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Objective:To investigate the value of α-synuclein (α-syn) concentration in cerebrospinal fluid (CSF) in predicting postoperative delirium (POD).Methods:One thousand patients underwent elective surgery with combined epidural-spinal anesthesia in our hospital from January 2018 to September 2020 were selected.The epidural puncture was performed at L 3, 4 interspace, and 2 ml of CSF was collected after the needle reaching the subarachnoid space.The concentrations of α-syn, β-amyloid (Aβ)40, Aβ42, total tau protein (T-tau), and phosphorylated tau protein (P-tau) in CSF were determined by enzyme-linked immunosorbent assay.The concentrations of α-syn in CSF and occurrence of POD in patients of different ages were recorded.Patients were divided into POD group and non-POD group according to whether POD occurred, and frequency matching (1∶1) was performed based on five matching variables of age, ASA physical status, education level, duration of operation, and intraoperative blood loss. Results:Eight hundred and forty-one patients were finally included in the study, and the incidence of POD was 15.0%. There were 126 cases in POD group and 126 cases in non-POD group after matching. The concentrations of α-syn in CSF and incidence of POD were gradually increased with age ( P<0.05). Compared with non-POD group, the concentrations of α-syn, T-tau and P-tau in CSF were significantly increased, the concentrations of Aβ40 and Aβ42 were decreased, Aβ40/P-tau, Aβ42/P-tau, Aβ42/Aβ40 and P-tau/T-tau were decreased in POD group ( P<0.05). After confounding factors were corrected by logistic regression analysis, increased concentrations of α-syn, p-tau, and T-tau in CSF were risk factors for POD ( P<0.05). Increased concentrations of Aβ40 and Aβ42 in CSF and increased Aβ40/P-tau and Aβ42/P-tau were protective factors for POD ( P<0.05). Multiple linear regression analysis showed that the concentration of α-syn in CSF was negatively correlated with Aβ40 and Aβ42 concentrations and positively correlated with P-tau and T-tau concentrations ( P<0.05). The area under the receiver operating characteristic curve of concentrations of α-syn in CSF predicting POD was 0.895, Youden index was 0.664, sensitivity was 80.00%, and specificity was 86.36% ( P<0.001). Conclusion:The concentration of α-syn in CSF is related to the occurrence of POD, and it provides higher accuracy in predicting POD.
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Objective:To evaluate the value of cerebrospinal fluid (CSF) nerve injury-related proteins levels in predicting postoperative delirium (POD) in patients.Methods:A total of 1 000 patients of both sexes, aged 40-90 yr, of American Society of Anesthesiologists physical status Ⅰ or Ⅱ, with Mini-Mental State Examination score>24 at 1 day before operation, undergoing elective knee/hip arthroplasty under spinal-epidural anesthesia , were enrolled in this study.Cubital venous blood samples were drawn before anesthesia for detection of the concentrations of plasma total cholesterol, high-density lipoprotein, low-density lipoprotein and triglyceride.CSF 2ml was extracted after successful spinal-epidural anesthesia puncture for measurement of concentrations of α-synuclein (α-syn), β-amyloid protein 1-40 (Aβ 1-40), Aβ 1-42, total-Tau (t-Tau), phosphorylated Tau (p-Tau), progranulin (PGRN) and soluble myeloid cell triggering receptor 2 (sTREM2) (by enzyme-linked immunosorbent assay). The Confusion Assessment Method was used at 1, 3 and 7 days after surgery to evaluate the occurrence of POD.The patients were divided into POD group and non-POD group according to whether POD occurred after operation.Logistic regression analysis was used to analyze the variables of which P values were less than 0.05 to analyze the risk factors for POD.The receiver operating characteristic (ROC) curve was drawn and area (AUC) under the curve was calculated to evaluate the accuracy of the related risk factors in predicting POD. Results:A total of 964 patients were enrolled in the study, and 108 patients were diagnosed with POD, and the incidence was 11.2%.The results of logistic regression analysis found that age and and increased α-syn in CSF concentration were risk factors for POD, and decreased PGRN in CSF concentration and Aβ 1-42/p-Tau in CSF were the protective factors for POD ( P<0.05). ROC curve analysis showed that α-syn (AUC 0.69, 95% confidence interval (CI) 0.634-0.748, sensitivity 57.41%, specificity 82.10%, Youden Index 0.3951), PGRN in CSF concentration (AUC 0.695, 95%CI 0.637-0.750, sensitivity 59.26%, specificity 80.86%, Youden Index 0.4012) and Aβ 1-42/p-Tau in CSF (AUC 0.635, 95%CI 0.574-0.692, sensitivity 93.52%, specificity 30.25%, Youden Index 0.2377) could predict the occurrence of POD. Conclusion:PGRN, α-syn concentration and Aβ 1-42/p-Tau in CSF can predict the occurrence of POD in patients.
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Objective:To evaluate the relationship between preoperative cerebrospinal fluid/serum albumin ratio (Q-alb) and postoperative delirium (POD) in patients undergoing neuraxial anesthesia.Methods:The patients, aged 40-90 yr, of American Society of Anesthesiologists physical status Ⅰ or Ⅱ, underwent total knee/hip replacement under combined spinal-epidural block in our hospital from January 2018 to December 2020, were collected.After admission to the operating room, venous blood and cerebrospinal fluid samples were collected for determination of cerebrospinal fluid albumin, β-amyloid (Aβ) 1-42, Aβ 1-40, total tau protein (t-Tau), phosphorylated tau protein (p-Tau) and serum albumin levels (by enzyme-linked immunosorbent assay) and for calculation of Q-alb.When Q-alb was more than 10.2, the patient was considered to have blood-brain barrier disruption.Mini-Mental State Examination scale was used to evaluate the cognitive level on 1 day before surgery. The development of POD was evaluated using Confusion Assessment Method Chinese Reversion and Memorial Delirium Assessment Scale at 1-7 days after surgery.The patients were divided into POD group (P group) and non-POD (NP group) according to whether POD occurred.The receiver operating characteristic (ROC) curve was used to analyze the accuracy of Q-alb in predicting POD. Results:There were 49 cases in each group.Compared with group NP, concentrations of Aβ 1-42 and Aβ 1-40 were significantly decreased, concentrations of t-Tau and p-Tau albumin were increased, the ratio of Q-alb and blood-brain barrier disruption was increased in group P ( P<0.05). Before and after adjusting for confounding factors, Q-alb, cerebrospinal fluid Aβ 1-42, Aβ 1-40, t-Tau and p-Tau levels were risk factors for POD ( P<0.05). There was a positive linear regression relationship between Q-alb and levels of t-Tau and p-Tauin cerebrospinal fluid (t-Tau: β=0.587, P<0.001; p-Tau: β=0.427, P<0.001), and there was a negative linear regression relationship between Q-alb and levels of Aβ 1-42 and Aβ 1-40 in cerebrospinal fluid (Aβ 1-42: β=-0.762, P<0.001; Aβ 1-40: β=-0.531, P<0.001). There was no linear regression relationship between Q-alb and level of p-Tau in group P ( P=0.121). There was no linear regression relationship between Q-alb and level of Aβ 1-40 in group NP ( P=0.467). The results of ROC curve analysis showed that the area under the curve for Q-alb in predicting POD (95% confidence interval) was 0.827 (0.738-0.896). Conclusion:Preoperative higher Q-alb is the risk factor for POD in patients undergoing neuraxial anesthesia, and is more accurate in predicting POD.
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Objective:To evaluate the changes in proteome in hippocampus and bioinformatics analysis in mice with perioperative neurocognitive disorders (PND).Methods:Clean-grade healthy male C57BL/6 mice, aged 15 months, weighing 30-35 g, were divided into 2 groups ( n=9 each) using a random number table method: control group (group C) and group PND.The model of PND was established by performing open tibial fracture with intramedullary fixation under isoflurane anesthesia in anesthetized mice.The Morris water maze test, open field test and fear conditioning test were performed at 1 day before operation and at 1, 3 and 7 days after operation.At 1, 3 and 7 days after operation, 3 mice with worst cognitive performance in each cognitive function assessments were sacrificed in group P, and three mice were randomly sacrificed in group C. The hippocampal tissues were then obtained, the expression of differentially expressed proteins was identified by high-performance liquid chromatography-mass spectrometry, and Gene Ontology (GO) functional analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were performed to analyze the differentially expressed proteins. Results:Compared with group C, the escape latency at different time points was significantly prolonged, and the percentage of time spend on target quadrant and the percentage of freezing time in fear conditioning test were decreased in group P ( P<0.05). There were 21 differentially expressed proteins, of which 12 proteins showed up-regulated expression and 9 proteins showed down-regulated expression.The GO functional analysis showed that the differentially expressed proteins were involved in the process such as the metabolism, signal transmission, regulation of biological processes, formed cell components such as synapses and organelles, and were related to molecular function such as binding and transportation.KEGG signaling pathway analysis showed that there were also differences in MAPK signaling pathway, ErbB signaling pathway, AMPK signaling pathway and the transport of SNARE protein in vesicle and etc. Conclusion:There are 21 differentially expressed proteins in the hippocampus of PND mice, and these proteins are involved in the pathophysiological process probably related to PND such as neuroinflammatory responses, abnormal synaptic structure, mitochondrial dysfunction and decreased autophagy.
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Objective:To establish the risk prediction models for postoperative delirium (POD) in elderly patients undergoing non-cardiac surgery and to evaluate the predictive efficacy.Methods:A total of 685 patients of both sexes, aged 65-90 yr, of American Society of Anesthesiologists (ASA) physical status Ⅰ-Ⅳ, who underwent non-cardiac elective surgery requiring tracheal intubation during general anesthesia in general surgery, orthopedics, urology, hepatobiliary and pancreatic surgery in our hospital from January 2020 to December 2020, were selected.Patients were assigned to the training set and validation set at a ratio of 7∶3 using a simple random sampling method.The clinical data of patients in the perioperative period were collected, and the patients were followed up within 1-7 days after operation (or before discharge), and the occurrence of POD was recorded.Univariate and multivariate logistic regression analysis was used to identify the independent risk factors for POD.The risk prediction model for POD was established based on the results of multivariate logistic regression analysis of the training set, a nomogram and receiver operating characteristic (ROC) curve were drawn, and the area under the curve (AUC) was calculated.The validation set was used to verify the prediction model and assess the efficacy of the risk prediction model for POD.Results:A total of 653 patients were enrolled in this study, 139 patients developed POD, and the incidence was 21.3%.The results of multivariate logistic regression analysis showed that advanced age, high ASA physical status classification, low preoperative Mini-Mental State Examination score, complication with diabetes mellitus, low years of education, high preoperative Pittsburgh Sleep Quality Index scale score, long anesthesia time and high numerical rating scale score after operation were independent risk factors for POD in elderly patients undergoing non-cardiac surgery.The risk prediction model for POD was established based on the independent risk factors mentioned above.The AUC of the training set was 0.981, the Youden index was 0.881, the sensitivity was 95.95%, and the specificity was 92.92%; the AUC of the validation set was 0.939, the Youden index was 0.795, the sensitivity was 94.44%, and the specificity was 85.09%.Conclusion:The risk prediction model for POD established based on age, ASA physical status classification, history of diabetes melittus, years of education, preoperative Mini-Mental State Examination score, preoperative Pittsburgh sleep quality index scale score, anesthesia time and postoperative numerical rating scale score has good predictive efficacy in elderly patients undergoing non-cardiac surgery.