Postoperative cognitive injury is characterized by decline of such mental functions as perception, memory, and information processing after a surgical procedure.1,2 The occurrence of cognitive dysfunction after coronary artery bypass graft (CABG) surgery is frequent and persistent with 30% to 65% of patients showing cognitive injury at 6 weeks after surgery.2–5 Despite surgical advancements reducing the once high mortality and morbidity rates associated with CABG, only a few strategies6,7 have been proposed to moderate postoperative cognitive decline and the associated reduction in quality of life.8 Preoperative risk factors for cognitive injury after surgical intervention include age, level of education, baseline cognition, and genetic predisposition.2,3,9,10 The hypothesized surgical risks for cognitive decline include cerebral embolism, cell salvage, valve surgery, hypoperfusion, systemic inflammatory responses, hemodilution, hyperglycemia, and hyperthermia.3,10–13
Perioperative factors associated with dysfunction have been well documented; nonetheless, there is much uncertainty and controversy surrounding the underlying pathophysiology, clinical sequelae, and chronicity of the phenomenon. It remains unclear in the literature whether short-term changes in cognitive performance lead to long-term postoperative declines. In a longitudinal study assessing neurocognitive function after CABG, Newman et al.2 reported that impairment at discharge was associated with a decline from baseline function 5 years after surgery. Other evidence suggests that postoperative cognitive dysfunction (POCD) is transient in nature, with no relationship between immediate and delayed cognitive injury.5,14 With the inclusion of a control group and adjustment for the variability of within-subject score changes, Selnes et al.14 found that while some cognitive dysfunctions occurred directly after CABG, there were no significant differences in long-term cognitive decline between patients who had undergone CABG surgery and nonsurgical controls with diagnosed coronary artery disease. Although these observations are of empirical importance to the phenomenon of cognitive decline, they have not identified factors that influence recovery from cognitive injury after cardiac surgery. Understanding the unique factors that contribute to recovery after postoperative cognitive injury may expedite overall recovery, inform risk stratification allowing for improved patient–family education, advance prevention models, and generate implications for treatment, thereby increasing the quality of life for cardiac surgical patients. We therefore sought to identify predictors associated with a return to baseline levels of cognitive performance after initial postoperative injury.
Study Population and Procedure
After IRB approval, 281 patients undergoing elective cardiac surgery (CABG, Valve, or CABG + Valve) with cardiopulmonary bypass from February 2000 to August 2009 who demonstrated cognitive decline 6 weeks after surgery in prospective cognitive trials4,10,12,15,16 and had complete data at baseline, 6-week, and 1-year assessments were retrospectively evaluated. The requirement for written informed consent was waived by the IRB. Patients were excluded from the parent trials if they presented with characteristics known to have confounding effects on cognition including a history of symptomatic cerebrovascular disease with residual deficit, psychiatric illness (any clinical diagnoses requiring therapy), hepatic insufficiency (liver function tests > 1.5 times the upper limit of normal), and renal insufficiency (creatinine levels > 2 mg/dL), and who were unable to read and thus unable to complete the cognitive testing or who scored <24 on a baseline Mini Mental State Examination. Patients who experienced an adverse postoperative event, such as a subsequent cardiac event were also excluded to create a more homogenous population and to isolate the effect of baseline characteristics on 1-year cognitive functioning. Of note, patients suffering from depression after surgery were not excluded.
To evaluate cognitive function, trained psychometricians administered a neurocognitive test battery at baseline (1.61 ± 1.74 days before surgery), 6 weeks, and 1 year after surgery, including the Short Story Module of the Randt Memory Test, a reliable measurement of discourse memory (immediate and delayed) and oral language comprehension;17 the Modified Visual Reproduction Test from the Wechsler Memory Scale on which patients are required to reproduce from memory several geometric shapes both immediately and after a 30-minute delay, testing for short-term and long-term figural memory;18 the Digit Span subtest of the Wechsler Adult Intelligence Scale-Revised (WAIS-R) examination, a measure of short-term auditory memory and attention that calls on subjects to repeat a series of digits that have been orally presented to them both forward and, in an independent test, in reverse order;18 the digit symbol subtest of the WAIS-R, an evaluation of psychomotor processing speed, in which number-symbol pairs are transcribed under timed conditions;18 and the Trail Making Test Part B, a timed test in which patients alternately connect letters and numbers to assess processing speed, attention, and mental flexibility.19
Quality of Life Testing
To identify quality-of-life outcomes, the following assessments were also administered at baseline, 6 weeks, and 1 year after surgery:
- The Duke Activity Status Index (DASI).20 A 12-item instrument designed specifically to evaluate functional status and physical capabilities in cardiovascular populations. Limitations experienced by the patients during household tasks, personal care, leisure activities, sexual function, and ambulation were reported on a 4-point Likert scale.
- The Duke Older Americans Resources and Services Procedures-Instrumental Activities of Daily Living (OARS-IADL) (IADL).21 Six IADL items from the OARS Procedures are used to measure patients’ ability to perform important daily self-care activities (e.g., “Could you prepare your own meals?” “Could you do errands, such as shopping for groceries or household necessities?”). Higher scores indicate increasing difficulty in engaging in daily activities.
- The Medical Outcomes Study 36-item Short-Form Health Survey (SF-36). A survey of health-related limitations and general health conditions used to assess overall health status.22 Two scales were used: General Health (1 item) and Work Activities (4 items). Higher Work Activities scores indicate more health-related difficulties.
- A social activities measure that indicates the degree of social interaction (e.g., “About how often do you visit with friends and relatives?”), with lower scores indicating more social activity.
- A symptoms limitations checklist in which patients were asked how often various symptoms (e.g., angina, shortness of breath, arthritis, etc.) restricted daily activities.23 Higher scores signified greater limitations.
- The Center for Epidemiological Studies Depression Scale.24 Clinically significant depression is indicated by a score of 16 or higher.
- The State-Trait Anxiety Inventory.25 A 20-item instrument used to measure anxiety in which patients are asked how frequently they experienced a particular symptom (e.g., “I feel worried,” “I feel nervous”), on a 4-point Likert scale ranging from “not at all” to “very much so.”
- The Perceived Social Support Scale. An assessment of global social support in which patients are asked how often various types of support are available to them.26
- The Cognitive Difficulties Scale. An instrument (based on a 5-point Likert scale) of self-perceived cognitive deficits in memory, concentration, attention, and psychomotor coordination.27
To account for the correlation among cognitive test scores, baseline raw test scores were subjected to a factor analysis as previously described.2 To maintain consistent factor definitions across time, follow-up scores were calculated using weights resulting from this baseline analysis. An analysis yielded independent scores representing 4 cognitive domains: (1) verbal memory and language comprehension; (2) attention, psychomotor processing speed, and concentration; (3) abstraction and visuospatial orientation; and (4) figural memory.
To quantify the overall neurocognitive function, a composite cognitive index (CI) score was calculated as a mean of the 4 domain scores. This unified index score has been shown to be a stronger correlate of quality-of-life outcomes than the individual domain scores.8 Patients who showed any decline in CI score from baseline to 6 weeks were considered “decliners” and comprised the analysis data set. The outcome variable cognitive recovery was then defined dichotomously as 1-year CI ≥ baseline CI. The association between cognitive recovery at 1 year and potential predictors including patient characteristics, quality-of-life factors, comorbidities, medications, and intraoperative variables was assessed with χ2 tests for categorical variables and t tests for continuous variables, followed by multivariable logistic regression modeling. Based on previous findings demonstrating significant associations with neurocognitive outcomes, 3 variables (age, years of education, and baseline cognition) were prespecified for inclusion in the model.2,9 To avoid model overfitting, on the basis of number of outcomes in our sample, we selected the 7 additional variables with the lowest univariate P values to incorporate into the multivariable modeling. Nonsignificant variables were individually dropped from the multivariable models until only significant variables remained; P < 0.05 was considered significant. Model fit and discrimination were evaluated using the Hosmer-Lemeshow goodness-of-fit test and the area under the receiver operating characteristic curve (c-index).
In secondary analysis, continuous change between 6 weeks and 1 year (rather than the dichotomous variable based on a return to baseline) was assessed using multivariable linear regression. Similarly, we assessed cognitive decline at 6 weeks as a ≥1 standard deviation (SD) decline in at least 1 of the 4 cognitive domains with cognitive recovery defined as a return to baseline at 1 year.
Of the 281 patients who had demonstrated a decline in CI from baseline to 6 weeks after surgery, 52 patients were excluded due to 54 major cardiac events in the first year (10 cardiac surgeries and 44 deaths). Of the 229 “decliners” in our final analysis data set, 178 underwent CABG surgery, 32 had CABG + valve surgery, and 19 had valve surgery alone. Forty-five percent (95% confidence interval, 38.5–51.5) of the patients (103/229) experienced cognitive recovery while 55% (126/229; 95% confidence interval, 48.5–61.5) remained below baseline at 1-year assessments. With regard to age, gender, comorbidities, surgical characteristics, statin use, depression, anxiety, marital status, and level of social support, no significant differences were observed between those patients who showed cognitive recovery and those who did not (Table 1).
Predictors of Change in Neurocognitive Function
Patients who demonstrated cognitive recovery 1 year after surgery were more likely to be Caucasian (89% vs 79%; P = 0.04) and declined less between baseline and 6 weeks than those who did not recover at 1 year (–0.16 ± 0.15 vs –0.23 ± 0.23; P = 0.01). In addition, cognitive improvement at 1-year after surgery was related to lower IADL scores (higher IADL scores reflect worse daily functioning) 6 weeks after surgery (8.7 ± 3.8 vs 10.8 ± 5.3; P = 0.006; Table 1). Multivariable logistic regression revealed 4 independent predictors of cognitive recovery: years of education (P < 0.001), baseline CI (P = 0.02), amount of cognitive decline between assessments at baseline and at 6 weeks after surgery (P = 0.004), and greater functional performance (lower IADL scores) at 6 weeks after surgery (P = 0.02; Table 2). The c-index for this model was 0.77, indicating moderately good discrimination of subjects. The Hosmer-Lemeshow test χ2 value was 11.73, P = 0.16, indicating that the observed event rates match the expected event rates. By examining the influence of diagnostic plots, we found that there are 3 data points that are not well accounted for by the model, and that may exert a large effect on goodness of fit. To determine whether our significant association was affected by these data points, we conducted a follow-up analysis excluding these data points. The model c-index improved to 0.79 and the P value for IADL to P = 0.002. The association between IADL and probability of recovery is depicted in Figure 1.
This association between IADL scores and cognitive recovery remained significant in the secondary analysis, in which cognitive improvement was assessed as a continuous outcome. IADL also remained a predictor of return to baseline at 1 year when cognitive decline was defined as ≥1 SD decline in at least 1 of the 4 cognitive domains at 6 weeks. Cognitive recovery at 1 year (return to baseline) using this 1 SD definition was seen in 40% (95% confidence interval, 31.1–48.6). Post hoc analysis incorporating the patients who had been excluded for a subsequent cardiac event showed that the adverse event itself was not a significant predictor of cognitive recovery and did not alter the predictive capacity of the other variables in the model.
To our knowledge, this is the first study to identify factors associated with cognitive improvement after early cognitive decline in patients undergoing cardiac surgery. We found that almost one half of the patients who exhibited cognitive decline 6 weeks after cardiac surgery demonstrated cognitive recovery by 1 year. We also identified 4 predictors that were associated with 1-year recovery including higher education level, baseline cognitive performance, less cognitive decline between baseline and 6 weeks, and lower IADL scores at 6 weeks (i.e., better functional performance).
In support of previous studies that showed an association between level of education and cognitive performance,28–39 we found a relationship between level of education and cognitive recovery after an initial decline. Possible explanations for this effect may lie in education’s influence over important environmental and neurological factors. Less educational attainment may put one at greater risk for cognitive deterioration, decreasing the likelihood of cognitive recovery through its association with other potential risk factors such as nutritional deficiencies, less health care access, psychiatric illness, or exposure to increased occupational hazards.29,30 Education may also directly influence brain structures early in development, resulting in increased synapses or vascularization and leading to improved lifetime cognitive function and brain plasticity.28,30,31,34 Alternatively, education may lead to a reserve of cognitive capacity that does not alter vulnerability to decline, but delays the appearance of clinical symptoms and/or compensates for early cognitive injury.40
Cognitive performance at 6 weeks also was a significant predictor of cognitive recovery at 1 year. Similar to quantity of education, heightened cognitive function can result in increased neuronal count and network capacity, efficiency, or compensation that may decrease risk for future cognitive impairment and increase ability to recover from cognitive damage.31,38,40 In addition, increases in cognitive function reflect lifestyle patterns that promote stimulation and recovery, thereby preventing or delaying cognitive decline. Epidemiologic studies have found slower rates of decline among those who routinely engage in more cognitively demanding tasks such as reading books and newspapers, playing cards, watching television, and solving puzzles than those who lead less cognitively engaged lifestyles.31,40
Our finding that heightened IADL performance 6 weeks after surgery is associated with the likelihood of cognitive recovery at 1 year after initial decline supports the previous findings of an association between functional status and cognition.41–48 IADL are complex, adaptive behaviors that facilitate independent living, reflect on one’s functional capacity, and include the following activities: meal preparation, telephone use, medication management, transportation, financial management, housekeeping duties, and shopping.42,46,48 Functional impairment is first expressed among instrumental activities44,46,49 and is an essential feature for the diagnosis of dementia.44 In other words, functional disability as shown by poor performance on IADL items separates individuals with severe cognitive dysfunction from those with moderate to no cognitive deficit. The functional changes associated with such cognitive decline have repercussions expanding from the individual (e.g., decreased quality of life, increased dysphoria, and low self-effectiveness) to the communal level (e.g., premature institutionalization, increased caregiver burden, and higher health care costs).50 The association between increased functional status in the early postoperative period and the likelihood of cognitive recovery in the later postoperative stages suggests that interventions that encourage the performance of instrumental activities immediately after surgery may result in improved cognitive performance.
The DASI, also a measure of functional status, was not found to significantly predict cognitive recovery. Unlike the IADL, which focuses on daily activities that involve planning or increased cognitive control (e.g., can you handle your own money, pay bills, write checks, balance checkbook?), the DASI concentrates more on the completion of more physically demanding or mechanical activities (e.g., can you climb a flight of stairs or walk up a hill?).51 Both instruments assess functional status and assess ability to perform routine activities; however, the IADL approaches functional capacity from a cognitive framework, and IADL impairment reflects difficulty in organizing, initiating, and performing actions, whereas DASI impairment suggests increased physical limitations, possibly as a result of poor cardiac function. Because the IADL inherently addresses functional capacity with a cognitive component, this distinction may help explain why IADL scores predict future cognitive recovery while DASI scores do not.
Similar to the DASI, the 2 SF-36 subscales were found to have no significant predictive relationship to cognitive recovery. The SF-36 and the IADL, both measures of quality of life, differ in test objective and agenda. The SF-36 was designed as a health economics tool to assess quality-adjusted life years, a pivotal variable in determining the cost-effectiveness of treatment. The SF-36 is foremost a means of monitoring and comparing disease burden and not aptitude, which is the measured intent of the IADL. As with the DASI, poor performance on the SF-36 indicates functional limitation at the level of overall physical condition and not cognitive ability. The inability of both the DASI and the SF-36 to significantly predict cognitive recovery highlights the IADL as a distinct, cognitively focused quality-of-life measure important in assessing the course of postoperative cognitive rehabilitation.
Previous studies have shown depressive symptoms to be independently associated with cognitive decline.48,52 However, we were unable to demonstrate an association between depression and social support systems and cognitive recovery at 1 year. Depression and social support systems often occur as by-products of functional status52 and are therefore less robust predictors of enhanced cognition in comparison with functional status itself.
Our study is limited by the observational and exploratory design; thus our findings should be considered the first step in identifying the factors that may lead to recovered cognitive functioning after an initial postoperative decline. Our study could also be criticized for our definition of cognitive recovery as a return to baseline, which is a dichotomous variable. For this reason, in a secondary supportive analysis, we examined cognitive recovery as a continuous outcome and found that the IADL score remains a significant predictor. Furthermore, from the point of view of the patient, a return to baseline functioning is an important landmark with numerous benefits and quality-of-life implications. Another consideration in the interpretation of our study is the inclusion of subjects with any decline from baseline to 6 weeks, rather than a prespecified unit of decline, such as an SD. Although there is little consensus in the literature about how to define POCD and an SD-based definition of decline is often challenged as being arbitrary, we do acknowledge that this decision leaves us unable to fully discount the effects of measurement error or regression on the mean. To further address this concern, we assessed cognitive decline at 6 weeks as a ≥1 SD decline in at least 1 of the 4 cognitive domains and found that the 6-week IADL score is still a predictor of return to baseline at 1 year. In addition to the inclusion of the IADL score in the study battery, future studies should ideally include additional measures of functional status to provide a more comprehensive understanding of the components of functional aptitude and how they relate to cognitive recovery. Future studies should also include control groups to elucidate the effect of surgery and coronary heart disease on this relationship.
To summarize, in this first study to examine factors predicting recovery from POCD, 45% of patients who experience cognitive decline at 6 weeks return to baseline cognitive function by 1 year. Higher educational levels, baseline cognitive performance, smaller cognitive decline at 6 weeks, and lower IADL scores (better functional performance) at 6 weeks are associated with cognitive recovery 1 year after cardiac surgery. Of note, age, depression, and social support systems do not seem to modulate this recovery. Whether increasing patients’ functional capacity through increased occupational activity (e.g., acts of self-care, work, and leisure) before a surgical admission (as opposed to postoperatively) would allow the individual to retain a higher level of functional capacity over their entire perioperative experience with resulting increases in quality of life and cognitive recovery should be further examined.
Name: Monique T. Fontes, BA.
Contribution: This author helped analyze the data and write the manuscript.
Attestation: Monique T. Fontes reviewed the analysis of the data and approved the final manuscript.
Name: R. Cameron Swift, MD.
Contribution: This author helped design the study, analyze the data, and write the manuscript.
Attestation: R. Cameron Swift has seen the original study data, reviewed the analysis of the data, and approved the final manuscript.
Name: Barbara Phillips-Bute, PhD.
Contribution: This author helped design the study, conduct the study, analyze the data, and write the manuscript.
Attestation: Barbara Phillips-Bute 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: Mihai V. Podgoreanu, MD.
Contribution: This author helped write the manuscript.
Attestation: Mihai V. Podgoreanu approved the final manuscript.
Name: Mark Stafford-Smith, MD.
Contribution: This author helped design the study and write the manuscript.
Attestation: Mark Stafford-Smith reviewed the analysis of the data and approved the final manuscript.
Name: Mark F. Newman, MD.
Contribution: This author helped write the manuscript.
Attestation: Mark F. Newman approved the final manuscript.
Name: Joseph P. Mathew, MD, MHSc.
Contribution: This author helped design and conduct the study, analyze the data, and write the manuscript.
Attestation: Joseph P. Mathew 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.
APPENDIX: Neurologic Outcome Research Group of the Duke Heart Center
Director: Joseph P. Mathew, MD, Codirector: James A. Blumenthal, PhD.
Anesthesiology: Manuel A. Fontes, MD, Miklos D. Kertai, MD, Frederick W. Lombard, MD, Joseph P. Mathew, MD, David L. McDonagh, MD, Terri G. Monk, MD, Mark F. Newman, MD, Mihai V. Podgoreanu, MD, Mark Stafford-Smith, MD, Madhav Swaminathan, MD, David S. Warner, MD, Bonita L. Funk, RN, CCRP, Narai Balajonda, MD, Roger L. Hall, AAS, Tiffany Bisanar, RN, BSN, Karen L. Clemmons, Monique T. Fontes, BA, Kathleen Lane, RN, BSN, Yi-Ju Li, PhD, Jacquelane F. Libed, MD, Greg Pecora, BA, Barbara Phillips-Bute, PhD, Prometheus T. Solon, MD, Yanne Toulgoat-Dubois, BA, Peter Waweru, CCRP, William D. White, MPH.
Behavioral Medicine: Michael A. Babyak, PhD, James A. Blumenthal, PhD, Jeffrey N. Browndyke, PhD, Kathleen A. Welsh-Bohmer, PhD.
Cardiology: Daniel B. Mark, MD, MPH, Michael H. Sketch, Jr, MD.
Neurology: Ellen R. Bennett, PhD, Carmelo Graffagnino, MD, Daniel T. Laskowitz, MD, Warren J. Strittmatter, MD.
Perfusion Services: Kevin Collins, BS, CCP, Greg Smigla, BS, CCP, Ian Shearer, BS, CCP.
Surgery: Mark F. Berry, MD, Thomas A. D’Amico, MD, R. Duane Davis, MD, Jeffrey G. Gaca, MD, Donald D. Glower, MD, R. David Harpole, MD, G. Chad Hughes, MD, Robert D.B. Jaquiss, MD, Shu S. Lin, MD, Andrew J. Lodge, MD, Carmelo A. Milano, MD, Mark W. Onaitis, MD, Jacob N. Schroeder, MD, Peter K. Smith, MD, Betty C. Tong, MD.
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