The authors have declared that no competing interests exist.
Conceived and designed the experiments: LP LX WOY. Performed the experiments: LP LX. Analyzed the data: LP LX. Contributed reagents/materials/analysis tools: LX. Wrote the manuscript: LP LX. Final approval of the submitted version: WOY.
Postoperative cognitive dysfunction (POCD) is common following cardiac and non-cardiac surgery, but the pathogenic mechanisms remain unknown. Many studies suggest that an inflammatory response is a key contributor to POCD. The current meta-analysis shows that the levels of peripheral inflammatory markers are associated with POCD.
An online search was performed to identify peer-reviewed studies without language restriction that measured peripheral inflammatory markers of patients with and without POCD, using PubMed, ScienceDirect, SinoMed and the National Knowledge Infrastructure database. Extracted data were analyzed with STATA (version 12).The standardized mean difference (SMD) and the 95% confidence interval (95%CI) were calculated for each outcome using a random effect model. Tests of heterogeneity assessment of bias, and meta-regression were performed in the meta-analysis.
A total of 13 studies that measured the concentrations of peripheral inflammatory markers were included. The current meta-analysis found significantly higher concentrations of S-100β(SMD[95%CI]) (1.377 [0.423, 2.331], p-value < 0.001, N [POCD/non-POCD] =178/391, 7 studies), and interleukin(IL)-6 (SMD[95%CI]) (1.614 [0.603,2.624], p-value < 0.001, N[POCD/non-POCD] = 91/99, 5 studies), but not of neuron specific enolase, interleukin-1β, or tumor necrosis factor-α , in POCD compared with patients without POCD. In meta-regression analyses, a significant positive association was found between the SMD and the preoperative interleukin-6 peripheral blood concentration in patients with POCD (Coef.= 0.0587, p-value=0.038, 5 studies).
This study shows that POCD is indeed correlated with the concentrations of peripheral inflammatory markers, particularly interleukin-6 and S-100β.
Postoperative cognitive dysfunction (POCD) usually manifests as an alteration in orientation, memory, thinking, attention, insight or other aspects of central nervous function. Initially, it was thought to be associated with cardiac surgery. However, later studies showed that it has been associated with non-cardiac surgery and even with non-invasive procedures such as coronary angiography [
Thus, POCD is an important concern for the anesthesiologist.
Considerable evidence suggests that an inflammatory response may be involved in the occurrence of POCD [
All analyses were performed according to PRISMA guidelines [
Original studies measuring inflammatory marker concentrations in living subjects with POCD were included. Inclusion criteria were as follows: 1.) case-control study including non-POCD subjects as controls; 2.) human subjects; 3.) explicit diagnostic criteria such as the Confusion Assessment Method [
Studies were excluded if: 1.) the article was a case report; 2.) the trials measured inflammatory marker concentrations from peripheral blood cells following additional stimulation; 3.) the trials did not group the results according to POCD status; 4.) the date were in an unavailable format.
Three independent raters examined each retrieved article. The results were compared between raters and any disagreements regarding inclusion were settled by consensus. The methods and results sections of each relevant article were analyzed, and cytokine concentration metrics for POCD and non-POCD groups were extracted, in the formats: mean (standard deviation, SD), median (interquartile range, IQR) or median (range, R). If data were presented in the format from which means and SDs were not extractable, these measures were tried to request from the corresponding author of the publication. If data were presented in the format median(R), our simulations show that the formula “R/4” is the best estimator of the standard deviation (variance) for moderately sized samples (15<n≤70). For large samples (n > 70), the formula “R/6” gives the best estimator for the standard deviation [
Three authors independently assessed the qualities of included studies using the Newcastle-Ottawa scale (NOS) [
The standardized mean difference (SMD) and 95% confidence interval (95%CI) were calculated for each outcome using a random effect model (the DerSimonian and Laird method). Random effect models were preferable if significant heterogeneity was expected because they assumed and accounted for variable underlying effects in estimates of uncertainty, including both within-study and between-study variance. A Q statistic was calculated using a chi-squared test to quantify the heterogeneity among combined results. A significant Q statistic indicates diversity in the characteristics of the combined trials. Inconsistency was calculated using an I2 index to determine the impact of heterogeneity.
To identify potential sources of heterogeneity, planned subgroup analyses were conducted in studies where control subjects were matched for age and gender, in studies excluding subjects with inflammatory comorbidity, and in studies using comparable assay methodology. Planned study level meta-regression analyses were conducted comparing SMDs to pre-operative peripheral inflammatory markers, age, and gender. Sensitivity analysis was used to investigate the influence of each individual study on the overall meta-analysis summary estimate.
The risk of publication bias was assessed using funnel plots and Egger’s tests. Funnel plots were used to plot the effect size of the component studies against the sample size, and Egger’s tests were used to detect skewness in the funnel plots, and by extension, publication bias in the data. The risk of selective reporting bias was examined within the studies. When the difference between groups was not significant, Altman’s method for describing confidence intervals was used. Meta-regression analysis (using metareg) was used to test whether effect sizes were influenced by specific study design features. Analyses were performed using STATA, version 12.0 (Stata Corporation, College Station, Texas, 2012)
We included 13 eligible studies [
Significantly higher peripheral blood inflammatory marker concentrations (SMD[95%CI]) were detected in POCD subjects compared with non-POCD subjects when examining S-100β(1.377 [0.423 , 2.331], p-value < 0.001 N[POCD/non-POCD] = 178/391,7 studies,
Forest plot for S-100β displaying the results of the random effects meta-analysis for the association between peripheral blood S-100β and postoperative cognitive dysfunction (POCD). The standardized mean difference is presented on the horizontal axis; positive values denote higher serum levels in POCD patients; negative values denote higher serum levels in control subjects. The dashed line is at the overall standardized mean difference. CI, confidence interval; SMD, standardized mean difference.
Forest plot for IL-6 displaying the results of the random-effects meta-analysis for the association between peripheral blood IL-6 concentrations and POCD. The standardized mean difference is presented on the horizontal axis; positive values denote higher serum levels in patients; negative values denote higher serum levels in control subjects. The dashed line is at the overall weighted mean difference. CI, confidence interval; SMD, standardized mean difference.
Main Effect |
Heterogeneity |
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Cytokine | Studies | N (P/NP) | SMD | 95% CI | Z | p | Chi2 | df | p | I2 |
S-100β | 7 | 178/391 | 1.377 | 0.423, 2.331 | 2.83 | 0.005 | 117.35 | 6 | 0.000 | 94.9% |
IL-6 | 5 | 91/99 | 1.614 | 0.603,2.624 | 3.13 | 0.002 | 43.78 | 4 | 0.000 | 90.9% |
NSE | 6 | 156/347 | 0.377 | -0.042,0.796 | 1.76 | 0.078 | 20.84 | 5 | 0.001 | 76.0% |
IL-1β | 3 | 47/70 | 0.612 | -0.439,1.662 | 1.14 | 0.254 | 14.19 | 2 | 0.001 | 85.9% |
TNF-α | 4 | 86/105 | 0.374 | -0.341,1.089 | 1.03 | 0.305 | 16.31 | 3 | 0.001 | 81.6% |
S-100β, S-100β protein; IL-6, interleukin-6; NSE, neuron specific enolase; IL-1β, interleukin-1β; TNF-α, tumor necrosis factor-α;N(P/NP), number of patients with POCD/number of patients without POCD;SMD, standardized mean difference (SMD);95% CI, 95% confidence interval
All inflammatory marker concentrations were compared in pictograms per milliliter or milligrams per milliliter; however, significant heterogeneity was found in all comparisons. For NSE, an I2 index of 76% indicated moderate heterogeneity, but we observed no significance relationship between elevated plasma NSE concentrations and POCD (p-value = 0.078 in 5 studies POCD/non-POCD=135/282). S-100β and IL-6 demonstrate significant relationships with POCD status, but the heterogeneity is high (for S-100β: χ2 = 117.35([d.f. = 6] ), p-value = 0.000, I2=94.9%, τ2=1.5417; for IL-6: χ2 = 43.78([d.f. = 4], p-value = 0.000, I2 = 90.9%, τ2= 1.190) (
Sensitivity analyses were conducted to ascertain the primary origin of the heterogeneity. For all inflammatory markers, no single study qualitatively changed the SMD, no point estimate of its "omitted" analysis lies outside the confidence interval of the "combined" analysis. Its "omitted" meta-analytic estimate differs in significance relative to the "combined" analysis. Those suggested that the results of this meta-analysis was stable.
Meta-regression analyses were used to assess the associations between the preoperative and postoperative peripheral blood concentrations of the studied inflammatory markers. We conducted this analysis only if the preoperative and postoperative peripheral blood concentrations had at least five measurements from different studies and had either a significant SMD or significant heterogeneity in the absence of a significant SMD. Meta-regression analyses found a significant positive association between the SMD and the preoperative IL-6 peripheral blood concentration in patients with POCD (Coef. = 0.0587, p-value = 0.038, 5 studies,
Plot of the preoperative IL-6 peripheral blood concentration vs. the peripheral blood IL-6 SMD in the 5 included studies showing a fitted random effects meta-regression line.( 5 studies, Coef.=0 .0587 ,p-value = 0.038 ) Coef., coefficient.
Cytokine | Number of studies | tau2 | I2 res | Adjusted R2 | Coef. | Std. Err. | t | P>|t| | [95% CI] |
---|---|---|---|---|---|---|---|---|---|
S100β |
6 | 2.106 | 94.27% | 9.22% | 9.554 | 7.839 | 1.22 | 0.290 | -12.21,31.32 |
IL-6 |
5 | 0.2118 | 61.02% | 87.46% | 0.0587 | 0 .0166 | 3.54 | 0.038 | 0.0059 0 .1114 |
# Preoperative S-100β peripheral blood concentration of all patients
## Preoperative IL-6 peripheral blood concentration of patients with POCD
tau2, estimate of between-study variance by residual maximum likelihood model;
I2 res, percentage of residual variation due to heterogeneity;
Adjusted R2, Proportion of between-study variance explained;
Coef., coefficient; Std. Err., standard error; 95% CI, 95% confidence interval.
Plot of the preoperative S-100β peripheral blood concentration vs. the peripheral blood S-100β SMD in the 6 included studies, showing a random effects meta-regression line. (6 studies, Coef.= 9.554,p-value = 0.290 ) Coef., coefficient.
Significant risk of publication bias was not detected, as demonstrated by funnel plots, and no significant correlations were found between effect size and sample size among studies of peripheral blood S-100β, NSE and inflammatory cytokines, including IL-1β, IL-6 and TNF-α. However, tests for funnel plot asymmetry were only recommended for use when at least 10 studies were included in the meta-analysis. Therefore, Egger’s test was implemented to evaluate asymmetry and publication bias. The results showed no evidence of publication bias: simultaneous reporting of negative results suggested a lower risk of reporting bias; the majority of included studies examined multiple biomarkers, and the majority of studies reported at least one significant comparison also reported at least one non-significant comparison. (
Egger’s test (bias) |
|||||
---|---|---|---|---|---|
Cytokine | Coef | 95% CI | t | p | |
S-100β | 5.998 | -6.389,18.39 | 1.24 | 0.268 | |
IL-6 | 10.19 | -1.384 ,21.76 | 2.80 | 0.068 | |
NSE | -0.3398 | -2.997,2.317 | 0.74 | 0.517 | |
IL-1β | 23.19 | -35.50,81.87 | 5.02 | 0.125 | |
TNF-α | -4.995 | -40.44,30.45 | -0.61 | 0.606 |
S-100β, S-100β protein; IL-6, interleukin-6; NSE, neuron specific enolase; IL-1β, interleukin-1β; TNF-α, tumor necrosis factor-α;Coef., coefficient; 95% CI, 95% confidence interval.
A study by van Harten and colleagues showed that an immunological reaction was one of the most important causative factors of cardiac POCD [
The concentrations of IL-1 and TNF-α did not differ significantly between the subjects with POCD and the control subjects. Following surgery, elderly patients often suffered from POCD, which could persist long after physical recovery. Surgery-induced tissue damage could activate the peripheral innate immune system, resulting the release of inflammatory mediators [
IL-1β was a pro-inflammatory cytokine that contributed to neuro-inflammation in many central nervous system (CNS) disorders [
It was possible that our findings could not be interpreted as truly negative due to small sample sizes and significant heterogeneity between studies. Additional evidence demonstrated inflammatory activity with POCD, which could be the mechanism through which peripheral pro-inflammatory markers induced POCD. In mouse models, Barrientos and colleagues demonstrated that a single intracisternal administration of interleukin-1 receptor antagonist (IL-1RA) at the time of surgery was sufficient to block both the behavioral deficits and the neuro-inflammatory response. Injecting the same dose of IL-1RA peripherally failed to have a protective effect. These data provided strong support for the specific role of central, but not peripheral, IL-1β in POCD [
Following surgery under general anesthesia, TNF-α was the first cytokine to be released, and its concentration peaked (p-value < 0.05) 30 min after surgery. Terrando explained that TNF-α was important in cognitive decline. TNF-α was upstream of IL-1 and stimulates its production in the brain. Peripheral blockade of TNF-α could limit the release of IL-1 and prevent neuro-inflammation and cognitive decline in a mouse model of surgery-induced cognitive decline [
Although POCD was a common complication of major surgery, its pathogenic mechanisms remained unknown. However, the contribution of several risk factors, including advanced age, duration of anesthesia, a second operation, low education level, postoperative infection, and respiratory complications, have been identified [
A clinically relevant concentration of β-amyloid generation and aggregation was a key factor in the pathogenesis of Alzheimer’s disease [
Lipopolysaccharide (LPS) came from gram-negative bacteria and it was an endotoxin that could cause a strong immune response. When LPS bound the CD14/Toll-like receptor 4 /MD2 complex, it could stimulate the inflammatory cells to secrete a variety of cytokines. Some studies have examined the relationship between LPS and POCD [
Observational studies could not clearly infer a causal relationship. Thus, the possibility that increased concentrations of pro-inflammatory cytokines were a consequence of POCD pathology should also be considered. Cibelli and colleagues explored whether systemic inflammation in response to surgical trauma triggers hippocampal inflammation and subsequent memory impairment in a mouse model of orthopedic surgery. Their studies suggested that inflammation play a critical role in the pathogenesis of POCD, as evidenced by the protection afforded to surgical animals by minocycline which was a nonspecific inhibitor of inflammation [
Peripheral pro-inflammatory signals can be actively propagated across the blood brain barrier (BBB) via crosstalk between peripheral and central immune cells [
The S-100β protein has been used as a marker of neuronal damage in various diseases [
Li and colleagues found that the serum levels of the pro-inflammatory markers IL-6 and S-100β increased after general anesthesia in total hip-replacement surgery, and these increases may be associated with the occurrence of POCD [
POCD is a growing and largely underestimated problem without a defined etiology. Globally, experts were focused on discovering risk factors for the occurrence of POCD and developing precautions to reduce its incidence rate [
As the global aging progresses, the search for new preventative measures and treatment strategies to maintain higher brain functions throughout life is of major economic and medical importance [
The present meta-analysis examining the role of peripheral inflammatory marks in POCD has several methodological limits. The literature search was limited to unstimulated cytokines (IL-1β, IL-6, TNF-α), NSE, and S-100β; however, other inflammatory markers (e.g. IL-10, high mobility group box 1(HMGB-1), NF-κB) have also been informative [
The present study was also limited by the use of a categorical diagnosis of POCD; thus, POCD severity effects could not be systematically investigated. Meta-regression analyses in subgroups of studies reporting preoperative mean IL-6 and S-100β protein levels suggested that the preoperative level of some inflammatory markers might have contributed to the heterogeneity.
Furthermore, in cross-sectional studies, continuous and stochastic elevations could not be distinguished, and differences in the secretion patterns and half-lives of different cytokines might have a considerable impact on their measured concentrations. Most inflammatory markers immediately reached the peak postoperative value [
Differences in enzyme linked immunosorbent assay (ELISA) techniques were investigated as a potential source of heterogeneity; however, many other assay parameters and methodological differences in the collection and handling of the samples that could not be systematically addressed might have contributed to heterogeneity.
Funnel plots and Egger's tests did not suggest the presence of publication bias. However, many observational studies were not registered with clinical trials data-bases, so the scope of the unpublished literature could not be ascertained and effects of bias at the study and outcome levels could not be ruled out. In addition, this article was mainly based on studies published in the English and Chinese language, and bias might have exist in the literature published in other languages.
In conclusion, our meta-analysis provides evidence that POCD is indeed correlated with the concentrations of IL-6 and S-100β. Furthermore, the meta-regression shows that IL-6 might serve an indicator to guide the prevention and treatment of POCD. Because POCD is a common postoperative complication and is related multiple factors, further investigation of the inflammatory response regulatory pathways, and the specific contributions of IL-6 and gene polymorphisms is necessary and meaningful.
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This work was supported by JianBin Tong, Yi Wang and Xuyuan Kuang.