .001).

Table 1
Demographic and clinical characteristics of patient sample*. Values represent mean, SD unless otherwise indicated.

Predictors of Postoperative Delirium

Regression analyses were then conducted to investigate the independent contributions of selected predictors when considered simultaneously. After adjustment for a priori selected covariates (see Table 1 for variables included), older age (P = .019), greater medical co-morbidities (P = .036), higher levels of depressive symptoms (P = .049), and poorer executive function (P = .007) continued to predict postoperative delirium (Table 2).

Table 2
Results of multivariable linear regression model predicting postoperative delirium

Executive Function Predictors of Delirium

Post-hoc examination of the predictive ability of individual executive function measures is shown in Table 3. As shown, all executive function measures were predictive of delirium in unadjusted analyses (P's < .013). After adjusting for age, education, medical co-morbidities, alcohol consumption, pain, and depressive symptoms, poorer performance on the modified Stroop task was the only index of executive function that predicted postoperative delirium (P = .006).

Table 3
Results of multivariable linear regression model predicting postoperative delirium

Additive Effects of Depression and Executive Dysfunction

Exploratory analyses were conducted in order to assess the additive effects of clinically significant depression among individuals exhibiting executive dysfunction. Clinically significant depression was defined based on previously established clinical cut-offs (BDI ≥ 14) and executive dysfunction was defined as ≥ 60 seconds for completion of the modified Stroop task (corresponding to the 20th percentile of the sample performance, approximately). Delirium risk was defined as `low' (neither executive dysfunction nor depression), `moderate' (either executive dysfunction or depression, but not both), or `high' (both executive dysfunction and depression). Results demonstrated that the prevalence of delirium increased with risk, such that individuals at `low', `moderate', and `high' risk exhibited delirium rates of 2.8%, 4.7%, and 12.0%, respectively (χ2 = 5.78, P <.016).

Discussion

These findings parallel those obtained by Greene and colleagues (11) in the companion article found in this issue. In the present sample, we again found that poorer executive function and higher levels of depressive symptoms were associated with an increased incidence of postoperative delirium among patients undergoing major non-cardiac surgery. We also found that, consistent with previous studies, greater age and medical co-morbidities were also associated with an increased risk of delirium, in addition to the independent risk introduced by executive and affective factors. Secondary analysis suggested that the association between executive function and incidence of delirium was strongest on tasks associated with greater complexity, such as the Stroop Color Word Test. In contrast, performance on executive tasks with limited sequencing requirements, such as the Concept Shifting and Letter-Digit Coding tasks, were not associated with increased delirium risk.

Our findings in a robust sample of approximately 1,000 patients of various ages are similar to those of Greene and colleagues' 11. We specifically demonstrate that executive function and depressive symptoms contribute unique information in assessing delirium risk among non-cardiac surgical patients, independent of age and co-morbidity effects. Although these studies varied in the diversity of executive tasks administered and analytical strategies, both found executive task complexity to be an important determinant of its predictive strength.

Our finding that poorer executive function was associated with increased likelihood of delirium is consistent with previous studies demonstrating an association between preoperative cognitive impairment and postoperative delirium. In a systematic literature review, Dasgupta and Dumbrell 6 found that preoperative cognitive impairment was a consistent predictor of postoperative delirium across numerous patient samples. Moreover, the relationship between cognitive impairment and delirium was predictive across studies, regardless of other variables considered. Recent studies among cardiac patients indicate that decrements in higher-order cognitive functions, such as executive function, may predict postoperative delirium even among patient samples without cognitive compromise. Rudolph and colleagues 7 recently found that executive dysfunction was associated with a greater incidence of delirium among 80 cardiac patients undergoing coronary artery bypass grafting or coronary artery bypass grafting-valve surgery. Notably, this association remained after controlling for other domains of cognitive function, including memory and general mental status, indicating that the effects are specific to the domain of executive function.

Our finding that greater levels of depressive symptoms may be associated with increased risk of delirium is consistent with previous findings among older adults 8,33,34. McAvay and colleagues 33 found that higher levels of depression, indexed using the Geriatric Depression Scale, were associated with increased delirium incidence among 412 individuals aged 70 years or older participating in the Delirium Prevention Trial. Galanakis and colleagues 34 reported similar findings among individuals aged 60 or older, demonstrating that higher levels of depression predicted delirium after adjustment for clinical predictors such as age and previous cognitive impairment. Similarly, Leung and colleagues 8 found that greater preoperative depression levels were associated with an increased incidence and longer duration of postoperative delirium among older individuals undergoing major, noncardiac surgery. Results of the present analysis therefore extend existing findings by demonstrating that preoperative depressive symptoms may predict postoperative delirium independent of age, and that executive dysfunction and depression independently increase the risk of delirium among noncardiac surgical patients.

Our finding that depressive symptoms predicted postoperative delirium is notable given that individuals currently undergoing psychiatric treatment or reporting a history of severe depression requiring electroconvulsive therapy treatment were excluded from our study sample, consistent with previous studies 35. It is possible that patients in our study not actively receiving treatment for depression may have had a recent history of major depression, or may have been actively experiencing subthreshold depressive symptoms during their preoperative assessments. This is consistent with previous studies demonstrating that the majority of depressed individuals will experience recurring episodes throughout their lifetimes 36,37. Subclinical depression is defined as depressive symptomatology of either insufficient frequency or severity to meet diagnostic criteria for major depressive disorder 38. Subclinical levels of depression, although less severe, have garnered recent attention as emerging evidence suggests that subclinical levels of depression may predict later episodes of full-blown depressive disorders 36 and have been shown to predict postoperative delirium in some studies 8. It is therefore not surprising that individuals exhibiting depressive symptoms preoperatively showed a greater vulnerability for developing delirium postoperatively in our sample, despite the exclusion of individuals undergoing active treatment for depression. Given the restricted range of depressive symptoms in our sample due to our exclusion of severely depressed individuals, we suspect that future studies incorporating patients with greater levels of depression will find similar, if not stronger, associations with delirium. Our findings provide evidence that subclinical depression represents a significant risk factor for delirium, which is compelling 39.

Our findings also provide preliminary evidence that tasks of executive function with greater complexity may have enhanced predictive utility relative to tasks relying more heavily on straightforward sequencing abilities. As an illustrative point among patients in the current sample, a 10-second slower score on the modified Stroop task conferred an increased risk of delirium comparable to an increase of 8 years in age (odds ratio = 1.531 (1.275 - 1.839) and odds ratio = 1.534 (1.238 - 1.900), respectively), controlling for the covariates included in our primary analyses. This finding is not surprising given that executive dysfunction has been shown to mediate age-related cognitive deterioration 40 and overlaps substantially with basic sequencing skills in some samples 12. The degree of complexity varies across executive measures, with some tasks tapping more basic attentional processes while others draw upon more complex reasoning, inhibition, or sequencing skills. There is evidence to suggest that the more complex executive tasks require the synthesis of information from multiple brain systems including cortical and subcortical areas associated with attention, working memory, and speed of processing 41.

In our study, the results of exploratory regression analyses of the separate measures revealed that the more complex response inhibition task was the only executive measure that remained an independent predictor among the other risk factors of depression, age, and comorbidities. In contrast, the simpler, more straightforward tasks did not remain as independent predictors. It is interesting to note that the methodology utilized by Greene and colleagues also identified the executive task with greater complexity as the most predictive of postoperative delirium 11. In that study, the investigators considered all of the executive measures simultaneously to identify which measure was most predictive, and also found that the task with the most complexity was independently related to delirium, as was depression. Further study of which executive tasks best predict delirium across studies is necessary in order to improve instrument selection for use in clinical samples.

Delirium is associated with significant reductions in global cerebral blood flow and systemic neurotransmitter dysfunction 42. Although the pathophysiology of delirium is multifactorial, the Gamma-Aminobutyric Acid, acetylcholine 43, and serotonin neurotransmitter systems appear to be principally involved 44. Recent evidence suggests that dysregulation in the homeostasis of tryptophan, the precursor to serotonin, may play a critical role in the pathogenesis of postoperative delirium 45. Because abnormalities in the regulation of serotonin have been consistently linked with depression 46, this may have important implications for elucidating the depression and delirium relationship. Future studies should examine the pathophysiologic mechanisms responsible for post-operative delirium and interventions to prevent its occurrence47.

It is also possible that occult white matter damage to the frontal-striatal areas of the brain predisposes some patients to develop delirium. It is not inconceivable that such mild white matter decrements could manifest preoperatively by decreased executive performance and/or greater levels of depression. This hypothesis is supported by the conclusion from recent coronary artery bypass grafting studies that the executive dysfunction and delirium relationship may be mediated by severity of atherosclerosis 7. Furthermore, abnormalities in the frontal-striatal circuitry have been previously shown to predict delirium among depressed individuals following electro-convulsive therapy 48 and are associated with executive deficits in a variety of patient populations 49,50. Again, the relationship between these factors and their independent and joint effects on delirium warrant further study.

Results from the present study should be viewed with the following limitations in mind. First, since our enrollment criteria excluded individuals with a prior history of specific psychiatric illnesses as well as patients under psychiatric care it is possible that our analyses of depressive symptoms were underpowered due to a restricted range of depressive symptoms in our sample. Therefore, our finding that depressive symptoms may predict postoperative delirium despite the limited range under examination underscores the need for future studies to investigate this relationship, as this association may be stronger among samples with more inclusive recruitment practices. However, even in this restrictive sample, the relationship between depressive symptoms and the development of postoperative delirium emerged clearly. In addition to the significance of current symptomatology to delirium risk, it is also interesting that those that developed delirium were also 2.5 times more likely to report having had a history of depression than those that did not develop delirium (31.4% vs. 14.8%, odds ratio = 2.65, P = .007). Our enrollment criteria also excluded individuals with cognitive impairment (defined as mini mental status exam < 23), restricting the range of our executive function variable in a similar manner. It is unclear, for example, how the executive measures used in our study would have functioned in a sample incorporating individuals with significant cognitive impairment or dementia. Second, the observed rates of delirium differed between our and Greene and colleagues 11 findings, most likely due to differences in patient populations. Finally, our multivariate selected multivariate model included more covariates than would have ideally been preferred given the small number of delirium cases in our study. However, it has been recommended by authorities in this area that a priori selected modeling is preferable to stepwise techniques 32 and recent simulation studies have demonstrated that this reduced number of events per variable provides adequate model estimates 51.

In summary, poorer executive function and greater levels of depressive symptoms were associated with a greater incidence of postoperative delirium among following major noncardiac surgery. Moreover, these effects persisted after adjustment for established risk factors of delirium. Secondary analyses indicated that the vulnerability to delirium exhibited on executive tasks may only be evidenced on tests associated with greater complexity. Future studies should systematically examine the predictive ability of individual executive measures in order to establish the most reliable and valid instruments by which to identify at-risk individuals preoperatively. Further study of the predictive ability of executive function measures among cognitively impaired patients is also warranted, as our sample excluded individuals with cognitive compromise or dementia. Furthermore, future studies should examine the effects of prophylactic interventions among patients exhibiting executive dysfunction to prevent postoperative delirium.

Acknowledgments

Supported by the National Institute on Aging (Grant K01-AG19214), Bethesda MD, USA;; Anesthesia Patient Safety Foundation, Indianapolis, IN; and I. Heermann Anesthesia Foundation, Inc., Gainesville, FL

Footnotes

Work should be attributed to the Department of Anesthesiology at the University of Florida, Gainesville, FL

Summary Statement: Although delirium is common postoperatively and is associated with significant mortality, clinical predictors among non-demented patients remain elusive. This prospective study of 998 non-demented patients demonstrates that preoperative executive dysfunction and depression independently predict delirium.

Reference List

1. 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: The Journal of the American Medical Association. 1994;271:134–9. [PubMed]
2. Demeure MJ, Fain MJ. The elderly surgical patient and postoperative delirium. J Am Coll Surg. 2006;203:752–7. [PubMed]
3. Lin SM, Liu CY, Wang CH, Lin HC, Huang CD, Huang PY, Fang YF, Shieh MH, Kuo HP. The impact of delirium on the survival of mechanically ventilated patients. Crit Care Med. 2004;32:2254–9. [PubMed]
4. Ely EW, Shintani A, Truman B, Speroff T, Gordon SM, Harrell FE, Jr., Inouye SK, Bernard GR, Dittus RS. Delirium as a predictor of mortality in mechanically ventilated patients in the intensive care unit. JAMA: The Journal of the American Medical Association. 2004;291:1753–62. [PubMed]
5. Cole MG. Delirium in elderly patients. Am J Geriatr Psychiatry. 2004;12:7–21. [PubMed]
6. Dasgupta M, Dumbrell AC. Preoperative risk assessment for delirium after noncardiac surgery: a systematic review. J Am Geriatr Soc. 2006;54:1578–89. [PubMed]
7. Rudolph JL, Jones RN, Grande LJ, Milberg WP, King EG, Lipsitz LA, Levkoff SE, Marcantonio ER. Impaired executive function is associated with delirium after coronary artery bypass graft surgery. J Am Geriatr Soc. 2006;54:937–41. [PMC free article] [PubMed]
8. Leung JM, Sands LP, Mullen EA, Wang Y, Vaurio L. Are preoperative depressive symptoms associated with postoperative delirium in geriatric surgical patients? J Gerontol A Biol.Sci Med Sci. 2005;60:1563–8. [PubMed]
9. Litaker D, Locala J, Franco K, Bronson DL, Tannous Z. Preoperative risk factors for postoperative delirium. Gen Hosp.Psychiatry. 2001;23:84–9. [PubMed]
10. McNicoll L, Pisani MA, Zhang Y, Ely EW, Siegel MD, Inouye SK. Delirium in the intensive care unit: occurrence and clinical course in older patients. J Am Geriatr Soc. 2003;51:591–8. [PubMed]
11. Greene NG, Attix DK, Weldon CB, McDonagh DL, Monk TG. Measures of executive function and depression identify patients at risk for postoperative delirium. 2008. (Under Review) [PMC free article] [PubMed]
12. Salthouse TA. Relations between cognitive abilities and measures of executive functioning. Neuropsychology. 2005;19:532–45. [PubMed]
13. Gualtieri CT, Johnson LG, Benedict KB. Neurocognition in depression: Patients on and off medication versus healthy comparison subjects. Journal of Neuropsychiatry and Clinical Neurosciences. 2006;18:217–25. [PubMed]
14. Sheline YI, Barch DM, Garcia K, Gersing K, Pieper C, Welsh-Bohmer K, Steffens DC, Doraiswamy PM. Cognitive function in late life depression: Relationships to depression severity, cerebrovascular risk factors and processing speed. Biological Psychiatry. 2006;60:58–65. [PubMed]
15. Smith PJ, Blumenthal JA, Babyak MA, Hoffman BM, Doraiswamy PM, Waugh R, Hinderliter A, Sherwood A. Cerebrovascular risk factors, vascular disease, and neuropsychological outcomes in adults with major depression. Psychosom.Med. 2007;69:578–86. [PMC free article] [PubMed]
16. Waldstein SR, Rice SC, Thayer JF, Najjar SS, Scuteri A, Zonderman AB. Pulse pressure and pulse wave velocity are related to cognitive decline in the Baltimore Longitudinal Study of Aging. Hypertension. 2008;51:99–104. [PubMed]
17. Gunning-Dixon FM, Raz N. Neuroanatomical correlates of selected executive functions in middle-aged and older adults: a prospective MRI study. Neuropsychologia. 2003;41:1929–41. [PubMed]
18. Pugh KG, Lipsitz LA. The microvascular frontal-subcortical syndrome of aging. Neurobiol.Aging. 2002;23:421–31. [PubMed]
19. Teodorczuk A, O'Brien JT, Firbank MJ, Pantoni L, Poggesi A, Erkinjuntti T, Wallin A, Wahlund LO, Gouw A, Waldemar G, Schmidt R, Ferro JM, Chabriat H, Bazner H, Inzitari D. White matter changes and late-life depressive symptoms: longitudinal study. Br.J Psychiatry. 2007;191:212–7. [PubMed]
20. Monk TG, Weldon BC, Garvan CW, Dede DE, van der Aa MT, Heilman KM, Gravenstein JS. Predictors of cognitive dysfunction after major noncardiac surgery. Anesthesiology. 2008;108:18–30. [PubMed]
21. Folstein MF, Folstein SE, McHugh PR. "Mini-mental state". A practical method for grading the cognitive state of patients for the clinician. J Psychiatr Res. 1975;12:189–98. [PubMed]
22. Acute Pain Management Guideline Panel . Acute Pain Management: Operative or Medical Procedures and Trauma. AHCPR publication 92-0032 edition US Department of Health and Human Services; Rockville, MD: 1992.
23. Charlson ME, Pompei P, Ales KL, Mackenzie CR. A new method of classifying prognostic comorbidity in longitudinal studies: development and validation. J Chronic Dis. 1987;40:373–83. [PubMed]
24. Inouye SK, van Dyck CH, Alessi CA, Balkin S, Siegal AP, Horwitz RI. Clarifying confusion: the confusion assessment method. A new method for detection of delirium. Ann Intern Med. 1990;113:941–8. [PubMed]
25. Reitan RM. Validity of the Trail Making Test as an indicator of organic brain function. Percept Mot.Skills. 1958;8:271–6.
26. Bohnen N, Twijnstra A, Jolles J. Performance in the Stroop color word test in relationship to the persistence of symptoms following mild head injury. Acta Neurol.Scand. 1992;85:116–21. [PubMed]
27. Lezak MD. Executive functions and motor performance, Neuropsychological assessment. 3rd ed. Oxford University Press; New York: 1995. pp. 650–75.
28. Beck AT, Steer RA, Brown GK. Annals of Behavioral Medicine. 2nd edition San Antonio (TX): 1996. Beck Depression Inventory Manual.
29. Beck AT, Ward CH, Mendelsohn M, Mock J, Erbaugh J. An inventory for measuring depression. Archives of General Psychiatry. 1961;4:561–71. [PubMed]
30. Beck AT, Steer RA, Garbin MG. Psychometric properties of the Beck Depression Inventory: twenty-five years of evaluation. Clinical Psychology Review. 1988;8:77–100.
31. Harrell FE, Jr., Lee KL, Califf RM, Pryor DB, Rosati RA. Regression modelling strategies for improved prognostic prediction. Stat Med. 1984;3:143–52. [PubMed]
32. Harrell FE, Jr., Lee KL, Mark DB. Multivariable prognostic models: issues in developing models, evaluating assumptions and adequacy, and measuring and reducing errors. Stat Med. 1996;15:361–87. [PubMed]
33. McAvay GJ, Van Ness PH, Bogardus ST, Jr., Zhang Y, Leslie DL, Leo-Summers LS, Inouye SK. Depressive symptoms and the risk of incident delirium in older hospitalized adults. J Am Geriatr Soc. 2007;55:684–91. [PubMed]
34. Galanakis P, Bickel H, Gradinger R, Von GS, Forstl H. Acute confusional state in the elderly following hip surgery: incidence, risk factors and complications. Int J Geriatr Psychiatry. 2001;16:349–55. [PubMed]
35. Zimmerman M, Mattia JI, Posternak MA. Are subjects in pharmacological treatment trials of depression representative of patients in routine clinical practice? Am J Psychiatry. 2002;159:469–73. [PubMed]
36. Kessler RC, Zhao S, Blazer DG, Swartz M. Prevalence, correlates, and course of minor depression and major depression in the National Comorbidity Survey. J Affect.Disord. 1997;45:19–30. [PubMed]
37. Kessler RC, Chiu WT, Demler O, Merikangas KR, Walters EE. Prevalence, severity, and comorbidity of 12-month DSM-IV disorders in the National Comorbidity Survey Replication. Arch Gen Psychiatry. 2005;62:617–27. [PMC free article] [PubMed]
38. American Psychiatric Association . Diagnostic and Statistical Manual of Mental Disorders - IV - Text Revision. 4th edition American Psychiatric Association; Washington, DC: 2004.
39. Blazer DG. Is depression more frequent in late life? An honest look at the evidence. Am.J.Geriatr.Psychiatry. 1994;2:193–9.
40. Salthouse TA, Atkinson TM, Berish DE. Executive functioning as a potential mediator of age-related cognitive decline in normal adults. J Exp Psychol Gen. 2003;132:566–94. [PubMed]
41. Rypma B, Berger JS, Prabhakaran V, Bly BM, Kimberg DY, Biswal BB, D'Esposito M. Neural correlates of cognitive efficiency. Neuroimage. 2006;33:969–79. [PubMed]
42. Silverstein JH, Timberger M, Reich DL, Uysal S. Central nervous system dysfunction after noncardiac surgery and anesthesia in the elderly. Anesthesiology. 2007;106:622–8. [PubMed]
43. Inouye SK. Delirium in older persons. N Engl J Med. 2006;354:1157–65. [PubMed]
44. Gunther ML, Morandi A, Ely EW. Pathophysiology of delirium in the intensive care unit. Crit Care Clin. 2008;24:45–65. viii. [PubMed]
45. Lewis MC, Barnett SR. Postoperative delirium: the tryptophan dyregulation model. Med Hypotheses. 2004;63:402–6. [PubMed]
46. Nestler EJ, Barrot M, DiLeone RJ, Eisch AJ, Gold SJ, Monteggia LM. Neurobiology of depression. Neuron. 2002;34:13–25. [PubMed]
47. Leung JM, Sands LP, Rico M, Petersen KL, Rowbotham MC, Dahl JB, Ames C, Chou D, Weinstein P. Pilot clinical trial of gabapentin to decrease postoperative delirium in older patients. Neurology. 2006;67:1251–3. [PubMed]
48. Figiel GS, Krishnan KR, Doraiswamy PM. Subcortical structural changes in ECT-induced delirium. J Geriatr Psychiatry Neurol. 1990;3:172–6. [PubMed]
49. Campbell JJ, Coffey CE. Neuropsychiatric significance of subcortical hyperintensity. Journal of Neuropsychiatry and Clinical Neurosciences. 2001;13:261–88. [PubMed]
50. Alexopoulos GS, Meyers BS, Young RC, Campbell S, Silbersweig D, Charlson M. `Vascular depression' hypothesis. Archives of General Psychiatry. 1997;54:915–22. [PubMed]
51. Vittinghoff E, McCulloch CE. Relaxing the rule of ten events per variable in logistic and Cox regression. Am J Epidemiol. 2007;165:710–8. [PubMed]