DÄ internationalArchive7/2017Cognitive Reserve and the Risk of Postoperative Cognitive Dysfunction

Original article

Cognitive Reserve and the Risk of Postoperative Cognitive Dysfunction

A Systematic Review and Meta-Analysis

Dtsch Arztebl Int 2017; 114: 110-7. DOI: 10.3238/arztebl.2017.0110

Feinkohl, I; Winterer, G; Spies, C D; Pischon, T

Background: Post-operative cognitive dysfunction (POCD) occurs in 10 to 54% of older patients during the first few weeks after surgery, but little is known about risk factors predisposing to POCD.

Methods: Systematic literature review and meta-analysis of cognitive reserve indicators and POCD risk.

Results: Fifteen studies on 5104 patients were included. Follow-up periods spanned 1 day to 6 months. Educational level was the most commonly assessed cognitive reserve indicator, and a longer time spent in education was associated with a reduced risk of POCD (relative risk [RR] per year increment 0.90; 95% confidence interval: [0.87; 0.94]), i.e. each year increase in education was associated with a 10% reduced risk. Similar findings were made for some analyses on education as a categorical predictor (high school versus further/higher education, RR 1.71, [1.30; 2.25]; lower than high school versus further/higher education, RR 1.69, [1.17; 2.44]) though risk was equivalent for patients with high school education and those with lower than high school education (RR 1.02; [0.78; 1.32]).

Conclusion: Patients with a relatively higher level of education are at reduced risk of POCD. Risk stratification of surgical patients according to educational level may prove useful.

LNSLNS

Post-operative cognitive dysfunction (POCD) occurs relatively frequently, in 10 to 54% of patients during the first few weeks after surgery (1). It is usually transient (2), but unlike for post-operative delirium (POD), clear diagnostic criteria are lacking for POCD (3, 4).

Despite its high prevalence, POCD is underresearched and well-established risk factors for POCD are few and far between (for a review, see [2]) so that at present the cognitive risk of a surgical patient is unpredictable. Recent research has shown that diabetes (5) and pre-existing cognitive impairment (6) may predispose patients to POCD. Compared with these types of clinical risk factors, however, research into the contribution of cognitive reserve to POCD has essentially been neglected.

Cognitive reserve is a theoretical construct that aims to explain links between factors such as a lower level of education, lower socioeconomic status (SES), or lower pre-morbid cognitive ability and an increased risk of cognitive impairment in older age (711). The account assumes that people differ in their ability to functionally ‘buffer’ neuropathological insult due to aging and disease according to their cognitive reserve capacity (1214). Simply put, brain networks of high-reserve individuals are thought to be better able to cope with disruptions due to working more efficiently and more flexibly compared with low-reserve individuals. Neuropathological burden may further be compensated for through recruitment of novel brain networks (13).

POCD is known to negatively impact on subjective cognitive function and quality of life in affected patients (15, 16). Studies suggest that it also increases the risk of dementia and mortality (1719). POCD is thus a cause for concern from a public health perspective that exceeds problems associated with cognitive deficits alone. With a lower cognitive reserve capacity as a predictor of age-related cognitive impairment, it appears reasonable to expect an association with POCD. A lower level of education is indeed frequently discussed as a contributing factor to POCD, though empirical evidence is rarely mentioned (2, 2023). If such evidence was to be confirmed, measures of cognitive reserve could supplement cognitive risk prediction on the basis of clinical risk factors. Because low cognitive reserve could reasonably constitute the starting point of a causal chain leading up to POCD, the identification of cognitive reserve parameters as risk factors for POCD would further add to our understanding of the processes underlying the condition.

Here, we aim to integrate the current epidemiological evidence on cognitive reserve and the risk of POCD in view to providing guidance for clinical practice.

Methods

Systematic search strategy

An electronic search (eTable 1, eBox 1) was performed by one investigator (IF) in accordance with the MOOSE and PRISMA guidelines (24, 25).

Overview of included studies
Overview of included studies
Table
Overview of included studies
Systematic search strategy
Systematic search strategy
eBox 1
Systematic search strategy
Parameters assessed in the present review with corresponding search terms
Parameters assessed in the present review with corresponding search terms
eTable 1
Parameters assessed in the present review with corresponding search terms

Study selection

Studies were eligible for inclusion if they

  • followed a prospective study design,
  • included human adults undergoing surgery (age ≥18 years),
  • had full texts published in English
  • reported original data on associations of cognitive reserve indicators (eTable 1) with POCD in the form of odds ratios or relative risks (RR; both termed RR in the present analysis) or as descriptive data that allowed calculation of RR. Any operationalization of POCD qualified for inclusion provided it was based on performance-based neuropsychological assessment.

Data extraction

Fully adjusted RR statistics were extracted unless no adjustment was made. If more than one article reported on the same sample, the article with the most complete reporting was selected. Data were extracted on the longest follow-up period. For 2 studies with multivariate-adjusted data at 7 day follow-up but not at 3 months, the 7 day follow-up was selected (26, 27). For one study comparing three levels of cognitive change, ‘severe deterioration’ was used to represent POCD (28). Enquiries were made to corresponding authors for unreported information.

Data synthesis and analysis

Studies were analyzed separately for each cognitive reserve indicator. We used the standard I2 index to identify statistical heterogeneity (29) and inverse variance fixed-effect models to calculate summary estimates of RR (95% CI) in meta-analyses across studies. Forest plots were generated to present pooled estimates. The main meta-analyses were repeated using random-effects models (eBox 2). Potential sources of heterogeneity were explored in subgroup and meta-regression analyses. Review Manager 5.3 and SAS Enterprise Guide 4.3 were used.

Results of main analyses in fixed effects models and random effects models
Results of main analyses in fixed effects models and random effects models
eBox 2
Results of main analyses in fixed effects models and random effects models

Results

The search retrieved 109 unique articles (eFigure 1); an independent search identified a further 28 articles. Overall, 64 full text articles were assessed. Of these, 40 did not meet our inclusion criteria and 9 articles (3038) were excluded due to suspected duplicate reporting (19, 26, 27, 39). In total, 15 articles were included.

Forest plot
Forest plot
Figure
Forest plot
Flow chart for search on cognitive reserve and postoperative cognitive reserve (POCD)
Flow chart for search on cognitive reserve and postoperative cognitive reserve (POCD)
eFigure 1
Flow chart for search on cognitive reserve and postoperative cognitive reserve (POCD)

The included studies originated in Europe, USA, Australia, and Asia (eTable 2). Surgical procedures included cardiac surgery (n = 7) and non-cardiac surgery (n = 8) under general (n = 9) or a combination of general and regional anesthesia (n = 4) (where reported) (Table). A total of 5104 patients were analyzed. Sample characteristics varied substantially between studies. The proportion of males ranged from 26% to 79% and the mean sample age from 51 to 75 years (mean 63 ± 8 years). Patients were followed up for between 1 and 180 days after surgery (median: 25 days; interquartile range: 7 to 45 days). All studies except one (40) applied detailed batteries of neuropsychological tests, though the criteria used to define POCD were heterogeneous. POCD occurred in 8% to 67% of patients.

Detailed summary of included studies
Detailed summary of included studies
eTable 2
Detailed summary of included studies

Findings of included studies and meta-analysis

a) Years of education—Eight articles reported data on years of education. The mean years of education in these studies ranged from 8 years in 2 studies from Italy and China (28, 40) to 14 years in 2 US studies (17, e1) (mean 12 ± 3 years). When effects were pooled, each year increase in education was associated with a 0.90 risk of POCD (RR 0.90 per year increment; 95% CI: [0.87; 0.94]; p<0.001) (Figure), i.e. a 10% reduced risk of POCD. Statistical heterogeneity between studies was moderate (chi2 [7] = 12.49; I2 = 44%; p = 0.09) with no evidence of publication bias (eFigure 3). The finding was universal across study designs and sample characteristics (eTable 3, eFigure 2).

Years of education and risk of POCD in subgroup analyses according
Years of education and risk of POCD in subgroup analyses according
eFigure 2
Years of education and risk of POCD in subgroup analyses according
Funnel plot for meta-analysis of years of education and POCD
Funnel plot for meta-analysis of years of education and POCD
eFigure 3
Funnel plot for meta-analysis of years of education and POCD
Subgroup analyses of included studies on education (years) and POCD (total N = 8)
Subgroup analyses of included studies on education (years) and POCD (total N = 8)
eTable 3
Subgroup analyses of included studies on education (years) and POCD (total N = 8)

b) to d) Level of education as a categorical predictor—Five studies assessed education as a categorical variable. Of these, 3 studies ascertained whether patients had completed a lower level than high school, had completed high school and/or had completed further/higher education (26, 27, e2). For the purpose of the present analyses, “middle school education” in one Chinese study (e3) was equated with “high school education.” For one US study (19), “ >16 years of education” was equated with “further/higher education.”

b) High school education versus further/higher education—When effects were pooled across 4 studies (19, 27, e2, e3), high school level of education was associated with a 71% increased risk of POCD compared with a higher level of education (RR 1.71 [1.30, 2.25]; p<0001) (Figure; eFigure 4). No statistical heterogeneity was indicated (chi2 [3] = 0.67; I2 = 0%; p = 0.88).

Funnel plot for meta-analysis of high school education versus further/higher education and POCD
Funnel plot for meta-analysis of high school education versus further/higher education and POCD
eFigure 4
Funnel plot for meta-analysis of high school education versus further/higher education and POCD

c) High school versus lower than high school education—No statistically significant associations emerged on high school versus not having attained high school education when effects were pooled across 4 studies (26, 27, e2, e3) (RR 1.02 [0.78; 1.32]; p = 0.89) (Figure; eFigure 5). Statistical heterogeneity was substantial (chi2 [3] = 15.19; I= 80%; p = 0.002).

Funnel plot for meta-analysis of high school education versus lower than high school education and POCD
Funnel plot for meta-analysis of high school education versus lower than high school education and POCD
eFigure 5
Funnel plot for meta-analysis of high school education versus lower than high school education and POCD

d) Lower than high school education versus further/higher education—Four studies compared the POCD risk of patients with lower than high school education with that of those with further/higher education (26, 27, e2, e3). Two of these studies (26, 27) adjusted their analyses for a range of covariates. Across all four studies, having attained lower than high school education was associated with a 69% increased risk of POCD (RR 1.69 [1.17; 2.44]; p = 0.005) (Figure; eFigure 6). Statistical heterogeneity was low (chi2 [3] = 3.08; I= 3%; p = 0.38).

Funnel plot for meta-analysis of lower than high school education versus further/higher education and POCD
Funnel plot for meta-analysis of lower than high school education versus further/higher education and POCD
eFigure 6
Funnel plot for meta-analysis of lower than high school education versus further/higher education and POCD

Other indicators of cognitive reserve

One study (e2) showed a trend for an increased risk of POCD in illiterate patients; however, this was not statistically significant (RR 1.47 [0.46; 4.69]; p = 0.52). Another study (e4), that derived a composite measure of reserve capacity from occupation, vocabulary, education, ethnicity, geographical region of the country, and sex found a statistically non-significantly reduced risk of POCD in low-reserve patients (RR 0.71 [0.45; 1.12]; p = 0.14). In one study (e5), no association was found between National Adult Reading Test (NART) scores and POCD risk (RR per NART score increment: 1.01 [0.96; 1.07]; p = 0.68).

Discussion

Here, we set out to integrate reports on indicators of cognitive reserve and risk of POCD. Only few studies were identified. Education was the most commonly ascertained reserve indicator and overall having attained a higher level of education was associated with a reduced risk of POCD. Due to considerable heterogeneity between studies, we are unable to comment on a potential dose–response relationship.

Several studies controlled for baseline level of cognitive function (39, e1, e6, e7) which in the assessment of education as a predictor represents overadjustment. True effects may therefore be larger than reported here though the role of confounding factors is entirely unclear. Our finding by no means implies causation. Null findings for reserve indicators other than education (e2, e4, e5) may be due to limited statistical power and the low study number. As reserve indicators tend to correlate (e8e11), lower pre-morbid ability and illiteracy, too, may be identified as contributing to POCD in the future. One study found a trend for a protective effect of lower cognitive reserve (e4). As cognitive reserve in that study was defined by a range of reserve indicators as well as demographics, this may suggest an influence by some factor other than education.

Our findings are supported by several studies that report associations of low education level with an increased risk of POCD in their abstracts but were excluded due to non-English language (e12e15). A lower reserve capacity may also increase the risk of post-operative delirium (POD) (e16, e17) and is well-established as a risk factor for age-related cognitive impairment. For instance, lower compared to higher levels of education have been associated with a 59 to 88% increased risk of dementia (7, 8).

Candidate pathophysiological mechanisms underlying POCD include surgery-induced inflammation (e18) and, potentially, anesthesia-induced neurodegeneration (e19). In line with the cognitive reserve model (1214, e20), patients with a higher cognitive reserve as indicated by a higher level of education may have a functional advantage: they may be able to better cope with such damage through adjusting existing or recruiting novel brain networks. Morphological advantages, such as a larger brain size, correlate with cognitive reserve (e21) and may also play a role (e22). Finally, associations may be mediated by clinical and lifestyle factors (e23). Low-reserve individuals tend to be exposed to higher levels of environmental hazards (e24) and detrimental lifestyle (e25) across their life span, yielding greater brain pathology in older age (e26). Low-reserve patients may then have presented for surgery with greater subclinical neuropathology, such as beta amyloid burden (e27), which was exacerbated by surgery to become expressed as cognitive deficits. This account is the most plausible explanation of the health consequences associated with POCD (1719, e28) and could be evaluated through adjustment of analyses for lifestyle and clinical risk factors; however in the studies included here, adjustment was inconsistent.

Research into the epidemiology of POCD is in its infancy and firm knowledge of all of its risk factors is lacking. We have recently shown that the metabolic syndrome may be associated with POCD (5, e29). The present findings are in line with that type of evidence as a lower cognitive reserve predisposes to metabolic syndrome in later life (e30). Clearly, further studies in this area are needed. These should consider multimorbidity as well as lifespan developments and could—once all risk factors for POCD have been identified—feed into the development of a risk score and of preventive measures. A large proportion of older patients in hospitals is cognitively impaired (e31) so that putting a halt to POCD would be immensely beneficial to global health.

Limitations

A number of limitations must be considered. There was substantial overlap in studies included in meta-analyses b) to d), level of education as a categorical predictor, which each were based on a small number of studies. Thus, no firm conclusions should be drawn on the basis of those analyses. RR and OR estimates are also not strictly equivalent (e32) but were equated here. Further, a single investigator performed the search and non-English articles were excluded from our analysis. Included studies were heterogeneous with respect to sample characteristics and definitions of POCD, so that the generalizability of our findings is uncertain. With the inclusion of studies that applied no adjustment at all, confounding of our results by any other sociodemographic and/or clinical variables is plausible. Grouping studies according to the categories “lower than high school education”; “high school education”, and “further/higher education” may have been suboptimal for those that did not explicitly refer to these categories (19, e3), and included studies were set in a total of 13 countries. Thus, our results will have been affected by cross-cultural differences between school systems and may not necessarily transfer to German hospitals. Readers are also advised that the relative risk estimates presented here do not reflect absolute risks. Nonetheless, our findings illustrate a trend to suggest that—while considering other coexisting factors—
enquiry into patients’ educational background during pre-surgery interview may be a straightforward and non-invasive way to identify at-risk patients.

Conclusion

The importance of patients’ cognitive reserve capacity is becoming increasingly recognized (e33). Virtually all previous studies of POCD have assessed indicators of cognitive reserve and could re-analyze their data to determine the roles of the frontal cortex and associated cognitive function, potential lifestyle mediators, and clinical mediators. Attention should be paid to overadjustment for variables that are closely related to both predictor and outcome and render statistical analyses non-significant despite an underlying relationship. Here, we identified only two studies that used a vocabulary-based estimate of peak pre-morbid ability as a reserve indicator. Future investigations are well-advised to take advantage of such tests, which are easily administered and well-validated (e34) and are unaffected by surgery (e35) or, unlike education, by societal constraints.

Our results show that middle-aged to older surgical patients with a higher level of education are at reduced risk of POCD compared with less educated patients. Mechanisms, contributing clinical and environmental factors, and strategies to reduce POCD risk in low-education patients warrant detailed research, but for now, we recommend that anesthetists and surgeons consider routine ascertainment of patients’ level of education in geriatric surgery.

Funding
This study was supported by funding from the European Union, Seventh Framework Programme [FP7/2007–2013], under the grant agreement No. HEALTH-F2–2014–602461 BioCog (Biomarker Development for Postoperative Cognitive Impairment in the Elderly).

Conflict of interest statement

Prof Winterer is coordinator of the BioCog Consortium and chief executive of the company Pharmaimage Biomarker Solutions GmbH. The company is one of the partners of the BioCog Consortium.

The remaining authors declare that they have no conflicts of interest.

Manuscript received on 25 May 2016, revised version accepted on 22 September 2016.

Corresponding author
Insa Feinkohl, PhD
Max-Delbrück-Centrum für Molekulare Medizin
in der Helmholtz-Gemeinschaft (MDC)
Robert-Rössle-Str. 10, 13092 Berlin, Germany
insa.feinkohl@mdc-berlin.de

Supplementary material
For eReferences please refer to:
www.aerzteblatt-international.de/ref0717

eFigures, eBoxes, eTables:
www.aerzteblatt-international.de/17m0110

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Del Ser T, Hachinski V, Merskey H, Munoz DG: An autopsy-verified study of the effect of education on degenerative dementia. Brain 1999; 122: 2309–19 CrossRef
e24.
Evans GW, Kantrowitz E: Socioeconomic status and health: the potential role of environmental risk exposure. Annu Rev Public Health 2002; 23: 303–31 CrossRef MEDLINE
e25.
Batty GD, Deary IJ, Macintyre S: Childhood IQ in relation to risk factors for premature mortality in middle-aged persons: the Aberdeen children of the 1950s study. J Epidemiol Community Health 2007; 61: 241–7 CrossRef MEDLINE PubMed Central
e26.
Lo RY, Jagust WJ: Effect of cognitive reserve markers on Alzheimer pathological progression. Alz Dis Ass Disord 2013; 27: 343–50 CrossRef MEDLINE PubMed Central
e27.
Evered LA, Silbert B, Scott DA, Ames D, Maruff PB: Cerebrospinal fluid biomarker for alzheimer disease predicts postoperative cognitive dysfunction. Anesthesiology 2016; 124: 353–61 CrossRef MEDLINE
e28.
Evered LA: Cognitive change that matters: the impact of cognitive change as a result of anaesthesia and surgery on functional outcomes and dementia. Melbourne, Australia: University of Melbourne 2013.
e29.
Feinkohl I, Winterer G, Pischon T: Obesity and post-operative cognitive dysfunction: a systematic review and meta-analysis. Diabetes Metab Res Rev 2016; 32: 643–51 CrossRef MEDLINE
e30.
Mõttus R, Luciano M, Starr JM, Deary IJ: Diabetes and life-long cognitive ability. J Psychosom Res 2013; 75: 275–8 CrossRef MEDLINE
e31.
von Renteln-Kruse W, Neumann L, Klugmann B, et al.: Geriatric patients with cognitive impairment. Dtsch Arztebl Int 2015; 112: 103–12 VOLLTEXT
e32.
Davies HT, Crombie IK, Tavakoli M: When can odds ratios mislead? BMJ 1998; 316: 989–91 CrossRef MEDLINE PubMed Central
e33.
Schmitt EM, Saczynski JS, Kosar CM, et al.: The successful aging after elective surgery study: cohort description and data quality procedures. JAGS 2015; 63: 2463–71 CrossRef MEDLINE PubMed Central
e34.
Deary IJ, Whalley LJ, Crawford JR: An ’instantaneous’ estimate of a lifetime’s cognitive change. Intelligence 2004; 32: 113–9 CrossRef
e35.
Brown LJE, Ferner HS, Robertson J, et al.: Differential effects of delirium on fluid and crystallized cognitive abilities. Arch Gerontol Geriatr 2011; 52: 153–8 CrossRef MEDLINE
e36.
McGurn B, Starr JM, Topfer JA, et al.: Pronunciation of irregular words is preserved in dementia, validating premorbid IQ estimation. Neurology 2004; 62: 1184–6 CrossRef MEDLINE
e37.
Hong SW, Shim JK, Choi YS, Kim DH, Chang BC, Kwak YL. Prediction of cognitive dysfunction and patients‘ outcome following valvular heart surgery and the role of cerebral oximetry. Eur J Cardiothorac Surg 2008; 33: 560–6 CrossRef MEDLINE
Molecular Epidemiology Research Group, Max Delbrück Center for Molecular Medicine in the Helmholtz Association (MDC), Berlin-Buch: Insa Feinkohl, PhD, Prof. Dr. med. Pischon, MPH
Charité – Universitätsmedizin Berlin: Prof. Dr. med. Winterer, Prof. Dr. med. Spies, Prof. Dr. med. Pischon, MPH
MDC/BIH Biobank, Max Delbrück Center for Molecular Medicine in the Helmholtz Association (MDC), Berlin-Buch and Berlin Institute of Health (BIH), Berlin: Prof. Dr. med. Pischon, MPH
Forest plot
Forest plot
Figure
Forest plot
Key messages
Overview of included studies
Overview of included studies
Table
Overview of included studies
Systematic search strategy
Systematic search strategy
eBox 1
Systematic search strategy
Results of main analyses in fixed effects models and random effects models
Results of main analyses in fixed effects models and random effects models
eBox 2
Results of main analyses in fixed effects models and random effects models
Flow chart for search on cognitive reserve and postoperative cognitive reserve (POCD)
Flow chart for search on cognitive reserve and postoperative cognitive reserve (POCD)
eFigure 1
Flow chart for search on cognitive reserve and postoperative cognitive reserve (POCD)
Years of education and risk of POCD in subgroup analyses according
Years of education and risk of POCD in subgroup analyses according
eFigure 2
Years of education and risk of POCD in subgroup analyses according
Funnel plot for meta-analysis of years of education and POCD
Funnel plot for meta-analysis of years of education and POCD
eFigure 3
Funnel plot for meta-analysis of years of education and POCD
Funnel plot for meta-analysis of high school education versus further/higher education and POCD
Funnel plot for meta-analysis of high school education versus further/higher education and POCD
eFigure 4
Funnel plot for meta-analysis of high school education versus further/higher education and POCD
Funnel plot for meta-analysis of high school education versus lower than high school education and POCD
Funnel plot for meta-analysis of high school education versus lower than high school education and POCD
eFigure 5
Funnel plot for meta-analysis of high school education versus lower than high school education and POCD
Funnel plot for meta-analysis of lower than high school education versus further/higher education and POCD
Funnel plot for meta-analysis of lower than high school education versus further/higher education and POCD
eFigure 6
Funnel plot for meta-analysis of lower than high school education versus further/higher education and POCD
Parameters assessed in the present review with corresponding search terms
Parameters assessed in the present review with corresponding search terms
eTable 1
Parameters assessed in the present review with corresponding search terms
Detailed summary of included studies
Detailed summary of included studies
eTable 2
Detailed summary of included studies
Subgroup analyses of included studies on education (years) and POCD (total N = 8)
Subgroup analyses of included studies on education (years) and POCD (total N = 8)
eTable 3
Subgroup analyses of included studies on education (years) and POCD (total N = 8)
1.Androsova G, Krause R, Winterer G, Schneider R: Biomarkers of postoperative delirium and cognitive dysfunction. Front Aging Neurosci 2015; 7: 112 CrossRef MEDLINE PubMed Central
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12.Stern Y: What is cognitive reserve? Theory and research application of the re-
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15.Kastaun S, Gerriets T, Schwarz NP, et al.: The relevance of postoperative cogni-
tive decline in daily living: results of a 1-year follow-up. J Cardiothor Vasc An 2016; 30: 297–303 CrossRef MEDLINE
16.Newman MF, Grocott HP, Mathew JP, et al.: Report of the substudy assessing the impact of neurocognitive function on quality of life 5 years after cardiac surgery. Stroke 2001; 32: 2874–81 CrossRef MEDLINE
17.Monk TG, Weldon C, Garvan CW, et al.: Predictors of cognitive dysfunction after major noncardiac surgery. Anesthesiology 2008; 108: 18–30 CrossRef MEDLINE
18.Steinmetz J, Christensen KB, Lund T, Lohse N, Rasmussen LS: The ISPOCD group. Long-term consequences of postoperative cognitive dysfunction. Anesthesiology 2009; 110: 548–55 CrossRef MEDLINE
19.Heyer EJ, Mergeche JL, Wang S, Gaudet JG, Connolly ES: Impact of cognitive dysfunction on survival in patients with and without statin use following carotid endarterectomy. Neurosurgery 2015; 77: 880–7 CrossRef MEDLINE
20.Monk TG, Price CC: Postoperative cognitive disorders. Curr Opin Crit Care 2011; 17: 376–81 CrossRef MEDLINE PubMed Central
21.Tsai TL, Sands LP, Leung JM: An update on postoperative cognitive dysfunction. Adv Anesth 2010; 28: 269–84 CrossRef MEDLINE PubMed Central
22.Terrando N, Brzezinski M, Degos V, et al.: Perioperative cognitive decline in the aging population. Mayo Clin Proc 2011; 86: 885–93 CrossRef MEDLINE PubMed Central
23.Martin JFV, de Melo ROV: Postoperative cognitive dysfunction after cardiac surgery. Rev Bras Cir Cardiovasc 2008; 23: 245–55 CrossRef MEDLINE
24.Stroup DF, Berlin JA, Morton SC, et al.: Meta-analysis of observational studies in epidemiology. A proposal for reporting. JAMA 2000; 283: 2008–12 CrossRef MEDLINE
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26.Moller JT, Cluitmans P, Rasmussen LS, et al.: Long-term postoperative cognitive dysfunction in the elderly: ISPOCD1 study. Lancet 1998; 351: 857–61 CrossRef CrossRef
27.Johnson T, Monk T, Rasmussen LS, et al.: Postoperative cognitive dysfunction in middle-aged patients. Anesthesiology 2002; 96: 1351–7 CrossRef MEDLINE
28.Di Carlo A, Perna AM, Pantoni L, et al.: Clinically relevant cognitive impairment after cardiac surgery: a 6-month follow-up study. J Neurol Sci 2001; 188: 85–93 CrossRef
29.Higgins JPT, Thompson SO: Quantifying heterogeneity in a meta-analysis. Stat Med 2002; 21: 1539–58 CrossRef MEDLINE
30.Canet J, Raeder J, Rasmussen LS, et al.: Cognitive dysfunction after minor surgery in the elderly. Acta Anaesthesiol Scand 2003; 47: 1204–10 CrossRef MEDLINE
31.Puskas F, Grocott HP, White WD, Mathew JP, Newman MF, Bar-Yosef S: Intraop-
erative hyperglycemia and cognitive decline after CABG. Ann Thorac Surg 2007; 84: 1467–73 CrossRef MEDLINE
32.Mathew JP, Grocott HP, Phillips-Bute B, et al.: Lower endotoxin immunity predicts increased cognitive dysfunction in elderly patients after cardiac surgery. Stroke 2003; 34: 508–13 CrossRef MEDLINE
33.Abildstrom H, Rasmussen LS, Rentowl P, et al.: Cognitive dysfunction 1–2 years after non-cardiac surgery in the elderly. Acta Anaesthesiol Scand 2000; 44: 1246–51 CrossRef MEDLINE
34.Heyer EJ, DeLaPaz R, Halazun HJ, et al.: Neuropsychological dysfunction in the absence of structural evidence for cerebral ischemia after uncomplicated carotid endarterectomy. Neurosurgery 2006; 58: 474–80 CrossRef MEDLINE PubMed Central
35. Mocco J, Wilson DA, Komotar RJ, et al.: Predictors of neurocognitive decline after carotid endarterectomy. Neurosurgery 2006; 58: 844–50 CrossRef MEDLINEPubMed Central
36.Heyer EJ, Mergeche JL, Anastasian ZH, Kim M, Mallon KA, Connolly ES: Arterial blood pressure management during carotid endarterectomy and early cognitive dysfunction. Neurosurgery 2014; 74: 245–53 CrossRef MEDLINE PubMed Central
37.Heyer EJ, Mergeche JL, Bruce SS, Connolly ES: Inflammation and cognitive dysfunction in type 2 diabetic carotid endarterectomy patients. Diabetes Care 2013; 36: 3283–6 CrossRef MEDLINE PubMed Central
38.Heyer EJ, Mergeche JL, Ward JT, et al.: Phosphodiesterase 4D single-nucleotide polymorphism 83 and cognitive dysfunction in carotid endarterectomy patients. Neurosurgery 2013; 73: 791–6 CrossRef MEDLINE PubMed Central
39.Mathew JP, Podgoreanu MV, Grocott HP, et al.: Genetic variants in P-selectin and C-reactive protein influence susceptibility to cognitive decline after cardiac surgery. J Am Coll Cardiol 2007; 49: 1934–42 CrossRef MEDLINE
40.Zhu SH, Ji MH, Gao DP, Li WY, Yang JJ: Association between perioperative blood transfusion and early postoperative cognitive dysfunction in aged patients following total hip replacement surgery. Upsala J Med Sci 2014; 119: 262–7 CrossRef MEDLINE PubMed Central
e1.McDonagh DL, Mathew JP, White WD, et al.: Cognitive function after major noncardiac surgery, apolipoprotein E4 genotype, and biomarkers of brain injury. Anesthesiology 2010; 112: 852–9 CrossRef MEDLINE PubMed Central
e2.Kotekar N, Kuruvilla CS, Murthy V: Postoperative cognitive dysfunction in the elderly: a prospective clinical study. Indian J Anaesth 2014; 58: 263–8 CrossRef MEDLINE PubMed Central
e3. Ni C, Xu T, Tian Y, et al.: Cerebral oxygen saturation after multiple perioperative influential factors predicts the occurrence of postoperative cognitive dysfunc-
tion. BMC Anesthesiol 2015; 15: 156 MEDLINE PubMed Central
e4. Ropacki SA, Bert AB, Ropacki MT, Rogers BL, Stern RA: The influence of cognitive reserve on neuropsychological functioning following coronary artery bypass grafting (CABG). Arch Clin Neuropsych 2007; 22: 73–85 CrossRef MEDLINE
e5.Medi C, Evered L, Silbert B, et al.: Subtle post-procedural cognitive dysfunction after atrial fibrillation ablation. J Am Coll Cardiol 2013; 62: 531–9 CrossRef MEDLINE
e6. Mathew JP, Mackensen GB, Phillips-Bute B, et al.: Effects of extreme hemodilution during cardiac surgery on cognitive function in the elderly. Anesthesiology 2007; 107: 577–84 CrossRef MEDLINE
e7. Mathew JP, White WD, Schinderle DB, et al.: Intraoperative magnesium administration does not improve neurocognitive function after cardiac surgery. Stroke 2013; 44: 3407–13 CrossRef MEDLINE PubMed Central
e8. Deary IJ, Brett CE: Predicting and retrodicting intelligence between childhood and old age in the 6-Day Sample of the Scottish Mental Survey 1947. Intelligence 2015; 50: 1–9 CrossRef MEDLINE PubMed Central
e9. Bickel H, Kurz A: Education, occupation, and dementia: the Bavarian School Sisters Study. Dement Geriatr Cogn 2009; 27: 548–56 CrossRef MEDLINE
e10.Foubert-Samier A, Catheline G, Amieva H, et al.: Education, occupation, leisure activities, and brain reserve: a population-based study. Neurobiol Aging 2012; 33: 423 .e15–.e25.
e11. Mõttus R, Gale CR, Starr JM, Deary IJ: „On the street where you live“: neighbourhood deprivation and quality of life among community-dwelling older people in Edinburgh, Scotland. Soc Sci Med 2012; 74: 1368–74 CrossRef MEDLINE
e12.Zhang Y, Qian Y, Si Y, Bao H, Zhou J: Differential expressions of serum cytokines in cognitive dysfunction patients after colorectal surgery. Xi Bao Yu Fen Zi Mian Yi Xue Za Zhi 2015; 31: 231–4 MEDLINE
e13. Tan WF, Zhao YH, Fang B, Ma H, Wang JK: A case-control study on the risk factors in postoperative cognitive dysfunction induced by patient self-controlled intravenous analgesia. Zhonghua Liu Xing Bing Xue Za Zhi 2008; 29: 188–90 MEDLINE
e14. Pan LF, Wang DX, Li J: Effects of different methods of anesthesia and analgesia on early postoperative cognitive dysfunction after non-cardiac surgery in the elderly. Beijing Da Xue Xue Bao 2006; 38: 510–4 MEDLINE
e15. Wang SY, Ling K, Guang-yan B, Guang-wu W: Effects of epidural analgesia and intravenous analgesia on early postoperative cognitive dysfunction after limb orthopedics surgery in the elderly. J Clin Rehab Tissue Engin Res 2011; 15: 6514–7.
e16. Lin Y, Chen J, Wang Z: Meta-analysis of factors which influence delirium following cardiac surgery. J Card Surg 2012; 27(4): 481–92 CrossRef MEDLINE
e17.Saczynski JS, Inoye SK, Kosar CM, et al.: Cognitive and brain reserve and the risk of postoperative delirium in older patients. Lancet Psychiatry 2014; 1: 437–43 CrossRef
e18. Riedel B, Browne K, Silbert B: Cerebral protection: inflammation, endothelial dysfunction, and postoperative cognitive dysfunction. Curr Op Anaesthesiol 2014; 27: 89–97 CrossRef MEDLINE
e19.Krenk L, Rasmussen LS, Kehlet H: New insights into the pathophysiology of postoperative cognitive dysfunction. Acta Anaesthesiol Scand 2010; 54: 951–6 CrossRef MEDLINE
e20. Whalley LJ, Deary IJ, Appleton CL, Starr JM: Cognitive reserve and the neurobiology of cognitive ageing. Ageing Res Rev 2004; 3: 369–82 CrossRef MEDLINE
e21.Pietschnig J, Penke L, Wicherts JM, Zeiler M, Voracek M: Meta-analysis of associations between human brain volume and intelligence differences: how strong are they and what do they mean? Neurosci Biobehav Rev 2015; 47: 411–32.
e22. Satz P, Cole MA, Hardy DJ, Rassovsky Y: Brain and cognitive reserve: Mediator(s) and construct validity, a critique. J Clin Exp Neuropsychol 2011; 33: 121–30 CrossRef MEDLINE
e23.Del Ser T, Hachinski V, Merskey H, Munoz DG: An autopsy-verified study of the effect of education on degenerative dementia. Brain 1999; 122: 2309–19 CrossRef
e24. Evans GW, Kantrowitz E: Socioeconomic status and health: the potential role of environmental risk exposure. Annu Rev Public Health 2002; 23: 303–31 CrossRef MEDLINE
e25. Batty GD, Deary IJ, Macintyre S: Childhood IQ in relation to risk factors for premature mortality in middle-aged persons: the Aberdeen children of the 1950s study. J Epidemiol Community Health 2007; 61: 241–7 CrossRef MEDLINE PubMed Central
e26. Lo RY, Jagust WJ: Effect of cognitive reserve markers on Alzheimer pathological progression. Alz Dis Ass Disord 2013; 27: 343–50 CrossRef MEDLINE PubMed Central
e27. Evered LA, Silbert B, Scott DA, Ames D, Maruff PB: Cerebrospinal fluid biomarker for alzheimer disease predicts postoperative cognitive dysfunction. Anesthesiology 2016; 124: 353–61 CrossRef MEDLINE
e28. Evered LA: Cognitive change that matters: the impact of cognitive change as a result of anaesthesia and surgery on functional outcomes and dementia. Melbourne, Australia: University of Melbourne 2013.
e29. Feinkohl I, Winterer G, Pischon T: Obesity and post-operative cognitive dysfunction: a systematic review and meta-analysis. Diabetes Metab Res Rev 2016; 32: 643–51 CrossRef MEDLINE
e30. Mõttus R, Luciano M, Starr JM, Deary IJ: Diabetes and life-long cognitive ability. J Psychosom Res 2013; 75: 275–8 CrossRef MEDLINE
e31. von Renteln-Kruse W, Neumann L, Klugmann B, et al.: Geriatric patients with cognitive impairment. Dtsch Arztebl Int 2015; 112: 103–12 VOLLTEXT
e32. Davies HT, Crombie IK, Tavakoli M: When can odds ratios mislead? BMJ 1998; 316: 989–91 CrossRef MEDLINE PubMed Central
e33. Schmitt EM, Saczynski JS, Kosar CM, et al.: The successful aging after elective surgery study: cohort description and data quality procedures. JAGS 2015; 63: 2463–71 CrossRef MEDLINE PubMed Central
e34. Deary IJ, Whalley LJ, Crawford JR: An ’instantaneous’ estimate of a lifetime’s cognitive change. Intelligence 2004; 32: 113–9 CrossRef
e35. Brown LJE, Ferner HS, Robertson J, et al.: Differential effects of delirium on fluid and crystallized cognitive abilities. Arch Gerontol Geriatr 2011; 52: 153–8 CrossRef MEDLINE
e36. McGurn B, Starr JM, Topfer JA, et al.: Pronunciation of irregular words is preserved in dementia, validating premorbid IQ estimation. Neurology 2004; 62: 1184–6 CrossRef MEDLINE
e37.Hong SW, Shim JK, Choi YS, Kim DH, Chang BC, Kwak YL. Prediction of cognitive dysfunction and patients‘ outcome following valvular heart surgery and the role of cerebral oximetry. Eur J Cardiothorac Surg 2008; 33: 560–6 CrossRef MEDLINE