Integrated Multi-Omics Analysis of Cerebrospinal Fluid in Postoperative Delirium.

Preoperative risk biomarkers for delirium may aid in identifying high-risk patients and developing intervention therapies, which would minimize the health and economic burden of postoperative delirium. Previous studies have typically used single omics approaches to identify such biomarkers. Preoperative cerebrospinal fluid (CSF) from the Healthier Postoperative Recovery study of adults ≥ 63 years old undergoing elective major orthopedic surgery was used in a matched pair delirium case-no delirium control design. We performed metabolomics and lipidomics, which were combined with our previously reported proteomics results on the same samples. Differential expression, clustering, classification, and systems biology analyses were applied to individual and combined omics datasets. Probabilistic graph models were used to identify an integrated multi-omics interaction network, which included clusters of heterogeneous omics interactions among lipids, metabolites, and proteins. The combined multi-omics signature of 25 molecules attained an AUC of 0.96 [95% CI: 0.85-1.00], showing improvement over individual omics-based classification. We conclude that multi-omics integration of preoperative CSF identifies potential risk markers for delirium and generates new insights into the complex pathways associated with delirium. With future validation, this hypotheses-generating study may serve to build robust biomarkers for delirium and improve our understanding of its pathophysiology.

Biomarkers of neurodegeneration and neural injury as potential predictors for delirium.

OBJECTIVES: Determine if biomarkers of Alzheimer's disease and neural injury may play a role in the prediction of delirium risk. METHODS: In a cohort of older adults who underwent elective surgery, delirium case-no delirium control pairs (N = 70, or 35 matched pairs) were matched by age, sex and vascular comorbidities. Biomarkers from CSF and plasma samples collected prior to surgery, including amyloid beta (Aß)42 , Aß40 , total (t)-Tau, phosphorylated (p)-Tau181 , neurofilament-light (NfL), and glial fibrillary acid protein (GFAP) were measured in cerebrospinal fluid (CSF) and plasma using sandwich enzyme-linked immunosorbent assays (ELISAs) or ultrasensitive single molecule array (Simoa) immunoassays. RESULTS: Plasma GFAP correlated significantly with CSF GFAP and both plasma and CSF GFAP values were nearly two-fold higher in delirium cases. The median paired difference between delirium case and control without delirium for plasma GFAP was not significant (p = 0.074) but higher levels were associated with a greater risk for delirium (odds ratio 1.52, 95% confidence interval 0.85, 2.72 per standard deviation increase in plasma GFAP concentration) in this small study. No matched pair differences or associations with delirium were observed for NfL, p-Tau 181, Aß40 and Aß42 . CONCLUSIONS: These preliminary findings suggest that plasma GFAP, a marker of astroglial activation, may be worth further investigation as a predictive risk marker for delirium.

Comparison of the frailty index and frailty phenotype and their associations with postoperative delirium incidence and severity.

BACKGROUND: Recent studies have reported an association between presurgical frailty and postoperative delirium. However, it remains unclear whether the frailty-delirium relationship differs by measurement tool (e.g., frailty index vs. frailty phenotype) and whether frailty is associated with delirium, independent of preoperative cognition. METHODS: We used the successful aging after elective surgery (SAGES) study, a prospective cohort of older adults age ≥70 undergoing major non-cardiac surgery (N = 505). Preoperative measurement of the modified mini-mental (3MS) test, frailty index and frailty phenotype were obtained. The confusion assessment method (CAM), supplemented by chart review, identified postoperative delirium. Delirium feature severity was measured by the sum of CAM-severity (CAM-S) scores. Generalized linear models were used to determine the relative risk of each frailty measure with delirium incidence and severity. Subsequent models adjusted for age, sex, surgery type, Charlson comorbidity index, and 3MS. RESULTS: On average, patients were 76.7 years old (standard deviation 5.22), 58.8% of women. For the frailty index, the incidence of delirium was 14% in robust, 17% in prefrail, and 31% in frail patients (p < 0.001). For the frailty phenotype, delirium incidence was 13% in robust, 21% in prefrail, and 27% in frail patients (p = 0.016). Frailty index, but not phenotype, was independently associated with delirium after adjustment for comorbidities (relative risk [RR] 2.13, 95% confidence interval [CI] 1.23-3.70; RR 1.61, 95% CI 0.77-3.37, respectively). Both frailty measures were associated with delirium feature severity. After adjustment for preoperative cognition, only the frailty index was associated with delirium incidence; neither index nor phenotype was associated with delirium feature severity. CONCLUSION: Both the frailty index and phenotype were associated with the development of postoperative delirium. The index showed stronger associations that remained significant after adjusting for baseline comorbidities and preoperative cognition. Measuring frailty prior to surgery can assist in identifying patients at risk for postoperative delirium.

Patterns and Persistence of Perioperative Plasma and Cerebrospinal Fluid Neuroinflammatory Protein Biomarkers After Elective Orthopedic Surgery Using SOMAscan.

BACKGROUND: The neuroinflammatory response to surgery can be characterized by peripheral acute plasma protein changes in blood, but corresponding, persisting alterations in cerebrospinal fluid (CSF) proteins remain mostly unknown. Using the SOMAscan assay, we define acute and longer-term proteome changes associated with surgery in plasma and CSF. We hypothesized that biological pathways identified by these proteins would be in the categories of neuroinflammation and neuronal function and define neuroinflammatory proteome changes associated with surgery in older patients. METHODS: SOMAscan analyzed 1305 proteins in blood plasma (n = 14) and CSF (n = 15) samples from older patients enrolled in the Role of Inflammation after Surgery for Elders (RISE) study undergoing elective hip and knee replacement surgery with spinal anesthesia. Systems biology analysis identified biological pathways enriched among the surgery-associated differentially expressed proteins in plasma and CSF. RESULTS: Comparison of postoperative day 1 (POD1) to preoperative (PREOP) plasma protein levels identified 343 proteins with postsurgical changes ( P < .05; absolute value of the fold change [|FC|] > 1.2). Comparing postoperative 1-month (PO1MO) plasma and CSF with PREOP identified 67 proteins in plasma and 79 proteins in CSF with altered levels ( P < .05; |FC| > 1.2). In plasma, 21 proteins, primarily linked to immune response and inflammation, were similarly changed at POD1 and PO1MO. Comparison of plasma to CSF at PO1MO identified 8 shared proteins. Comparison of plasma at POD1 to CSF at PO1MO identified a larger number, 15 proteins in common, most of which are regulated by interleukin-6 (IL-6) or transforming growth factor beta-1 (TGFB1) and linked to the inflammatory response. Of the 79 CSF PO1MO-specific proteins, many are involved in neuronal function and neuroinflammation. CONCLUSIONS: SOMAscan can characterize both short- and long-term surgery-induced protein alterations in plasma and CSF. Acute plasma protein changes at POD1 parallel changes in PO1MO CSF and suggest 15 potential biomarkers for longer-term neuroinflammation that warrant further investigation.

Proteome-Wide Analysis Using SOMAscan Identifies and Validates Chitinase-3-Like Protein 1 as a Risk and Disease Marker of Delirium Among Older Adults Undergoing Major Elective Surgery.

BACKGROUND: Delirium (an acute change in cognition) is a common, morbid, and costly syndrome seen primarily in aging adults. Despite increasing knowledge of its epidemiology, delirium remains a clinical diagnosis with no established biomarkers to guide diagnosis or management. Advances in proteomics now provide opportunities to identify novel markers of risk and disease progression for postoperative delirium and its associated long-term consequences (eg, long-term cognitive decline and Alzheimer's disease [AD]). METHODS: In a nested matched case-control study (18 delirium/no-delirium pairs) within the Successful Aging after Elective Surgery study (N = 556), we evaluated the association of 1305 plasma proteins preoperatively [PREOP] and on postoperative day 2 [POD2]) with delirium using SOMAscan. Generalized linear models were applied to enzyme-linked immunosorbant assay (ELISA) validation data of one protein across the full cohort. Multi-protein modeling included delirium biomarkers identified in prior work (C-reactive protein, interleukin-6 [IL6]). RESULTS: We identified chitinase-3-like-protein-1 (CHI3L1/YKL-40) as the sole delirium-associated protein in both a PREOP and a POD2 predictor model, a finding confirmed by ELISA. Multi-protein modeling found high PREOP CHI3L1/YKL-40 and POD2 IL6 increased the risk of delirium (relative risk [95% confidence interval] Quartile [Q]4 vs Q1: 2.4[1.2-5.0] and 2.1[1.1-4.1], respectively). CONCLUSIONS: Our identification of CHI3L1/YKL-40 in postoperative delirium parallels reports of CHI3L1/YKL-40 and its association with aging, mortality, and age-related conditions including AD onset and progression. This highlights the type 2 innate immune response, involving CHI3L1/YKL-40, as an underlying mechanism of postoperative delirium, a common, morbid, and costly syndrome that threatens the independence of older adults.

Development and internal validation of a predictive model of cognitive decline 36 months following elective surgery.

INTRODUCTION: Our goal was to determine if features of surgical patients, easily obtained from the medical chart or brief interview, could be used to predict those likely to experience more rapid cognitive decline following surgery. METHODS: We analyzed data from an observational study of 560 older adults (≥70 years) without dementia undergoing major elective non-cardiac surgery. Cognitive decline was measured using change in a global composite over 2 to 36 months following surgery. Predictive features were identified as variables readily obtained from chart review or a brief patient assessment. We developed predictive models for cognitive decline (slope) and predicting dichotomized cognitive decline at a clinically determined cut. RESULTS: In a hold-out testing set, the regularized regression predictive model achieved a root mean squared error (RMSE) of 0.146 and a model r-square (R2 ) of .31. Prediction of "rapid" decliners as a group achieved an area under the curve (AUC) of .75. CONCLUSION: Some of our models could predict persons with increased risk for accelerated cognitive decline with greater accuracy than relying upon chance, and this result might be useful for stratification of surgical patients for inclusion in future clinical trials.

Plasma and cerebrospinal fluid inflammation and the blood-brain barrier in older surgical patients: the Role of Inflammation after Surgery for Elders (RISE) study.

BACKGROUND: Our understanding of the relationship between plasma and cerebrospinal fluid (CSF) remains limited, which poses an obstacle to the identification of blood-based markers of neuroinflammatory disorders. To better understand the relationship between peripheral and central nervous system (CNS) markers of inflammation before and after surgery, we aimed to examine whether surgery compromises the blood-brain barrier (BBB), evaluate postoperative changes in inflammatory markers, and assess the correlations between plasma and CSF levels of inflammation. METHODS: We examined the Role of Inflammation after Surgery for Elders (RISE) study of adults aged ≥ 65 who underwent elective hip or knee surgery under spinal anesthesia who had plasma and CSF samples collected at baseline and postoperative 1 month (PO1MO) (n = 29). Plasma and CSF levels of three inflammatory markers previously identified as increasing after surgery were measured using enzyme-linked immunosorbent assay: interleukin-6 (IL-6), C-reactive protein (CRP), and chitinase 3-like protein (also known as YKL-40). The integrity of the BBB was computed as the ratio of CSF/plasma albumin levels (Qalb). Mean Qalb and levels of inflammation were compared between baseline and PO1MO. Spearman correlation coefficients were used to determine the correlation between biofluids. RESULTS: Mean Qalb did not change between baseline and PO1MO. Mean plasma and CSF levels of CRP and plasma levels of YKL-40 and IL-6 were higher on PO1MO relative to baseline, with a disproportionally higher increase in CRP CSF levels relative to plasma levels (CRP tripled in CSF vs. increased 10% in plasma). Significant plasma-CSF correlations for CRP (baseline r = 0.70 and PO1MO r = 0.89, p < .01 for both) and IL-6 (PO1MO r = 0.48, p < .01) were observed, with higher correlations on PO1MO compared with baseline. CONCLUSIONS: In this elective surgical sample of older adults, BBB integrity was similar between baseline and PO1MO, plasma-CSF correlations were observed for CRP and IL-6, plasma levels of all three markers (CRP, IL-6, and YKL-40) increased from PREOP to PO1MO, and CSF levels of only CRP increased between the two time points. Our identification of potential promising plasma markers of inflammation in the CNS may facilitate the early identification of patients at greatest risk for neuroinflammation and its associated adverse cognitive outcomes.

Targeted metabolomics analysis of postoperative delirium.

Postoperative delirium is the most common complication among older adults undergoing major surgery. The pathophysiology of delirium is poorly understood, and no blood-based, predictive markers are available. We characterized the plasma metabolome of 52 delirium cases and 52 matched controls from the Successful Aging after Elective Surgery (SAGES) cohort (N = 560) of patients ≥ 70 years old without dementia undergoing scheduled major non-cardiac surgery. We applied targeted mass spectrometry with internal standards and pooled controls using a nested matched case-control study preoperatively (PREOP) and on postoperative day 2 (POD2) to identify potential delirium risk and disease markers. Univariate analyses identified 37 PREOP and 53 POD2 metabolites associated with delirium and multivariate analyses achieved significant separation between the two groups with an 11-metabolite prediction model at PREOP (AUC = 83.80%). Systems biology analysis using the metabolites with differential concentrations rendered "valine, leucine, and isoleucine biosynthesis" at PREOP and "citrate cycle" at POD2 as the most significantly enriched pathways (false discovery rate < 0.05). Perturbations in energy metabolism and amino acid synthesis pathways may be associated with postoperative delirium and suggest potential mechanisms for delirium pathogenesis. Our results could lead to the development of a metabolomic delirium predictor.

Machine Learning to Develop and Internally Validate a Predictive Model for Post-operative Delirium in a Prospective, Observational Clinical Cohort Study of Older Surgical Patients.

BACKGROUND: Our objective was to assess the performance of machine learning methods to predict post-operative delirium using a prospective clinical cohort. METHODS: We analyzed data from an observational cohort study of 560 older adults (≥ 70 years) without dementia undergoing major elective non-cardiac surgery. Post-operative delirium was determined by the Confusion Assessment Method supplemented by a medical chart review (N = 134, 24%). Five machine learning algorithms and a standard stepwise logistic regression model were developed in a training sample (80% of participants) and evaluated in the remaining hold-out testing sample. We evaluated three overlapping feature sets, restricted to variables that are readily available or minimally burdensome to collect in clinical settings, including interview and medical record data. A large feature set included 71 potential predictors. A smaller set of 18 features was selected by an expert panel using a consensus process, and this smaller feature set was considered with and without a measure of pre-operative mental status. RESULTS: The area under the receiver operating characteristic curve (AUC) was higher in the large feature set conditions (range of AUC, 0.62-0.71 across algorithms) versus the selected feature set conditions (AUC range, 0.53-0.57). The restricted feature set with mental status had intermediate AUC values (range, 0.53-0.68). In the full feature set condition, algorithms such as gradient boosting, cross-validated logistic regression, and neural network (AUC = 0.71, 95% CI 0.58-0.83) were comparable with a model developed using traditional stepwise logistic regression (AUC = 0.69, 95% CI 0.57-0.82). Calibration for all models and feature sets was poor. CONCLUSIONS: We developed machine learning prediction models for post-operative delirium that performed better than chance and are comparable with traditional stepwise logistic regression. Delirium proved to be a phenotype that was difficult to predict with appreciable accuracy.

Identification of Plasma Proteome Signatures Associated With Surgery Using SOMAscan.

OBJECTIVES: To characterize the proteomic signature of surgery in older adults and association with postoperative outcomes. SUMMARY OF BACKGROUND DATA: Circulating plasma proteins can reflect the physiological response to and clinical outcomes after surgery. METHODS: Blood plasma from older adults undergoing elective surgery was analyzed for 1305 proteins using SOMAscan. Surgery-associated proteins underwent Ingenuity Pathways Analysis. Selected surgery-associated proteins were independently validated using Luminex or enzyme-linked immunosorbent assay methods. Generalized linear models estimated correlations with postoperative outcomes. RESULTS: Plasma from a subcohort (n = 36) of the Successful Aging after Elective Surgery (SAGES) study was used for SOMAscan. Systems biology analysis of 110 proteins with Benjamini-Hochberg (BH) corrected P value ≤0.01 and an absolute foldchange (|FC|) ≥1.5 between postoperative day 2 (POD2) and preoperative (PREOP) identified functional pathways with major effects on pro-inflammatory proteins. Chitinase-3-like protein 1 (CHI3L1), C-reactive protein (CRP), and interleukin-6 (IL-6) were independently validated in separate validation cohorts from SAGES (n = 150 for CRP, IL-6; n = 126 for CHI3L1). Foldchange CHI3L1 and IL-6 were associated with increased postoperative complications [relative risk (RR) 1.50, 95% confidence interval (95% CI) 1.21-1.85 and RR 1.63, 95% CI 1.18-2.26, respectively], length of stay (RR 1.35, 95% CI 0.77-1.92 and RR 0.98, 95% CI 0.52-1.45), and risk of discharge to postacute facility (RR 1.15, 95% CI 1.04-1.26 and RR 1.11, 95% CI 1.04-1.18); POD2 and PREOP CRP difference was associated with discharge to postacute facility (RR 1.14, 95% CI 1.04-1.25). CONCLUSION: SOMAscan can identify novel and clinically relevant surgery-induced protein changes. Ultimately, proteomics may provide insights about pathways by which surgical stress contributes to postoperative outcomes.

Association of Plasma Neurofilament Light with Postoperative Delirium.

OBJECTIVE: To examine the association of the plasma neuroaxonal injury markers neurofilament light (NfL), total tau, glial fibrillary acid protein, and ubiquitin carboxyl-terminal hydrolase L1 with delirium, delirium severity, and cognitive performance. METHODS: Delirium case-no delirium control (n = 108) pairs were matched by age, sex, surgery type, cognition, and vascular comorbidities. Biomarkers were measured in plasma collected preoperatively (PREOP), and 2 days (POD2) and 30 days postoperatively (PO1MO) using Simoa technology (Quanterix, Lexington, MA). The Confusion Assessment Method (CAM) and CAM-S (Severity) were used to measure delirium and delirium severity, respectively. Cognitive function was measured with General Cognitive Performance (GCP) scores. RESULTS: Delirium cases had higher NfL on POD2 and PO1MO (median matched pair difference = 16.2pg/ml and 13.6pg/ml, respectively; p < 0.05). Patients with PREOP and POD2 NfL in the highest quartile (Q4) had increased risk for incident delirium (adjusted odds ratio [OR] = 3.7 [95% confidence interval (CI) = 1.1-12.6] and 4.6 [95% CI = 1.2-18.2], respectively) and experienced more severe delirium, with sum CAM-S scores 7.8 points (95% CI = 1.6-14.0) and 9.3 points higher (95% CI = 3.2-15.5). At PO1MO, delirium cases had continued high NfL (adjusted OR = 9.7, 95% CI = 2.3-41.4), and those with Q4 NfL values showed a -2.3 point decline in GCP score (-2.3 points, 95% CI = -4.7 to -0.9). INTERPRETATION: Patients with the highest PREOP or POD2 NfL levels were more likely to develop delirium. Elevated NfL at PO1MO was associated with delirium and greater cognitive decline. These findings suggest NfL may be useful as a predictive biomarker for delirium risk and long-term cognitive decline, and once confirmed would provide pathophysiological evidence for neuroaxonal injury following delirium. ANN NEUROL 2020;88:984-994.

The Role of Inflammation after Surgery for Elders (RISE) study: Examination of [11C]PBR28 binding and exploration of its link to post-operative delirium.

Major surgery is associated with a systemic inflammatory cascade that is thought, in some cases, to contribute to transient and/or sustained cognitive decline, possibly through neuroinflammatory mechanisms. However, the relationship between surgery, peripheral and central nervous system inflammation, and post-operative cognitive outcomes remains unclear in humans, primarily owing to limitations of in vivo biomarkers of neuroinflammation which vary in sensitivity, specificity, validity, and reliability. In the present study, [11C]PBR28 positron emission tomography, cerebrospinal fluid (CSF), and blood plasma biomarkers of inflammation were assessed pre-operatively and 1-month post-operatively in a cohort of patients (N = 36; 30 females; ≥70 years old) undergoing major orthopedic surgery under spinal anesthesia. Delirium incidence and severity were evaluated daily during hospitalization. Whole-brain voxel-wise and regions-of-interest analyses were performed to determine the magnitude and spatial extent of changes in [11C]PBR28 uptake following surgery. Results demonstrated that, compared with pre-operative baseline, [11C]PBR28 binding in the brain was globally downregulated at 1 month following major orthopedic surgery, possibly suggesting downregulation of the immune system of the brain. No significant relationship was identified between post-operative delirium and [11C]PBR28 binding, possibly due to a small number (n = 6) of delirium cases in the sample. Additionally, no significant relationships were identified between [11C]PBR28 binding and CSF/plasma biomarkers of inflammation. Collectively, these results contribute to the literature by demonstrating in a sizeable sample the effect of major surgery on neuroimmune activation and preliminary evidence identifying no apparent associations between [11C]PBR28 binding and fluid inflammatory markers or post-operative delirium.

The Role of Inflammation after Surgery for Elders (RISE) study: Study design, procedures, and cohort profile.

INTRODUCTION: The Role of Inflammation after Surgery for Elders study correlates novel inflammatory markers measured in blood, cerebrospinal fluid (CSF) assays, and [11C]-PBR28 positron-emission tomography imaging. METHODS: This study involved a prospective cohort design with patients who underwent elective hip and knee arthroplasty under spinal anesthesia. Sixty-five adults participated with their family members. Inflammatory biomarker assays were measured preoperatively on day 1 and postoperatively at one month. RESULTS: On average, participants were 75 years old, and 72% were female. 54% underwent total knee arthroplasty, and 46% underwent total hip arthroplasty. The mean Modified Mini-Mental State (3MS) Examination score was 89.3; four patients (6%) scored ≤77 points. Plasma assays were completed in 63 (97%) participants, cerebrospinal fluid assays in 61 (94%), and PET imaging in 44 (68%). DISCUSSION: This complex study presents an innovative effort to correlate peripheral and central inflammatory biomarkers before and after major surgery in older adults. Strengths include collecting concurrent blood, cerebrospinal fluid, and positron-emission tomography with detailed clinical characterization of delirium, cognition, and functional status.

Development of a Dynamic Multi-Protein Signature of Postoperative Delirium.

Background: Delirium is common, morbid, and costly, yet its biology is poorly understood. We aimed to develop a multi-protein signature of delirium by identifying proteins associated with delirium from unbiased proteomics and combining them with delirium biomarkers identified in our prior work (interleukin [IL]-6 and IL-2). Methods: We used the Successful Aging after Elective Surgery (SAGES) Study of adults age ≥70 undergoing major noncardiac surgery (N = 560; 24% delirium). Plasma was collected preoperatively (PREOP) and on postoperative day 2 (POD2). In a nested matched case-control study involving 12 pairs of delirium cases and no-delirium controls, isobaric tags for relative and absolute quantitation-based (iTRAQ) mass spectrometry proteomics was applied to identify the top set of delirium-related proteins. With these proteins, we then conducted enzyme-linked immunosorbent assay (ELISA) confirmation, and if confirmed, ELISA validation in 75 matched pairs. Multi-marker conditional logistic regression was used to select the "best" PREOP and POD2 models for delirium. Results: We identified three proteins from iTRAQ: C-reactive protein (CRP), zinc alpha-2 glycoprotein (AZGP1), and alpha-1 antichymotrypsin (SERPINA3). The "best" multi-protein models of delirium included: PREOP: CRP and AZGP1 (Bayesian information criteria [BIC]: 93.82, c-statistic: 0.77); and POD2: IL-6, IL-2, and CRP (BIC: 87.11, c-statistic: 0.84). Conclusion: The signature of postoperative delirium is dynamic, with some proteins important before surgery (risk markers) and others at the time of delirium (disease markers). Our dynamic, multi-protein signature for delirium improves our understanding of delirium pathophysiology and may identify patients at-risk of this devastating disorder that threatens independence of older adults.

The Association Between C-Reactive Protein and Postoperative Delirium Differs by Catechol-O-Methyltransferase Genotype.

OBJECTIVE: Catechol-O-methyltransferase (COMT), a key enzyme in degrading catecholamines associated with the stress response, may influence susceptibility to delirium. Individuals with the COMT (rs4680) Val/Val genotype (designated "warriors") withstand the onset of neuropsychiatric disorders and cognitive decline, whereas individuals with Met/Met and Val/Met genotypes ("nonwarriors") are more susceptible to these conditions. We evaluated whether COMT genotype modifies the established association between acute phase reactant (stress marker) C-reactive protein (CRP) and postoperative delirium. METHODS: This was a prospective cohort study conducted at two academic medical centers. The study involved 547 patients aged 70 or older undergoing major noncardiac surgery. We collected blood, extracted DNA, and performed COMT genotyping using allele-specific polymerase chain reaction assays, considering warriors versus nonwarriors. High plasma CRP, measured on postoperative day 2 using enzyme-linked immunosorbent assay, was defined by the highest sample-based quartile (≥234.12 mg/L). Delirium was determined using the Confusion Assessment Method, augmented by a validated chart review. We used generalized linear models adjusted for age, sex, surgery type, and race/ethnicity, stratified by COMT genotype, to determine whether the association between CRP and delirium differed by COMT. RESULTS: Prevalence of COMT warriors was 26%, and postoperative delirium occurred in 23%. Among COMT warriors, high CRP was not associated with delirium (relative risk [RR] 1.0, 95% confidence interval [CI] 0.4-2.6). In contrast, among nonwarriors, we found the expected relationship of high CRP and delirium (RR 1.5, 95% CI 1.1-2.2). CONCLUSION: COMT warriors may be protected against the increased risk of delirium associated with high CRP on postoperative day 2. With further confirmation, COMT genotype may help target interventions for delirium prevention in the vulnerable nonwarrior group.

Delirium Severity Post-Surgery and its Relationship with Long-Term Cognitive Decline in a Cohort of Patients without Dementia.

BACKGROUND: Delirium has been associated with more rapid cognitive decline. However, it is unknown whether increased delirium severity is associated with a higher rate of long-term cognitive decline. OBJECTIVE: To evaluate delirium severity and the presence and rate of cognitive decline over 36 months following surgery. METHODS: We examined patients from the Successful Aging after Elective Surgery Study, who were age ≥70 years undergoing major elective surgery (N = 560). Delirium severity was determined by the peak Confusion Assessment Method-Severity (CAM-S) score for each patient's hospitalization and grouped based on the sample distribution: scores of 0-2, 3-7, and 8-19. A neuropsychological composite, General Cognitive Performance (GCP), and proxy-reported Informant Questionnaire for Cognitive Decline (IQCODE) were used to examine cognitive outcomes following surgery at 0, 1, and 2 months, and then every 6 months for up to 3 years. RESULTS: No significant cognitive decline was observed for patients with peak CAM-S scores 0-2 (-0.17 GCP units/year, 95% confidence interval [CI] -0.35, 0.01). GCP scores decreased significantly in the group with peak CAM-S scores 3-7 (-0.30 GCP units/year, 95% CI -0.51, -0.09), and decreased almost three times faster in the highest delirium severity group (peak CAM-S scores 8-19; -0.82 GCP units/year, 95% CI -1.28, -0.37). A similar association was found for delirium severity and the proportion of patients who developed IQCODE impairment over time. CONCLUSION: Patients with the highest delirium severity experienced the greatest rate of cognitive decline, which exceeds the rate previously observed for patients with dementia, on serial neuropsychological testing administered over 3 years, with a dose-response relationship between delirium severity and long-term cognitive decline.

Alzheimer's-related cortical atrophy is associated with postoperative delirium severity in persons without dementia.

Patients with dementia due to Alzheimer's disease (AD) have increased risk of developing delirium. This study investigated the relationship between a magnetic resonance imaging (MRI)-derived biomarker associated with preclinical AD and postoperative delirium. Participants were older adults (≥70 years) without dementia who underwent preoperative MRI and elective surgery. Delirium incidence and severity were evaluated daily during hospitalization. Cortical thickness was averaged across a published set of a priori brain regions to derive a measure known as the "AD signature." Logistic and linear regression was used, respectively, to test whether the AD signature was associated with delirium incidence in the entire sample (N = 145) or with the severity of delirium among those who developed delirium (N = 32). Thinner cortex in the AD signature did not predict incidence of delirium (odds ratio = 1.15, p = 0.38) but was associated with greater delirium severity among those who developed delirium (b = -1.2, p = 0.014). These results suggest that thinner cortices, perhaps reflecting underlying neurodegeneration due to preclinical AD, may serve as a vulnerability factor that increases severity once delirium occurs.

Methodologic considerations in the design and analysis of nested case-control studies: association between cytokines and postoperative delirium.

BACKGROUND: The nested case-control study (NCC) design within a prospective cohort study is used when outcome data are available for all subjects, but the exposure of interest has not been collected, and is difficult or prohibitively expensive to obtain for all subjects. A NCC analysis with good matching procedures yields estimates that are as efficient and unbiased as estimates from the full cohort study. We present methodological considerations in a matched NCC design and analysis, which include the choice of match algorithms, analysis methods to evaluate the association of exposures of interest with outcomes, and consideration of overmatching. METHODS: Matched, NCC design within a longitudinal observational prospective cohort study in the setting of two academic hospitals. Study participants are patients aged over 70 years who underwent scheduled major non-cardiac surgery. The primary outcome was postoperative delirium from in-hospital interviews and medical record review. The main exposure was IL-6 concentration (pg/ml) from blood sampled at three time points before delirium occurred. We used nonparametric signed ranked test to test for the median of the paired differences. We used conditional logistic regression to model the risk of IL-6 on delirium incidence. Simulation was used to generate a sample of cohort data on which unconditional multivariable logistic regression was used, and the results were compared to those of the conditional logistic regression. Partial R-square was used to assess the level of overmatching. RESULTS: We found that the optimal match algorithm yielded more matched pairs than the greedy algorithm. The choice of analytic strategy-whether to consider measured cytokine levels as the predictor or outcome-- yielded inferences that have different clinical interpretations but similar levels of statistical significance. Estimation results from NCC design using conditional logistic regression, and from simulated cohort design using unconditional logistic regression, were similar. We found minimal evidence for overmatching. CONCLUSIONS: Using a matched NCC approach introduces methodological challenges into the study design and data analysis. Nonetheless, with careful selection of the match algorithm, match factors, and analysis methods, this design is cost effective and, for our study, yields estimates that are similar to those from a prospective cohort study design.

High C-Reactive Protein Predicts Delirium Incidence, Duration, and Feature Severity After Major Noncardiac Surgery.

OBJECTIVES: To examine associations between the inflammatory marker C-reactive protein (CRP) measured preoperatively and on postoperative day 2 (POD2) and delirium incidence, duration, and feature severity. DESIGN: Prospective cohort study. SETTING: Two academic medical centers. PARTICIPANTS: Adults aged 70 and older undergoing major noncardiac surgery (N = 560). MEASUREMENTS: Plasma CRP was measured using enzyme-linked immunosorbent assay. Delirium was assessed from Confusion Assessment Method (CAM) interviews and chart review. Delirium duration was measured according to number of hospital days with delirium. Delirium feature severity was defined as the sum of CAM-Severity (CAM-S) scores on all postoperative hospital days. Generalized linear models were used to examine independent associations between CRP (preoperatively and POD2 separately) and delirium incidence, duration, and feature severity; prolonged hospital length of stay (LOS, >5 days); and discharge disposition. RESULTS: Postoperative delirium occurred in 24% of participants, 12% had 2 or more delirium days, and the mean ± standard deviation sum CAM-S was 9.3 ± 11.4. After adjusting for age, sex, surgery type, anesthesia route, medical comorbidities, and postoperative infectious complications, participants with preoperative CRP of 3 mg/L or greater had a risk of delirium that was 1.5 times as great (95% confidence interval (CI) = 1.1-2.1) as that of those with CRP less than 3 mg/L, 0.4 more delirium days (P < .001), more-severe delirium (3.6 CAM-S points higher, P < .001), and a risk of prolonged LOS that was 1.4 times as great (95% CI = 1.1-1.8). Using POD2 CRP, participants in the highest quartile (≥235.73 mg/L) were 1.5 times as likely to develop delirium (95% CI = 1.0-2.4) as those in the lowest quartile (≤127.53 mg/L), had 0.2 more delirium days (P < .05), and had more severe delirium (4.5 CAM-S points higher, P < .001). CONCLUSION: High preoperative and POD2 CRP were independently associated with delirium incidence, duration, and feature severity. CRP may be useful to identify individuals who are at risk of developing delirium.

Higher C-Reactive Protein Levels Predict Postoperative Delirium in Older Patients Undergoing Major Elective Surgery: A Longitudinal Nested Case-Control Study.

BACKGROUND: Delirium is a common, morbid, and costly postoperative complication. We aimed to identify blood-based postoperative delirium markers in a nested case-control study of older surgical patients using a proteomics approach followed by enzyme-linked immunosorbent assay (ELISA) validation. METHODS: The Successful Aging after Elective Surgery study enrolled dementia-free adults ≥70 years old undergoing major scheduled noncardiac surgery (N = 566; 24% delirium). Plasma was collected at four time points: preoperative, postanesthesia care unit, postoperative day 2, and 1 month postoperative. Matched pairs were selected for the independent discovery (39 pairs) and replication cohorts (36 pairs), which were subsequently combined into the pooled cohort (75 pairs). Isobaric tags for relative and absolute quantitation-based relative quantitation mass spectrometry proteomics were performed to identify the strongest delirium-related protein, which was selected for ELISA validation. Using the ELISA results, statistical analyses using nonparametric signed rank tests were performed in all cohorts examining the association between the identified protein and delirium. RESULTS: C-reactive protein emerged from the proteomics analysis as the strongest delirium-related protein. Validation by ELISA confirmed that compared with controls, cases had significantly higher C-reactive protein levels in the discovery, replication, and pooled cohorts at the preoperative (median paired difference [MPD] 1.97 mg/L [p < .05], 0.29 mg/L, 1.56 mg/L [p < .01]), postanesthesia care unit (MPD 2.83 mg/L, 2.22 mg/L [p < .05], 2.53 mg/L [p < .01]) and postoperative day 2 (MPD 71.97 mg/L [p < .01], 35.18 mg/L [p < .05], 63.76 mg/L [p < .01]) time points, but not 1 month postoperative (MPD 2.72 mg/L, -0.66 mg/L, 1.10 mg/L). CONCLUSIONS: Elevated preoperative and postoperative plasma levels of C-reactive protein were associated with delirium, suggesting that a preinflammatory state and heightened inflammatory response to surgery are potential pathophysiologic mechanisms of delirium.