Postoperative delirium and its relationship with biomarkers for dementia: a meta-analysis

Prevalence of neurocognitive disorders 5 years after elective orthopaedic surgery

BACKGROUND

Peri-operative neurocognitive disorders are one of the most common complications affecting older adults after anaesthesia and surgery. It is not clear how exposure to surgery and anaesthesia contributes to the prevalence of long-term neurocognitive disorders. This study aimed to report the prevalence of neurocognitive disorders, and explore pre-operative factors associated with neurocognitive disorders 5 years after elective orthopaedic surgery.

METHODS

A prospective, 5-year longitudinal, cohort study was performed recruiting patients (aged ≥ 60 y) undergoing elective orthopaedic surgery and a contemporaneous non-surgical control group. Neurocognitive disorder was evaluated and classified at baseline and 5-year review incorporating: self- and informant-reported cognition; functional participation; and performance on neuropsychological tests.

RESULTS

Recruitment at 5-year follow-up included 195 patients and 21 control participants. In the patient cohort the prevalence of neurocognitive disorder was 38.1% (n = 75), with 61 (30.1%) meeting the criteria for mild neurocognitive disorder and 14 (7.1%) for major neurocognitive disorder. At 5-year follow-up, 121 (61.4%) patients were classified with a neurocognitive disorder, with 88 (44.7%) characterised with mild neurocognitive disorder and 33 (16.8%) with major neurocognitive disorder. Age (odds ratio (95%CI) 1.07 (1.02-1.13); p = 0.01) and baseline cognitive impairment (odds ratio (95%CI) 2.1 (1.06-4.15); p = 0.03) were significant predictors of neurocognitive disorder 5 years after surgery.

CONCLUSION

More than half of older adult patients had some form of neurocognitive disorder 5 years after elective orthopaedic surgery. Surgery and anaesthesia may be associated with the trajectory of cognitive decline in at-risk older adults, including those with pre-operative cognitive impairment. Cognitive screening should be factored into pre-operative assessments of older adults to inform subsequent care.

Alterations in Neurotrophins in Alcohol-Addicted Patients during Alcohol Withdrawal

BACKGROUND

Alcohol use disorder (AUD) is related to mental and somatic disorders that result in alcohol withdrawal syndrome (AWS), with 30% of AWS cases leading to life-threatening delirium tremens (DTs). Currently, studies do not support using any one biomarker in DTs. Neurotrophins affect neuromodulation, playing a role in the pathogenesis of AUD, AWS, and DTs.

METHODS

This review aims to summarize experimental and clinical data related to neurotrophins and S100B in neuroplasticity, as well as neurodegeneration in the context of AUD, AWS, and DTs. This work used publications that were selected based on the protocol consistent with the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) statement.

RESULTS

The BDNF level could be a good candidate biomarker for relapse susceptibility, as it is significantly reduced during consumption and gradually increases during abstinence. GDNF influences AUD through its integral role in the function of dopaminergic neurons and ablates the return to alcohol-drinking behavior. NGF protects neurons from ethanol-induced cytotoxic damage and affects recovery from cognitive deficits after brain damage. The NT-3 level is decreased after alcohol exposure and is involved in compensatory mechanisms for cognitive decline in AUD. NT-4 affects oxidative stress, which is associated with chronic alcohol consumption. S100B is used as a biomarker of brain damage, with elevated levels in serum in AUD, and can protect 5-HT neurons from the damage caused by alcohol.

CONCLUSIONS

BDNF, GDNF, NT-3, NT-4, NGF, and S100B may be valuable markers for withdrawal syndrome. In particular, the most relevant is their association with the development of delirium complications. However, there are few data concerning some neurotrophins in AWS and DTs, suggesting the need for further research.

Inflammatory and nutritional markers predict the risk of post-operative delirium in elderly patients following total hip arthroplasty

Objectives

This study intended to explore whether albumin-associated inflammatory and nutritional markers could predict post-operative delirium (POD) in older patients after total hip arthroplasty (THA). In addition, we established a nomogram model for POD prediction.

Methods

Totally, 254 elderly cases who received THA were included. Clinical and laboratory data of these patients were retrospectively collected. Albumin-associated inflammatory and nutritional markers included neutrophil-to-albumin ratio (NAR), CRP-to-albumin ratio (CAR), prognostic nutritional index (PNI), and systemic inflammation score (SIS). The LASSO, univariate and multivariate logistic regression analyses were utilized to screen risk factors. A nomogram model was developed according to the results of multivariate regression analyses.

Results

Among 254 patients, 49 cases had POD with an incidence of 19.3%. LASSO regression and multivariate logistic analyses suggested that preoperative NAR, preoperative PNI, preoperative SIS, and age >75 years were risk factors for POD. A nomogram model was developed according to the results of multivariate logistic analyses. The calibration curve suggested that the predicted probability of this nomogram model was in good line with the actual probability. The DCA showed that this nomogram model had net benefits for the prediction of POD for elderly patients following THA.

Conclusion

Albumin-associated inflammatory and nutritional markers including NAR, PNI, and SIS could predict POD in elderly patients following THA.

Taming Postoperative Delirium with Dexmedetomidine: A Review of the Therapeutic Agent's Neuroprotective Effects following Surgery

Postoperative delirium (POD) represents a perioperative neurocognitive disorder that has dreaded ramifications on a patient's recovery from surgery. Dexmedetomidine displays multiple mechanisms of neuroprotection to assist in preventing POD as a part of a comprehensive anesthetic care plan. This review will cover dexmedetomidine's pharmacological overlap with the current etiological theories behind POD along with pre-clinical and clinical studies on POD prevention with dexmedetomidine. While the body of evidence surrounding the use of dexmedetomidine for POD prevention still requires further development, promising evidence exists for the use of dexmedetomidine in select dosing and circumstances to enhance recovery from surgery.

Postoperative Delirium and Dementia in Patients Undergoing Cardiac Surgery: A Review of Randomized Controlled Trials

Delirium and dementia are considered to be the most significant postoperative neurocognitive complications in patients undergoing cardiac surgery, particularly those aged 60 years and older, which reduces the post-surgery quality of life, prolongs hospitalization, increases costs, and elevated the rates of mortality. Nevertheless, the etiology, risk factors, and predictive biomarkers, have not been well elucidated particularly, in patients with unmanifested underline cognitive impairments. The present study aimed to review the findings on the etiology, factors increasing the risk of incidence, and predictive biomarkers of postoperative delirium and dementia after cardiac surgery, and to describe the suggested pharmacological and non-pharmacological interventions.

Causal relationships between delirium and Alzheimer's disease: a bidirectional two-sample Mendelian randomization study

BACKGROUND

Previous observational studies have reported that delirium has an association with an increased risk of Alzheimer's disease (AD), and that patients with AD have a higher risk of developing delirium. However, due to the limitations of observational study, it is challenging to confirm whether delirium has a causal effect on AD or reverse causation exists.

METHODS

A bidirectional two-sample Mendelian randomization (MR) was performed to investigate the relationship between delirium and AD. Summary statistics from genome-wide association studies of delirium and AD phenotypes were utilized. Inverse-variance weighted (IVW) method was used as the main analysis approach, and additional analyses were performed using MR Egger, weighted median, simple mode and weighted mode to ensure result accuracy. Heterogeneity and horizontal pleiotropy were assessed using Cochran's Q statistics and MR Egger intercept, separately.

RESULTS

The MR analyses showed that genetically predicted delirium was not associated with AD (IVW: odds ratio [OR] 0.98, 95% CI 0.91-1.05, P = 0.544; MR Egger: OR 0.98, 95% CI 0.83-1.15, P = 0.780; weighted median: OR 0.96, 95% CI 0.88-1.05, P = 0.323; simple mode: OR 0.91, 95% CI 0.80-1.04, P = 0.212; weighted mode: OR 0.93, 95% CI 0.83-1.05, P = 0.277). However, in the reverse direction, AD was associated with delirium (IVW: OR 1.32, 95% CI 1.13-1.54, P = 3.91E-04; MR Egger: OR 1.42, 95% CI 1.02-1.98, P = 5.60E-02; Weighted median: OR 1.39, 95% CI 1.18-1.63, P = 8.22E-05; Simple mode: OR 1.41, 95% CI 1.10-1.80, P = 1.41E-02; Weighted mode: OR 1.39, 95% CI 1.16-1.67, P = 3.23E-03).

CONCLUSION

Based on the results of our MR study, there is no bidirectional causality between delirium and AD, delirium is not associated with an increased risk of AD, while genetically predicted AD is a potential causal risk factor for delirium.

Biomarkers of delirium risk in older adults: a systematic review and meta-analysis

Delirium is a neuropsychiatric syndrome associated with increased morbidity and mortality in older patients. The aim of this study was to review predictive biomarkers of delirium in older patients to gain insights into the pathophysiology of this syndrome and provide guidance for future studies. Two authors independently and systematically searched MEDLINE, Embase, Cochrane Library, Web of Science and Scopus databases up to August 2021. A total of 32 studies were included. Only 6 studies were eligible for the meta-analysis, pooled results showed a significant increase in some serum biomarkers (C-reactive protein [CRP], tumour necrosis factor alpha [TNF-α] and interleukin-6 [IL-6]) among patients with delirium (odds ratio = 1.88, 95% CI 1.01 to 1.637; I2 = 76.75%). Although current evidence does not favour the use of any particular biomarker, serum CRP, TNF-α, and IL-6 were the most consistent biomarkers of delirium in older patients.

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.

Postoperative C-Reactive Protein Predicts Postoperative Delirium in Colorectal Cancer Following Surgery

Background

Postoperative delirium (POD) is a common complication in operative patients. Neuroinflammation has been reported to be a potential mechanism associated with the development of POD. Identifying available inflammatory markers such as C-reactive protein (CRP) would aid clinicians in early detection of POD. Previous studies have demonstrated that CRP may be a promising predictive marker for POD. Thus, this study aimed to explore the association between CRP and POD among those elderly colorectal cancer (CRC) patients.

Methods

643 patients with CRC were included in this study. CRP levels were measured before operation and on postoperative day 1. The univariate and multivariate regression analyses were used to identify risk factors for POD.

Results

Of 643 patients with CRC, 112 cases (17.4%) had POD. CRC patients with POD showed older age, higher CRP level on postoperative day 1, and higher percentage of smoking, diabetes mellitus, and chronic obstructive pulmonary disease (COPD) than CRC patients without POD. Preoperative CRP level was not associated with the POD. Univariate and multivariate regression analyses showed that older age (> 70 years), diabetes mellitus, COPD, and higher CRP level on postoperative day 1 (> 48 mg/L) were risk factors for POD in CRC patients.

Conclusion

Postoperative CRP level is an independent indicator for POD among CRC patients, suggesting the predictive role of postoperative CRP levels for POD in elderly CRC patients undergoing surgery.

The effect of parecoxib sodium on postoperative delirium in elderly patients with hip arthroplasty

Objective: This study aimed to clarify the effect of parecoxib sodium on the occurrence of postoperative delirium and to investigate its possible mechanism. Methods: A total of 80 patients who underwent elective hip arthroplasty in our hospital between December 2020 and December 2021 were selected and randomly divided into two groups: a parecoxib sodium group (group P, n = 40) and a control group (group C, n = 40). Patients in group P were intravenously injected with 40 mg of parecoxib sodium 30 min before anesthesia and at the end of the surgery. Patients in group C were intravenously injected with the same volume of normal saline at the same time points. The primary endpoint was the incidence of POD, and the secondary endpoints were the levels of inflammatory factors (tumor necrosis factor- α [TNF-α], interleukin [IL]-1β, IL-6, and IL-10), nerve injury-related factors (brain-derived neurotrophic factor [BDNF], S-100β protein, neuron-specific enolase [NSE], and neurofilament light chain [NfL]), and antioxidant factors (heme oxygenase-1 [HO-1]), as well as the Visual Analogue Scale (VAS) and Confusion Assessment Method-Chinese Reversion (CAM-CR) scores. Results: The incidence of POD was 10% in group P and 27.5% in group C. Intergroup comparison revealed that the levels of TNF-α, IL-1β, S-100β, NfL, and NSE were lower, and BDNF was higher, in group P than in group C at each postoperative time point. The levels of IL-6 were lower, and the levels of IL-10 and HO-1 were higher, in group P than in group C at 1 h and 1 day postoperatively (p < 0.05). Three days after surgery, the differences in the levels of IL-6, IL-10, and HO-1 were not statistically significant between the two groups (p > 0.05). The VAS and CAM-CR scores were lower at each postoperative time point in group P than in group C (p < 0.05). Conclusion: Parecoxib sodium could reduce postoperative pain, decrease the plasma levels of inflammatory and nerve injury-related factors, upregulate HO-1 levels, and reduce the incidence of POD. The results of this study suggest that parecoxib sodium may reduce the occurrence of POD through the effects of anti-inflammation, analgesia, and antioxidants.

Automated machine learning-based model for the prediction of delirium in patients after surgery for degenerative spinal disease

OBJECTIVE

This study used machine learning algorithms to identify critical variables and predict postoperative delirium (POD) in patients with degenerative spinal disease.

METHODS

We included 663 patients who underwent surgery for degenerative spinal disease and received general anesthesia. The LASSO method was used to screen essential features associated with POD. Clinical characteristics, preoperative laboratory parameters, and intraoperative variables were reviewed and were used to construct nine machine learning models including a training set and validation set (80% of participants), and were then evaluated in the rest of the study sample (20% of participants). The area under the receiver-operating characteristic curve (AUROC) and Brier scores were used to compare the prediction performances of different models. The eXtreme Gradient Boosting algorithms (XGBOOST) model was used to predict POD. The SHapley Additive exPlanations (SHAP) package was used to interpret the XGBOOST model. Data of 49 patients were prospectively collected for model validation.

RESULTS

The XGBOOST model outperformed the other classifier models in the training set (area under the curve [AUC]: 92.8%, 95% confidence interval [CI]: 90.7%-95.0%), validation set (AUC: 87.0%, 95% CI: 80.7%-93.3%). This model also achieved the lowest Brier Score. Twelve vital variables, including age, serum albumin, the admission-to-surgery time interval, C-reactive protein level, hypertension, intraoperative blood loss, intraoperative minimum blood pressure, cardiovascular-cerebrovascular disease, smoking, alcohol consumption, pulmonary disease, and admission-intraoperative maximum blood pressure difference, were selected. The XGBOOST model performed well in the prospective cohort (accuracy: 85.71%).

CONCLUSION

A machine learning model and a web predictor for delirium after surgery for the degenerative spinal disease were successfully developed to demonstrate the extent of POD risk during the perioperative period, which could guide appropriate preventive measures for high-risk patients.