Relationship between cortical brain atrophy, delirium, and long-term cognitive decline in older surgical patients.

In older patients, delirium after surgery is associated with long-term cognitive decline (LTCD). The neural substrates of this association are unclear. Neurodegenerative changes associated with dementia are possible contributors. We investigated the relationship between brain atrophy rates in Alzheimer's disease (AD) and cognitive aging signature regions from magnetic resonance imaging before and one year after surgery, LTCD assessed by the general cognitive performance (GCP) score over 6 years post-operatively, and delirium in 117 elective surgery patients without dementia (mean age = 76). The annual change in cortical thickness was 0.2(1.7) % (AD-signature p = 0.09) and 0.4(1.7) % (aging-signature p = 0.01). Greater atrophy was associated with LTCD (AD-signature: beta(CI) = 0.24(0.06-0.42) points of GCP/mm of cortical thickness; p < 0.01, aging-signature: beta(CI) = 0.55(0.07-1.03); p = 0.03). Atrophy rates were not significantly different between participants with and without delirium. We found an interaction with delirium severity in the association between atrophy and LTCD (AD-signature: beta(CI) = 0.04(0.00-0.08), p = 0.04; aging-signature: beta(CI) = 0.08(0.03-0.12), p < 0.01). The rate of cortical atrophy and severity of delirium are independent, synergistic factors determining postoperative cognitive decline in the elderly.

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.

Social determinants of health and incident postoperative delirium: Exploring key relationships in the SAGES study.

BACKGROUND: Examining the associations of social determinants of health (SDOH) with postoperative delirium in older adults will broaden our understanding of this potentially devastating condition. We explored the association between SDOH factors and incident postoperative delirium. METHODS: A retrospective study of a prospective cohort of patients enrolled from June 18, 2010, to August 8, 2013, across two academic medical centers in Boston, Massachusetts. Overall, 560 older adults age ≥70 years undergoing major elective non-cardiac surgery were included in this analysis. Exposure variables included income, lack of private insurance, and neighborhood disadvantage. Our main outcome was incident postoperative delirium, measured using the Confusion Assessment Method long form. RESULTS: Older age (odds ratio, OR: 1.01, 95% confidence interval, CI: 1.00, 1.02), income <20,000 a year (OR: 1.12, 95% CI: 1.00, 1.26), lack of private insurance (OR: 1.19, 95% CI: 1.04, 1.38), higher depressive symptomatology (OR: 1.02, 95% CI: 1.01, 1.04), and the Area Deprivation Index (OR: 1.02, 95% CI: 1.01, 1.04) were significantly associated with increased risk of postoperative delirium in bivariable analyses. In a multivariable model, explaining 27% of the variance in postoperative delirium, significant independent variables were older age (OR 1.01, 95% CI 1.00, 1.02), lack of private insurance (OR 1.18, 95% CI 1.02, 1.36), and depressive symptoms (OR 1.02, 95% CI 1.00, 1.03). Household income was no longer a significant independent predictor of delirium in the multivariable model (OR:1.02, 95% CI: 0.90, 1.15). The type of medical insurance significantly mediated the association between household income and incident delirium. CONCLUSIONS: Lack of private insurance, a social determinant of health reflecting socioeconomic status, emerged as a novel and important independent risk factor for delirium. Future efforts should consider targeting SDOH factors to prevent postoperative delirium in older adults.

Successful aging after elective surgery II: Study cohort description.

BACKGROUND: The Successful Aging after Elective Surgery (SAGES) II Study was designed to examine the relationship between delirium and Alzheimer's disease and related dementias (AD/ADRD), by capturing novel fluid biomarkers, neuroimaging markers, and neurophysiological measurements. The goal of this paper is to provide the first complete description of the enrolled cohort, which details the baseline characteristics and data completion. We also describe the study modifications necessitated by the COVID-19 pandemic, and lay the foundation for future work using this cohort. METHODS: SAGES II is a prospective observational cohort study of community-dwelling adults age 65 and older undergoing major non-cardiac surgery. Participants were assessed preoperatively, throughout hospitalization, and at 1, 2, 6, 12, and 18 months following discharge to assess cognitive and physical functioning. Since participants were enrolled throughout the COVID-19 pandemic, procedural modifications were designed to reduce missing data and allow for high data quality. RESULTS: About 420 participants were enrolled with a mean (standard deviation) age of 73.4 (5.6) years, including 14% minority participants. Eighty-eight percent of participants had either total knee or hip replacements; the most common surgery was total knee replacement with 210 participants (50%). Despite the challenges posed by the COVID-19 pandemic, which required the use of novel procedures such as video assessments, there were minimal missing interviews during hospitalization and up to 1-month follow-up; nearly 90% of enrolled participants completed interviews through 6-month follow-up. CONCLUSION: While there are many longitudinal studies of older adults, this study is unique in measuring health outcomes following surgery, along with risk factors for delirium through the application of novel biomarkers-including fluid (plasma and cerebrospinal fluid), imaging, and electrophysiological markers. This paper is the first to describe the characteristics of this unique cohort and the data collected, enabling future work using this novel and important resource.

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.

Six-Year Cognitive Trajectory in Older Adults Following Major Surgery and Delirium.

Importance: The study results suggest that delirium is the most common postoperative complication in older adults and is associated with poor outcomes, including long-term cognitive decline and incident dementia. Objective: To examine the patterns and pace of cognitive decline up to 72 months (6 years) in a cohort of older adults following delirium. Design, Setting, and Participants: This was a prospective, observational cohort study with long-term follow-up including 560 community-dwelling older adults (older than 70 years) in the ongoing Successful Aging after Elective Surgery study that began in 2010. The data were analyzed from 2021 to 2022. Exposure: Development of incident delirium following major elective surgery. Main Outcomes and Measures: Delirium was assessed daily during hospitalization using the Confusion Assessment Method, which was supplemented with medical record review. Cognitive performance using a comprehensive battery of neuropsychological tests was assessed preoperatively and across multiple points postoperatively to 72 months of follow-up. We evaluated longitudinal cognitive change using a composite measure of neuropsychological performance called the general cognitive performance (GCP), which is scaled so that 10 points on the GCP is equivalent to 1 population SD. Retest effects were adjusted using cognitive test results in a nonsurgical comparison group. Results: The 560 participants (326 women [58%]; mean [SD] age, 76.7 [5.2] years) provided a total of 2637 person-years of follow-up. One hundred thirty-four participants (24%) developed postoperative delirium. Cognitive change following surgery was complex: we found evidence for differences in acute, post-short-term, intermediate, and longer-term change from the time of surgery that were associated with the development of postoperative delirium. Long-term cognitive change, which was adjusted for practice and recovery effects, occurred at a pace of about -1.0 GCP units (95% CI, -1.1 to -0.9) per year (about 0.10 population SD units per year). Participants with delirium showed significantly faster long-term cognitive change with an additional -0.4 GCP units (95% CI, -0.1 to -0.7) or -1.4 units per year (about 0.14 population SD units per year). Conclusions and Relevance: This cohort study found that delirium was associated with a 40% acceleration in the slope of cognitive decline out to 72 months following elective surgery. Because this is an observational study, we cannot be sure whether delirium directly causes subsequent cognitive decline, or whether patients with preclinical brain disease are more likely to develop delirium. Future research is needed to understand the causal pathway between delirium and cognitive decline.

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.

Successful aging after elective surgery II: Study design and methods.

BACKGROUND: The Successful Aging after Elective Surgery (SAGES) II study was designed to increase knowledge of the pathophysiology and linkages between delirium and dementia. We examine novel biomarkers potentially associated with delirium, including inflammation, Alzheimer's disease (AD) pathology and neurodegeneration, neuroimaging markers, and neurophysiologic markers. The goal of this paper is to describe the study design and methods for the SAGES II study. METHODS: The SAGES II study is a 5-year prospective observational study of 400-420 community dwelling persons, aged 65 years and older, assessed prior to scheduled surgery and followed daily throughout hospitalization to observe for development of delirium and other clinical outcomes. Delirium is measured with the Confusion Assessment Method (CAM), long form, after cognitive testing. Cognitive function is measured with a detailed neuropsychologic test battery, summarized as a weighted composite, the General Cognitive Performance (GCP) score. Other key measures include magnetic resonance imaging (MRI), transcranial magnetic stimulation (TMS)/electroencephalography (EEG), and Amyloid positron emission tomography (PET) imaging. We describe the eligibility criteria, enrollment flow, timing of assessments, and variables collected at baseline and during repeated assessments at 1, 2, 6, 12, and 18 months. RESULTS: This study describes the hospital and surgery-related variables, delirium, long-term cognitive decline, clinical outcomes, and novel biomarkers. In inter-rater reliability assessments, the CAM ratings (weighted kappa = 0.91, 95% confidence interval, CI = 0.74-1.0) in 50 paired assessments and GCP ratings (weighted kappa = 0.99, 95% CI 0.94-1.0) in 25 paired assessments. We describe procedures for data quality assurance and Covid-19 adaptations. CONCLUSIONS: This complex study presents an innovative effort to advance our understanding of the inter-relationship between delirium and dementia via novel biomarkers, collected in the context of major surgery in older adults. Strengths include the integration of MRI, TMS/EEG, PET modalities, and high-quality longitudinal data.

Neurophysiologic predictors of individual risk for post-operative delirium after elective surgery.

BACKGROUND: Post-surgical delirium is associated with increased morbidity, lasting cognitive decline, and loss of functional independence. Within a conceptual framework that delirium is triggered by stressors when vulnerabilities exist in cerebral connectivity and plasticity, we previously suggested that neurophysiologic measures might identify individuals at risk for post-surgical delirium. Here we demonstrate the feasibility of the approach and provide preliminary experimental evidence of the predictive value of such neurophysiologic measures for the risk of delirium in older persons undergoing elective surgery. METHODS: Electroencephalography (EEG) and transcranial magnetic stimulation (TMS) were collected from 23 patients prior to elective surgery. Resting-state EEG spectral power ratio (SPR) served as a measure of integrity of neural circuits. TMS-EEG metrics of plasticity (TMS-plasticity) were used as indicators of brain capacity to respond to stressors. Presence or absence of delirium was assessed using the confusion assessment method (CAM). We included individuals with no baseline clinically relevant cognitive impairment (MoCA scores ≥21) in order to focus on subclinical neurophysiological measures. RESULTS: In patients with no baseline cognitive impairment (N = 20, age = 72 ± 6), 3 developed post-surgical delirium (MoCA = 24 ± 2.6) and 17 did not (controls; MoCA = 25 ± 2.4). Patients who developed delirium had pre-surgical resting-state EEG power ratios outside the 95% confidence interval of controls, and 2/3 had TMS-plasticity measures outside the 95% CI of controls. CONCLUSIONS: Consistent with our proposed conceptual framework, this pilot study suggests that non-invasive and scalable neurophysiologic measures can identify individuals at risk of post-operative delirium. Specifically, abnormalities in resting-state EEG spectral power or TMS-plasticity may indicate sub-clinical risk for post-surgery delirium. Extension and confirmation of these findings in a larger sample is needed to assess the clinical utility of the proposed neurophysiologic markers, and to identify specific connectivity and plasticity targets for therapeutic interventions that might minimize the risk of delirium.

Parental Education and Delirium Risk after Surgery in Older Adults.

OBJECTIVES: Efforts to conceptualize risk factors for postoperative delirium in older adults have focused on the time proximate to the episode, but how early-life exposures influence delirium risk is poorly understood. METHODS: An observational cohort of 547 patients aged 70+undergoing major non-cardiac surgery at two academic medical centers in Boston. Demographic characteristics, cognition, parental education, health, and participation in cognitively stimulating activities were assessed prior to surgery. Delirium incidence and severity were measured daily during hospitalization. RESULTS: Higher paternal education was associated with significantly lower incidence of delirium (X2(1, N =547)=8.35, p <.001; odds ratio OR=.93, 95% CI, .87 to .98) and inversely associated with delirium severity (r(545)=-.13, p <.001). Higher maternal education was associated with lower delirium incidence but did not reach statistical significance. The effect of paternal education on delirium incidence was independent of the patient's education, estimated premorbid intelligence, medical comorbidities, neighborhood disadvantage, and participation in cognitively stimulating activities (X2(2, N =547)=31.22, p <.001). CONCLUSIONS: Examining early-life exposures may yield unique insights into the risks and pathogenesis of delirium. CLINICAL IMPLICATIONS: Evaluating long-term factors that increase vulnerability to delirium may improve our ability to calculate risk. It may guide clinical decision-making and inform pre- and post-operative recommendations.

Structural integrity of the anterior mid-cingulate cortex contributes to resilience to delirium in SuperAging.

Despite its devastating clinical and societal impact, approaches to treat delirium in older adults remain elusive, making it important to identify factors that may confer resilience to this syndrome. Here, we investigated a cohort of 93 cognitively normal older patients undergoing elective surgery recruited as part of the Successful Aging after Elective Surgery study. Each participant was classified either as a SuperAger (n = 19) or typically aging older adult (n = 74) based on neuropsychological criteria, where the former was defined as those older adults whose memory function rivals that of young adults. We compared these subgroups to examine the role of preoperative memory function in the incidence and severity of postoperative delirium. We additionally investigated the association between indices of postoperative delirium symptoms and cortical thickness in functional networks implicated in SuperAging based on structural magnetic resonance imaging data that were collected preoperatively. We found that SuperAging confers the real-world benefit of resilience to delirium, as shown by lower (i.e. zero) incidence of postoperative delirium and decreased severity scores compared with typical older adults. Furthermore, greater baseline cortical thickness of the anterior mid-cingulate cortex-a key node of the brain's salience network that is also consistently implicated in SuperAging-predicted lower postoperative delirium severity scores in all patients. Taken together, these findings suggest that baseline memory function in older adults may be a useful predictor of postoperative delirium risk and severity and that superior memory function may contribute to resilience to delirium. In particular, the integrity of the anterior mid-cingulate cortex may be a potential biomarker of resilience to delirium, pointing to this region as a potential target for preventive or therapeutic interventions designed to mitigate the risk or consequences of developing this prevalent clinical syndrome.

Identifying Delirium in Persons With Moderate or Severe Dementia: Review of Challenges and an Illustrative Approach.

Delirium and dementia are common causes of cognitive impairment among older adults, which often coexist. Delirium is associated with poor clinical outcomes, and is more frequent and more severe in patients with dementia. Identifying delirium in the presence of dementia, also described as delirium superimposed on dementia (DSD), is particularly challenging, as symptoms of delirium such as inattention, cognitive dysfunction, and altered level of consciousness, are also features of dementia. Because DSD is associated with poorer clinical outcomes than dementia alone, detecting delirium is important for reducing morbidity and mortality in this population. We review a number of delirium screening instruments that have shown promise for use in DSD, including the 4-DSD, combined Six Item Cognitive Impairment Test (6-CIT) and 4 'A's Test (4AT), Confusion Assessment Method (CAM), and the combined UB2 and 3D-CAM (UB-CAM). Each has advantages and disadvantages. We then describe the operationalization of a CAM-based approach in a current ECT in dementia project as an example of modifying an existing instrument for patients with moderate to severe dementia. Ultimately, any instrument modified will need to be validated against a standard clinical reference, in order to fully establish its sensitivity and specificity in the moderate to severe dementia population. Future work is greatly needed to advance the challenging area of accurate identification of delirium in moderate or severe dementia.

Assessment of potential selection bias in neuroimaging studies of postoperative delirium and cognitive decline: lessons from the SAGES study.

Due to cost and participant burden, neuroimaging studies are often performed in relatively small samples of voluntary participants. This may lead to selection bias. It is important to identify factors associated with participation in neuroimaging studies and understand their effect on outcome measures. We investigated the effect of postoperative delirium on long-term (over 48 months) cognitive decline (LTCD) in 560 older surgical patients (≥ 70 years), including a nested MRI cohort (n = 146). We observed a discrepancy in the effect of delirium on cognitive decline as a function of MRI participation. Although overall difference in cognitive decline due to delirium was not greater than what might be expected due to chance (p = .21), in the non-MRI group delirium was associated with a faster pace of LTCD (-0.063, 95% CI -0.094 to -0.032, p < .001); while in the MRI group the effect of delirium was less and not significant (-0.023, 95% CI -0.076, 0.030, p = .39). Since this limits our ability to investigate the neural correlates of delirium and cognitive decline using MRI data, we attempted to mitigate the observed discrepancy using inverse probability weighting for MRI participation. The approach was not successful and the difference of the effect of delirium in slope was essentially unchanged. There was no evidence that the MRI sub-group experienced delirium that differed in severity relative to MRI non-participants. We could not attribute the observed discrepancy to selection bias based on measured factors. It may reflect a power issue due to the smaller MRI subsample or selection bias from unmeasured factors.

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.

One-Year Medicare Costs Associated With Delirium in Older Patients Undergoing Major Elective Surgery.

Importance: Delirium is a common, serious, and potentially preventable problem for older adults, associated with adverse outcomes. Coupled with its preventable nature, these adverse sequelae make delirium a significant public health concern; understanding its economic costs is important for policy makers and health care leaders to prioritize care. Objective: To evaluate current 1-year health care costs attributable to postoperative delirium in older patients undergoing elective surgery. Design, Setting, and Participants: This prospective cohort study included 497 patients from the Successful Aging after Elective Surgery (SAGES) study, an ongoing cohort study of older adults undergoing major elective surgery. Patients were enrolled from June 18, 2010, to August 8, 2013. Eligible patients were 70 years or older, English-speaking, able to communicate verbally, and scheduled to undergo major surgery at 1 of 2 Harvard-affiliated hospitals with an anticipated length of stay of at least 3 days. Eligible surgical procedures included total hip or knee replacement; lumbar, cervical, or sacral laminectomy; lower extremity arterial bypass surgery; open abdominal aortic aneurysm repair; and open or laparoscopic colectomy. Data were analyzed from October 15, 2019, to September 15, 2020. Exposures: Major elective surgery and hospitalization. Main Outcomes and Measures: Cumulative and period-specific costs (index hospitalization, 30-day, 90-day, and 1-year follow-up) were examined using Medicare claims and extensive clinical data. Total inflation-adjusted health care costs were determined using data from Medicare administrative claims files for the 2010 to 2014 period. Delirium was rated using the Confusion Assessment Method. We also examined whether increasing delirium severity was associated with higher cumulative and period-specific costs. Delirium severity was measured with the Confusion Assessment Method-Severity long form. Regression models were used to determine costs associated with delirium after adjusting for patient demographic and clinical characteristics. Results: Of the 566 patients who were eligible for the study, a total of 497 patients (mean [SD] age, 76.8 [5.1] years; 281 women [57%]; 461 White participants [93%]) were enrolled after exclusion criteria were applied. During the index hospitalization, 122 patients (25%) developed postoperative delirium, whereas 375 (75%) did not. Patients with delirium had significantly higher unadjusted health care costs than patients without delirium (mean [SD] cost, $146 358 [$140 469] vs $94 609 [$80 648]). After adjusting for relevant confounders, the cumulative health care costs attributable to delirium were $44 291 (95% CI, $34 554-$56 673) per patient per year, with the majority of costs coming from the first 90 days: index hospitalization ($20 327), subsequent rehospitalizations ($27 797), and postacute rehabilitation stays ($2803). Health care costs increased directly and significantly with level of delirium severity (none-mild, $83 534; moderate, $99 756; severe, $140 008), suggesting an exposure-response relationship. The adjusted mean cumulative costs attributable to severe delirium were $56 474 (95% CI, $40 927-$77 440) per patient per year. Extrapolating nationally, the health care costs attributable to postoperative delirium were estimated at $32.9 billion (95% CI, $25.7 billion-$42.2 billion) per year. Conclusions and Relevance: These findings suggest that the economic outcomes of delirium and severe delirium after elective surgery are substantial, rivaling costs associated with cardiovascular disease and diabetes. These results highlight the need for policy imperatives to address delirium as a large-scale public health issue.

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.

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.

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.