Association of CSF Alzheimer's disease biomarkers with postoperative delirium in older adults

Potential value of serum prealbumin and serum albumin in the identification of postoperative delirium in patients undergoing knee/hip replacement: an observational study and internal validation study

Background

Postoperative delirium (POD) is a common postoperative neurological complication that can lead to a variety of postoperative complications. At present, the pathogenesis of POD is unclear. This study aims to explore the relationship between serum prealbumin and serum albumin and POD and whether serum prealbumin and serum albumin influence POD through POD core pathology.

Objective

We enrolled 500 Chinese Han patients between September 2020 to January 2023. We analyzed the risk and protective factors of POD using the multivariate logistic regression. We also assessed the predictive power of serum prealbumin, serum albumin, and both in combination with CSF POD biomarkers. We used Stata MP16.0. to examine whether the association between serum prealbumin and serum albumin and POD was mediated by CSF POD biomarkers, and conducted an internal validation study to verify the accuracy of the combination of serum prealbumin + serum albumin + CSF POD biomarkers for predicting POD. The model was visualized using ROC curve and decision curve analysis (DCA). DynNom and Shiny packages were used to create an online calculator. Ten patients who had POD occurring from February 2023 to October 2023 were selected for internal verification.

Results

Finally, a total of 364 patients were included in our study. Levels of serum prealbumin, serum albumin in the POD group were lower than those in the NPOD group. The lever of serum prealbumin, serum albumin were protective factors for POD. The relationship between serum prealbumin, serum albumin and POD was partially mediated by T-tau (12.28%) and P-tau (20.61%). The model combining serum prealbumin and serum albumin and POD biomarkers exhibited a relatively better discriminatory ability to predict POD. DCA also showed that the combination of serum prealbumin and serum albumin and POD biomarkers brought high predictive benefits to patients. The dynamic online calculator can accurately predict the occurrence of POD in the internal validation study.

Conclusion

Preoperative low serum prealbumin and serum albumin levels were the preoperative risk factors for POD, which is partly mediated by T-tau and P-tau. The model combining serum prealbumin and serum albumin and CSF POD biomarkers can accurately predict the occurrence of POD.

Clinical trial registration

http://www.clinicaltrials.gov, identifier ChiCTR2000033439.

Associations between Alzheimer's disease biomarkers and postoperative delirium or cognitive dysfunction: A meta-analysis and trial sequential analysis of prospective clinical trials

BACKGROUND

The relationship between Alzheimer's disease biomarkers and postoperative complications, such as postoperative delirium (POD) and postoperative cognitive dysfunction (POCD), remains a subject of ongoing debate.

OBJECTIVE

This meta-analysis aimed to determine whether there is an association between perioperative Alzheimer's disease biomarkers and postoperative complications.

DESIGN

We conducted a meta-analysis of observational clinical studies that explored the correlation between Alzheimer's disease biomarkers and POD or POCD in patients who have undergone surgery, following PRISMA guidelines. The protocol was previously published (INPLASY: INPLASY202350001).

DATA SOURCES

A comprehensive search was conducted across PubMed, Embase, Web of Science, and Cochrane databases until March 2023.

ELIGIBILITY CRITERIA

Surgical patients aged at least 18 years, studies focusing on POD or POCD, research involving Alzheimer's disease biomarkers, including Aβ or tau in blood or cerebrospinal fluid (CSF), and availability of the full text.

RESULTS

Our meta-analysis included 15 studies: six focusing on POD and nine on POCD. The findings revealed a negative correlation between preoperative CSF β-amyloid 42 (Aβ42) levels and the onset of POD [mean difference -86.1, 95% confidence interval (CI), -114.15 to -58.05, I2 : 47%]; this association was strongly supported by trial sequential analysis (TSA). A similar negative correlation was discerned between preoperative CSF Aβ42 levels and the incidence of POCD (-165.01, 95% CI, -261.48 to -68.53, I2 : 95%). The TSA also provided robust evidence for this finding; however, the evidence remains insufficient to confirm a relationship between other Alzheimer's disease biomarkers [β-amyloid 40 (Aβ40), total tau (T-tau), phosphorylated tau (P-tau), and Aβ42/T-tau ratio] and POD or POCD.

CONCLUSION

The study results indicate a negative correlation between preoperative CSF Aβ42 levels and the occurrence of both POD and POCD. Future investigations are warranted to identify the predictive cutoff value of preoperative CSF Aβ42 for POD and POCD.

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 (Aβ)42 , Aβ40 , 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, Aβ40 and Aβ42 .

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.

A Real-Time Neurophysiologic Stress Test for the Aging Brain: Novel Perioperative and ICU Applications of EEG in Older Surgical Patients

As of 2022, individuals age 65 and older represent approximately 10% of the global population [1], and older adults make up more than one third of anesthesia and surgical cases in developed countries [2, 3]. With approximately > 234 million major surgical procedures performed annually worldwide [4], this suggests that > 70 million surgeries are performed on older adults across the globe each year. The most common postoperative complications seen in these older surgical patients are perioperative neurocognitive disorders including postoperative delirium, which are associated with an increased risk for mortality [5], greater economic burden [6, 7], and greater risk for developing long-term cognitive decline [8] such as Alzheimer's disease and/or related dementias (ADRD). Thus, anesthesia, surgery, and postoperative hospitalization have been viewed as a biological "stress test" for the aging brain, in which postoperative delirium indicates a failed stress test and consequent risk for later cognitive decline (see Fig. 3). Further, it has been hypothesized that interventions that prevent postoperative delirium might reduce the risk of long-term cognitive decline. Recent advances suggest that rather than waiting for the development of postoperative delirium to indicate whether a patient "passed" or "failed" this stress test, the status of the brain can be monitored in real-time via electroencephalography (EEG) in the perioperative period. Beyond the traditional intraoperative use of EEG monitoring for anesthetic titration, perioperative EEG may be a viable tool for identifying waveforms indicative of reduced brain integrity and potential risk for postoperative delirium and long-term cognitive decline. In principle, research incorporating routine perioperative EEG monitoring may provide insight into neuronal patterns of dysfunction associated with risk of postoperative delirium, long-term cognitive decline, or even specific types of aging-related neurodegenerative disease pathology. This research would accelerate our understanding of which waveforms or neuronal patterns necessitate diagnostic workup and intervention in the perioperative period, which could potentially reduce postoperative delirium and/or dementia risk. Thus, here we present recommendations for the use of perioperative EEG as a "predictor" of delirium and perioperative cognitive decline in older surgical patients.

Preclinical and translational models for delirium: Recommendations for future research from the NIDUS delirium network

Delirium is a common, morbid, and costly syndrome that is closely linked to Alzheimer's disease (AD) and AD-related dementias (ADRD) as a risk factor and outcome. Human studies of delirium have advanced our knowledge of delirium incidence and prevalence, risk factors, biomarkers, outcomes, prevention, and management. However, understanding of delirium neurobiology remains limited. Preclinical and translational models for delirium, while challenging to develop, could advance our knowledge of delirium neurobiology and inform the development of new prevention and treatment approaches. We discuss the use of preclinical and translational animal models in delirium, focusing on (1) a review of current animal models, (2) challenges and strategies for replicating elements of human delirium in animals, and (3) the utility of biofluid, neurophysiology, and neuroimaging translational markers in animals. We conclude with recommendations for the development and validation of preclinical and translational models for delirium, with the goal of advancing awareness in this important field.

A Review of Biomarkers in Delirium Superimposed on Dementia (DSD) and Their Clinical Application to Personalized Treatment and Management

Delirium superimposed on dementia (DSD) occurs when patients with pre-existing dementia develop delirium. This complication causes patients to become impaired, posing safety concerns for both hospital staff and patients. Furthermore, there is an increased risk of worsening functional disability and death. Despite medical advances, DSD provides both diagnostic and therapeutic challenges to providers. Identifying at-risk patients and providing personalized medicine and patient care can decrease disease burden in a time-efficient manner. This review delves into bioinformatics-based studies of DSD in order to design and implement a personalized medicine-based approach. Our findings suggest alternative medical treatment methods based on gene-gene interactions, gene-microRNA (miRNA) interactions, gene-drug interactions, and pharmacogenetic variants involved in dementia and psychiatric disorders. We identify 17 genes commonly associated with both dementia and delirium including apolipoprotein E (ApoE), brain-derived neurotrophic factor (BDNF), catechol-O-methyltransferase (COMT), butyrylcholinesterase (BChE), acetylcholinesterase (AChE), DNA methyltransferase 1 (DNMT1), prion protein (PrP), tumor necrosis factor (TNF), serine palmitoyltransferase long chain base subunit 1 (SPTLC1), microtubule-associated protein tau (MAPT), alpha-synuclein (αS), superoxide dismutase 1 (SOD1), amyloid beta precursor protein (APP), neurofilament light (NFL), neurofilament heavy, 5-hydroxytryptamine receptor 2A (HTR2A), and serpin family A member 3 (ERAP3). In addition, we identify six main genes that form an inner concentric model, as well as their associated miRNA. The FDA-approved medications that were found to be effective against the six main genes were identified. Furthermore, the PharmGKB database was used to identify variants of these six genes in order to suggest future treatment options. We also looked at previous research and evidence on biomarkers that could be used to detect DSD. According to research, there are three types of biomarkers that can be used depending on the stage of delirium. The pathological mechanisms underlying delirium are also discussed. This review will identify treatment and diagnostic options for personalized DSD management.

The relationship between mild cognitive impairment and postoperative delirium undergoing total knee arthroplasty: The PNDABLE study

Background

Patients undergoing surgery are at a higher risk of developing postoperative delirium (POD) as a result of anesthesia and surgical procedures. This study examined the association between POD and mild cognitive impairment (MCI) and whether MCI influences POD through the core pathology of POD.

Methods

We enrolled Chinese Han patients undergoing unilateral total knee arthroplasty (aged 50–90, weighing 50–80 kg, and using ASAI-II), combined with epidural anesthesia between October 2020 and June 2021. All the participants were assessed using Winblad's criteria for diagnosing MCI on pre-operation and using the Confusion Assessment Method (CAM) and the Memorial Delirium Assessment Scale (MDAS) postoperative 1–7 days (or before discharge) for diagnosing POD by an anesthesiologist. Cerebrospinal fluid (CSF) biomarkers of POD were measured by enzyme-linked immunosorbent assay (ELISA). To examine the mechanism by which POD pathologies affect cognition, causal mediation analyses were performed.

Results

POD incidence was 20.2%, including 32.5% in the MCI group and 12.4% in the non-mild cognitive impairment (NMCI) group. The MCI and CSF levels of T-tau and P-tau were risk factors, and the CSF levels of Aβ₄₂, Aβ₄₂/ T-tau, and Aβ₄₂/ P-tau were protective factors in POD (p < 0.05). Part of the effects of MCI on cognition can be attributed to amyloid pathology and tau.

Conclusion

MCI may be a reasonably good prognostic factor in POD development. Overall, amyloid pathology and tau protein might partially mediate the influence of MCI on POD.

Clinical trial registration

www.clinicaltrials.gov, identifier: ChiCTR2000033439.

Potential Value of Cerebrospinal Fluid Progranulin in the Identification of Postoperative Delirium in Geriatrics Patients Undergoing Knee Replacement: The Perioperative Neurocognitive Disorder and Biomarker LifestylE Study

Objective: The aim of this study was to investigate whether progranulin (PGRN) levels in cerebrospinal fluid (CSF) were associated with postoperative delirium (POD) in geriatric patients undergoing knee replacement.

Method: A total of 600 Han Chinese patients aged 65–90 years and who underwent unilateral total knee arthroplasty were included in the Perioperative Neurocognitive Disorder And Biomarker LifestylE (PNDABLE) study from June 2020 to November 2020. All participants were assessed using the Confusion Assessment Method and the Memorial Delirium Assessment Scale on postoperative days 1–7 (or before discharge) by an anesthesiologist. CSF PGRN and CSF biomarkers of POD were measured by ELISA. We analyzed the risk and protective factors of POD using the multivariate logistic regression, and the associations between CSF PGRN and CSF biomarkers of POD using multiple linear regression. We also explored whether the influence of CSF PGRN on POD was mediated by POD core pathology in linear regression models.

Results: Postoperative delirium incidence was 9.7% (53/545). There were significant differences in preoperative CSF PGRN between patients with POD and non-POD (NPOD). As for CSF biomarkers, CSF Aβ₄₀, T-tau, and P-tau were risk factors for POD, while CSF PGRN, Aβ₄₂, and Aβ₄₂/Aβ₄₀ were protective factors for POD, as shown by the multivariate logistic regression analysis. CSF PGRN was positively associated with CSF Aβ₄₂ and was negatively associated with CSF Aβ₄₀, T-tau, and P-tau in patients with POD. We found that the AUC was 0.795 (95% CI = 0.706, 0.867) for PGRN between POD and NPOD groups. We found the influence of CSF PGRN on POD was mediated by POD core pathology. The effect was considered partial mediation with the proportion of mediation varying from 44.92 to 62.07%.

Conclusion: Cerebrospinal fluid PGRN may be a reasonably good prognostic factor for POD development. Overall, amyloid pathology and tau protein might partially mediate the influence of PGRN on POD.

Clinical Trial Registration:www.clinicaltrials.gov, identifier ChiCTR2000033439.

Neuroinflammation in perioperative neurocognitive disorders: From bench to the bedside

The perioperative neurocognitive disorders (PNDs) are one of the most common complications in elderly patients characterized by various forms of cognitive decline after anesthesia and surgery. Although the etiology for PNDs remained unclear, neuroinflammation has been characterized as one of the major causes, especially in the elderly patients. The activation of glial cells including microglia and astrocytes plays a significant role in the inflammatory responses in central nerve system (CNS). Although carefully designed, clinical studies on PNDs showed controversial results. Meanwhile, preclinical studies provided evidence from various levels, including behavior performance, protein levels, and gene expression. In this review, we summarize high‐quality studies and recent advances from both clinical and preclinical studies and provide a broad view from the onset of PNDs to its potential therapeutic targets. Future studies are needed to investigate the signaling pathways in PNDs for prevention and treatment, as well as the relationship of PNDs and future neurocognitive dysfunction.

Potential Value of Serum Lipid in the Identication of Postoperative Delirium Undergoing Knee/Hip Arthroplasty: The Perioperative Neurocognitive Disorder and Biomarker Lifestyle Study

OBJECTIVE

We aimed to investigate the relationship between preoperative lipid level and postoperative delirium (POD) and explore whether lipid's effect on POD is mediated by POD core protein.

METHODS

A total of 635 patients who were planned to undergo knee/hip arthroplasty under combined spinal-epidural anesthesia, regardless of gender, were selected. The patients were aged 40-90 years with American Society of Anesthesiologists physical status I II. The Mini-Mental State Examination (MMSE) was completed 1 day before the operation. Five milliliter elbow venous blood was taken from the patients before anesthesia, and serum levels of total cholesterol (TG), triglyceride (TC), low-density lipoprotein (LDL-C), and high-density lipoprotein (HDL-C) were detected. Cerebrospinal fluid (CSF) was extracted after successful spinal-epidural combined puncture, and amyloid beta₄₀ (Aβ₄₀), amyloid beta₄₂ (Aβ₄₂), total Tau (t-Tau), and phosphorylated Tau (p-Tau) in the CSF were measured by enzyme-linked immunosorbent assays (ELISA). After the operation, the occurrence and severity of POD were assessed using the Confusion Assessment Method and the Memorial Delirium Assessment Scale (MDAS), respectively. Patients were categorized into POD group and NPOD group. Logistic regression was used to analyze the relationship between POD and TC, TG, LDL-C, and HDL-C, and the mediating effect was used to analyze the role of POD core proteins in the relationship between lipid and MDAS. We used the receiver operating characteristic (ROC) and the precision-recall curve (PRC) analysis to assess the ability of TC, TG, LDL-C, and HDL-C ability to predict POD. Finally, we performed a sensitivity analysis to assess the stability of the results.

RESULTS

A total of 562 patients were finally enrolled in this study, and 66 patients developed POD, with an incidence of 11.7%. Logistic regression analysis showed that high concentration of TC (OR = 3.148, 95%CI 1.858∼5.333, P < 0.001), TG (OR = 2.483, 95%CI 1.573∼3.918, P < 0.001), and LDL-C (OR = 2.469, 95%CI 1.310∼4.656, P = 0.005) in serum were risk factors for POD. A high concentration of HDL-C (OR = 0.258, 95%CI 0.112∼0.594, P = 0.001) was a protective factor for POD after adjusted for age, sex, education, and MMSE score. ROC curves showed that HDL-C have the highest sensitivity and specificity in predicting POD. For these four lipid markers, the PRC range from 0.602 to 0.731, respectively. The mediating analysis showed that POD core proteins could partially mediate the relationship between lipid and POD (effect value: 16.19∼91.04%). The results were barely changed in the sensitivity analysis, and the sensitivity analysis has shown that the results were stable.

CONCLUSION

The increase of serum TG, TC, and LDL-C concentration is a risk factor for POD development, while high HDL-C concentration is a protective factor for POD, and the occurrence of POD is caused by hyperlipidemia may be caused by POD core proteins.

CLINICAL TRIAL REGISTRATION

[www.ClinicalTrials.gov], identifier [Chictr200033439].