Purpose: We aimed to investigate the relevance of body mass index (BMI) to postoperative delirium (POD), and to test whether the influences of BMI on POD were mediated by cerebrospinal fluid (CSF) biomarkers.Patients and methods: Our study recruited 682 and 761 cognitively intact individuals from the perioperative neurocognitive disorder risk factor and prognosis (PNDRFAP) study and the perioperative neurocognitive disorder and biomarker lifestyle (PNDABLE) study, respectively. The incidence of POD was evaluated by using Confusion Assessment Method (CAM), and POD severity was measured by using the Memorial Delirium Assessment Scale (MDAS). Logistic regression was used to analyze the relationship between BMI and POD. The levels of Aβ40, Aβ42, T‐tau, and P‐tau in preoperative CSF were measured by enzyme‐linked immune‐sorbent assay (ELISA) in the PNDABLE study. Mediation analysis with 5000 bootstrapped iterations was used to explore the mediation effects.Results: In the PNDRFAP study, the incidence of POD was 16.3%, with logistic regression analysis showing that BMI (odds ratio [OR] = 0.900, 95% confidence interval [CI] 0.823–0.985, p = .022) is a protective factor of POD. In the PNDABLE study, the incidence of POD was 18.7%, and regression analysis confirmed that BMI (OR = 0.832, 95% CI 0.761–0.910, p < .001) is a protective factor of POD, while T‐tau (OR = 1.005, 95% CI 1.003–1.006, p < .001) and P‐tau (OR = 1.037, 95% CI 1.024–1.050, p < .001) were risk factors of POD. Mediation analyses revealed that the association between BMI and POD was partially mediated by T‐tau (proportion: 36%) and P‐tau (proportion: 24%).Conclusion: Higher BMI mediated protective effects on POD through CSF biomarkers (T‐tau and P‐tau).

Objectives: This study aimed to reveal the relationship between alcohol consumption and Postoperative delirium (POD) in the elderly. Methods: We selected 252 patients from the Perioperative Neurocognitive Disorder And Biomarker Lifestyle (PNDABLE ) study. Patients in the PNDABLE database have been measured for Alzheimer-related biomarkers in CSF (Aβ₄₀, Aβ₄₂, P-tau, and tau protein). Mini-Mental State Examination (MMSE) was used to assess the preoperative mental status of patients. POD was diagnosed using the Confusion Assessment Method (CAM) and assessed for severity using the Memorial Delirium Assessment Scale (MDAS). Logistic regression analysis was utilized to explore the association of alcohol consumption with POD. Linear regression analysis was used to study the relationship between alcohol consumption and CSF biomarkers. Mediation analyses with 10,000 bootstrapped iterations were used to explore the mediation effects. Finally, we constructed the receiver operating characteristic (ROC) curve and the nomogram model to evaluate the efficacy of alcohol consumption and CSF biomarkers in predicting POD. Result: The incidence of POD was 17.5%. Logistic regression showed that alcohol consumption (OR = 1.016, 95%CI 1.009–1.024, P < 0.001) is a risk factor for POD. What’s more, Aβ₄₂ is a protective factor for POD (OR = 0.993, 95%CI 0.989–0.997, P < 0.05), and P-Tau was a risk factor for POD (OR = 1.093, 95%CI 1.022–1.168, P < 0.05). Linear regression analysis revealed that alcohol consumption was negatively associated with CSF Aβ₄₂ (β = -0.638, P < 0.001) in POD patients. Mediation analyses showed that alcohol consumption is likely to partially mediate POD through Aβ42 (proportion:14.21%). ROC curve showed that alcohol consumption (AUC = 0.904; P < 0.001) exhibited a relatively better discriminatory ability in POD prediction compared to Aβ₄₂ (AUC = 0.798; P < 0.001). The calibration curve indicated a good nomogram prediction (P = 0.797). Conclusion: Alcohol consumption is a risk factor for POD (particularly for those with > 24 g a day on average) in the elderly, and contributes to POD through the mediation of Aβ₄₂.

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].

Objective: Our study aimed to investigate the correlation between intraoperative hypothermia and postoperative delirium (POD) in patients undergoing general anesthesia for gastrointestinal surgery.Methods: The study comprised 750 participants from the Perioperative Neurocognitive Disorder Risk Factor and Prognosis (PNDRFAP) study database, which ultimately screened 510 individuals in the final analysis. Preoperative cognitive function was evaluated using the Mini‐Mental State Examination (MMSE). The occurrence of POD was determined using the Confusion Assessment Method, and the severity of POD was evaluated using the Memorial Delirium Assessment Scale. Logistic regression was employed to scrutinize the association between intraoperative hypothermia and the incidence of POD, and the sensitivity analysis was conducted by introducing adjusted confounding variables. Decision curves and a nomogram model were utilized to assess the predictive efficacy of intraoperative hypothermia for POD. Mediation analysis involving 10,000 bootstrapped iterations was employed to appraise the suggested mediating effect of numeric rating scale (NRS) scores at 24 and 48 h post‐surgeries. The receiver‐operating characteristic (ROC) was utilized to evaluate the effectiveness of intraoperative hypothermia in predicting POD.Results: In the PNDRFAP study, the occurrence of POD was notably higher in the intraoperative hypothermia group (62.2%) compared to the intraoperative normal body temperature group (9.8%), with an overall POD incidence of 17.6%. Logistic regression analysis, adjusted for various confounding factors (age [40–90], gender, education, MMSE, smoking history, drinking history, hypertension, diabetes, and the presence of cardiovascular heart disease), demonstrated that intraoperative hypothermia significantly increased the risk of POD (OR = 4.879, 95% CI = 3.020–7.882, p < .001). Mediation analyses revealed that the relationship between intraoperative hypothermia and POD was partially mediated by NRS 24 h after surgery, accounting for 14.09% of the association (p = .002). The area under the curve of the ROC curve was 0.685, which confirmed that intraoperative hypothermia could predict POD occurrence to a certain extent. Decision curve and nomogram analyses, conducted using the R package, further substantiated the predictive efficacy of intraoperative hypothermia on POD.Conclusion: Intraoperative hypothermia may increase the risk of POD, and this association may be partially mediated by NRS scores 24 h after surgery.

Background: In the global aging population, the incidence of postoperative delirium (POD) is increasing. Therefore, finding its effective predictive tools becomes crucial. We aimed to identify potential Cerebrospinal fluid (CSF)biomarkers for POD. Methods: A total of 825 patients undergoing knee/hip arthroplasty under combined spinal-epidural anesthesia were selected. The patients were aged 40 to 90 years with American Society of Anesthesiologists physical status I~II. The Mini-Mental State Examination was completed 1 day before the operation. CSF was extracted after successful spinal-epidural combined puncture, and α-synuclein (α-syn), amyloid beta₄₀ (Aβ₄₀), amyloid beta₄₂ (Aβ₄₂), t-Tau, phosphorylated Tau (p-Tau), progranulin (PGRN) and soluble triggering receptor expressed on myeloid cells 2 (sTREM2) in the CSF were measured by enzyme-linked immunosorbent assays (ELISA). The patient’s operation time, anesthesia time, intraoperative blood loss and fluid input were also recorded. After the operation, the occurrence rate and severity of POD were determined by the Confusion Assessment Method and the Memorial Delirium Assessment Scale (MDAS), respectively. Patients were categorized into POD group and non-POD group. Logistic regression analysis was performed on the indicators with statistically significant differences, and the area under the ROC curve (AUC) was used to estimate the predictive accuracy of the biomarkers for POD. Results: A total of 92 patients developed POD and the incidence of POD was 11.15%. The results of the multivariable logistic regression showed that CSF t-Tau (P = 0.004, OR = 1.006, 95%CI 1.002~1.009) and α-syn (P = 0.004, OR = 1.001, 95%CI 1.000~1.001) were positively associated with the occurrence rate of POD, while Aβ₄₂ (P < 0.001, OR = 0.989, 95%CI 0.986~0.993), CSF PGRN (P = 0.002, OR = 0.999, 95%CI 0.999~1.000), Aβ₄₂/ t-Tau (P < 0.001, OR = 0.181, 95%CI 0.102~0.319) and Aβ₄₂/p-Tau (P < 0.001, OR = 0.617, 95%CI 0.526~0.725) were inversely proportional to the occurrence of POD. ROC curve analysis indicated that Aβ₄₂/t-Tau (AUC = 0.823), CSF Aβ₄₂ (AUC = 0.813), Aβ₄₂/p-Tau (AUC = 0.810), α-syn (AUC = 0.644) and PGRN (AUC = 0.638) could predict the occurrence rate of POD. The combination of all these biomarkers showed a greater AUC(0.896) than using any of them alone. Conclusions: CSF Aβ₄₂, PGRN, α-syn, Aβ₄₂/t-Tau and Aβ₄₂/p-Tau might be associated with the occurrence rate of POD in patients undergoing knee/hip arthroplasty. Trial registration: Clinical Registration No. ChiCTR2000033439.

Objectives: In this study, the relationship between preoperative neutrophil‐to‐lymphocyte ratio (NLR) and Alzheimer‐related biomarkers in cerebrospinal fluid (CSF) was investigated to determine whether high NLR is a potential risk factor for postoperative delirium (POD) and to evaluate its predictive efficacy.Methods: We selected 1000 patients from the perioperative neurocognitive disorder risk factor and prognosis (PNDRFAP) database and 999 patients from the perioperative neurocognitive disorder and biomarker lifestyle (PNDABLE) database. Patients in the PNDABLE database have been measured for Alzheimer‐related biomarkers in CSF (Aβ₄₀, Aβ₄₂, P‐tau, and tau protein). Mini‐mental state examination was used to assess the preoperative mental status of patients. POD was diagnosed using the confusion assessment method and assessed for severity using the memorial delirium assessment scale. Logistic regression analysis was utilized to explore the association of preoperative NLR with POD. What's more, we also performed sensitivity analysis by adding corrected confounders, and the results were almost unchanged. Spearman's rank correlation was used to determine the associations between NLR and Alzheimer‐related biomarkers. Mediation analyses with 10,000 bootstrapped iterations were used to explore the mediation effects. Finally, we use decision curves and the nomogram model to evaluate the efficacy of preoperative NLR in predicting POD; we also performed external validation using data from Qilu Hospital.Result: Logistic regression results showed that an elevated preoperative NLR was a risk factor for the development of POD in patients (PNDRFAP: OR = 1.067, 95% CI 1.020–1.116; PNDABLE: OR = 1.182, 95% CI 1.048–1.335, p < .05). Spearman's rank correlation analysis showed a positive but weak correlation between NLR and P‐tau/T‐tau (R = .065). The mediating effect results indicate that NLR likely mediates the occurrence of POD through elevated tau protein levels (proportion: 47.47%). The results of the box plots showed statistically significant NLR and CSF biomarkers between the POD and non‐POD (NPOD) groups (p < .05), with higher NLR, P‐tau, and T‐tau in the POD group than in the NPOD group. In contrast, the NPOD group had higher Aβ₄₂ levels compared to the POD group. In addition, we used R package to plot the decision curve and nomogram both suggesting a good predictive effect of preoperative NLR on the occurrence of POD.Conclusion: Elevated preoperative NLR levels may be a risk factor for POD and likely mediate the development of POD through elevated P‐tau/T‐tau levels.