Association of sleep quality on the night of operative day with postoperative delirium in elderly patients: A prospective cohort study.

BACKGROUND: Sleep disturbances in the peri-operative period have been associated with adverse outcomes, including postoperative delirium (POD). However, research on sleep quality during the immediate postoperative period is limited. OBJECTIVES: This study aimed to investigate the association between sleep quality on the night of the operative day assessed using the Sleep Quality Numeric Rating Scale (SQ-NRS), and the incidence of POD in a large cohort of surgical patients. DESIGN: A prospective cohort study. SETTING: A tertiary hospital in China. PATIENTS: This study enrolled patients aged 65 years or older undergoing elective surgery under general anaesthesia. The participants were categorised into the sleep disturbance and no sleep disturbance groups according to their operative night SQ-NRS. MAIN OUTCOME MEASURES: The primary outcome was delirium incidence, whereas the secondary outcomes included acute kidney injury, stroke, pulmonary infection, cardiovascular complications and all-cause mortality within 1 year postoperatively. RESULTS: In total, 3072 patients were included in the analysis of this study. Among them, 791 (25.72%) experienced sleep disturbances on the night of operative day. Patients in the sleep disturbance group had a significantly higher risk of developing POD (adjusted OR 1.43, 95% CI 1.11 to 1.82, P  = 0.005). Subgroup analysis revealed that age 65-75 years; male sex; ASA III and IV; haemoglobin more than 12 g l -1 ; intra-operative hypotension; surgical duration more than 120 min; and education 9 years or less were significantly associated with POD. No interaction was observed between the subgroups. No significant differences were observed in the secondary outcomes, such as acute kidney injury, stroke, pulmonary infection, cardiovascular complications and all-cause mortality within 1 year postoperatively. CONCLUSIONS: The poor subjective sleep quality on the night of operative day was independently associated with increased POD risk, especially in certain subpopulations. Optimising peri-operative sleep may reduce POD. Further research should investigate potential mechanisms and causal relationships. TRIAL REGISTRY: chictr.org.cn: ChiCTR1900028545.

Association between intraoperative mean arterial pressure variability and postoperative delirium after hip fracture surgery: a retrospective cohort study.

BACKGROUND: Postoperative delirium (POD) is a common complication in elderly patients after hip fracture surgery. Our study was to investigate whether intraoperative mean arterial pressure variability (MAPV) was associated with POD in elderly patients after hip fracture surgery. METHODS: In this retrospective cohort study, patients aged 65 years and older undergoing hip fracture surgery were included. The correlation between MAPV and POD was investigated using univariate and multivariate logistic regression. Covariate-related confounding effects were eliminated with propensity score matching (PSM) analysis. Then, a subgroup analysis was conducted to further examine the associations between MAPV and POD. RESULTS: Nine hundred sixty-three patients with a median age of 80 years (IQR: 73-84) were enrolled. POD occurred in 115/963 (11.9%) patients within 7 days after surgery. According to multivariate regression analysis, MAPV > 2.17 was associated with an increased risk of POD (OR: 2.379, 95% CI: 1.496-3.771, P < 0.001). All covariates between the two groups were well balanced after PSM adjustment. A significant correlation between MAPV and POD was found in the PSM analysis (OR: 2.851, 95% CI: 1.710-4.746, P < 0.001). CONCLUSIONS: An increased intraoperative MAPV may be a predictor for POD.

The modified lymphocyte C-reactive protein score is a promising indicator for predicting 3-year mortality in elderly patients with intertrochanteric fractures.

BACKGROUND: Hip fractures are common in elderly patients, and almost all the patients undergo surgery. This study aimed to develop a novel modified lymphocyte C-reactive protein (CRP) score (mLCS) to simply and conveniently predict 3-year mortality in elderly patients undergoing intertrochanteric fracture surgery. METHODS: A retrospective study was conducted on elderly patients who underwent intertrochanteric fracture surgery between January 2014 and December 2017. The mLCS was developed according to the value of CRP and lymphocyte counts. Univariate and multivariate Cox regression analyses were used to identify independent risk factors for 3-year mortality after surgery. The performances of the lymphocyte CRP score (LCS) and mLCS to predict 3-year mortality were then compared using C-statistics, decision curve analysis (DCA), net reclassification index (NRI) and integrated discrimination improvement (IDI). RESULTS: A total of 291 patients were enrolled, of whom 52 (17.9%) died within 3 years after surgery. In the multivariate Cox regression analysis, mLCS (hazard ratio (HR), 5.415; 95% confidence interval (CI), 1.743-16.822; P = 0.003) was significantly associated with postoperative 3-year mortality. The C-statistics of LCS and mLCS for predicting 3-year mortality were 0.644 and 0.686, respectively. The NRI (mLCS vs. LCS, 0.018) and IDI (mLCS vs. LCS, 0.017) indicated that the mLCS performed better than the LCS. DCA also showed that mLCS had a higher clinical net benefit. CONCLUSIONS: mLCS is a promising predictor that can simply and conveniently predict 3-year mortality in elderly patients undergoing intertrochanteric fracture surgery.

Preoperative Alpha-Blocker Therapy in Patients with Missed Preoperative Diagnosis of Extra-Adrenal Retroperitoneal Paraganglioma Undergoing Resection: A Retrospective Study of 167 Cases at a Single Center.

INTRODUCTION: Preoperative α-adrenergic blockade is thought to decrease perioperative risks and mortality in surgeries for adrenal pheochromocytoma. However, there are limited data on the efficacy of α-blockers in surgeries for retroperitoneal paragangliomas. The aim of this study was to evaluate the effects of the preoperative α-adrenergic blockade on outcomes in patients undergoing surgery for extra-adrenal retroperitoneal paraganglioma. METHODS: We searched the clinical database for patients diagnosed with extra-adrenal retroperitoneal paraganglioma by postoperative histopathology in the General Hospital of People's Liberation Army in China from 2000 to 2017. We compared the preoperative status of patients, preoperative examination, preoperative preparation, intraoperative and postoperative cardiovascular events, intake and output, length of stay in the intensive care unit, length of hospital stays, and short-term outcomes between patients who received preoperative treatment with α-adrenergic blockade and those who did not. RESULTS: Of the 167 patients enrolled in the study, 61 received preoperative α-adrenergic blockade therapy. Intraoperative heart rate elevation and highest heart rate were higher in patients undergoing tumor manipulation with preoperative α-adrenergic blockade than those who did not (p < 0.05). However, there were no significant differences between these 2 groups in terms of intraoperative blood pressure elevation and systolic blood pressure decrease following tumorectomy (p > 0.05). Moreover, there were no significant differences in postoperative complications and outcomes (p > 0.05). CONCLUSION: Under the current medical practice, resection of extra-adrenal retroperitoneal paraganglioma can be successfully carried out with or without preoperative α-adrenergic blockade.

Systemic immune-inflammation index predicts postoperative delirium in elderly patients after surgery: a retrospective cohort study.

BACKGROUND: Postoperative delirium (POD) is a common complication among elderly patients after surgery. It is unclear whether the systemic immune-inflammation index (SII) can be a predictor of POD. We explored the prognostic value of the SII in predicting POD in elderly patients undergoing non-neurosurgery and non-cardiac surgery in a large retrospective cohort. METHODS: We enrolled elderly patients undergoing non-neurosurgery and non-cardiac surgery between January 2014 and August 2019. Univariate and multivariate logistic regression analyses were performed to explore the correlation between POD and the SII value as both a continuous and categorical variable. Then, propensity score matching (PSM) analysis was applied to eliminate the confounding effect of covariates and prove our results. Subgroup analyses were then performed to discover the association between the SII and POD in different subgroups. RESULTS: A total of 29,608 patients with a median age of 70 years (IQR: 67-74) were enrolled in the retrospective cohort. The cut-off value of the SII was 650, which was determined by the receiver operating characteristic (ROC) curve. The ORs of an SII value > 650 was 2.709 (95% CI:2.373-3.092, P < 0.001), 1.615 (95% CI:1.384-1.882, P < 0.001), 1.855 (95% CI:1.602-2.146, P < 0.001), and 1.302 (95% CI:1.106-1.531, P = 0.001) for prediction of POD in univariate model and three multivariate regression models. After PSM, the OR of an SII value > 650 was 1.301 (95% CI: 1.062-1.598, P = 0.011). The subgroup analysis indicated that the SII indicates a significantly increased risk of POD in patients with Hb < 130 g/L, 4*109/L < WBC ≤ 10*109/L, albumin < 39 g/L, or duration of MAP < 60 mmHg ≥ 5 min. The SII was found to be a useful prognostic predictor of POD for patients of different ages, sexes, and ASA classifications. CONCLUSIONS: The SII had a predictive value for POD in patients undergoing non-neurosurgery and non-cardiac surgery. As an index generated from routine blood tests, the SII has advantages regarding cost and time. After further validation, the SII may provide a new option for POD prediction.

Development and validation of a risk nomogram for postoperative acute kidney injury in older patients undergoing liver resection: a pilot study.

BACKGROUND: Postoperative acute kidney injury (AKI) is associated with poor clinical outcomes. Early identification of high-risk patients of developing postoperative AKI can optimize perioperative renal management and facilitate patient survival. The present study aims to develop and validate a nomogram to predict postoperative AKI after liver resection in older patients. METHODS: A retrospective observational study was conducted involving data from 843 older patients scheduled for liver resection at a single tertiary high caseload general hospital between 2012 and 2019. The data were randomly divided into training (70%, n = 599) and validation (30%, n = 244) datasets. The training cohort was used to construct a predictive nomogram for postoperative AKI with the logistic regression model which was confirmed by a validation cohort. The model was evaluated by receiver operating characteristic (ROC) curve, calibration plot, and decision curve analysis in the validation cohort. A summary risk score was also constructed for identifying postoperative AKI patients. RESULTS: Postoperative AKI occurred in 155 (18.4%) patients and was highly associated with in-hospital mortality (5.2% vs. 0.7%, P <  0.001). The six predictors selected and assembled into the nomogram included age, preexisting chronic kidney disease (CKD), non-steroidal anti-inflammatory drugs (NSAIDs) usage, intraoperative hepatic inflow occlusion, blood loss, and transfusion. The predictive nomogram performed well in terms of discrimination with area under ROC curve (AUC) in training (0.73, 95% confidence interval (CI): 0.68-0.78) and validation (0.71, 95% CI: 0.63-0.80) datasets. The nomogram was well-calibrated with the Hosmer-Lemeshow chi-square value of 9.68 (P = 0.47). Decision curve analysis demonstrated a significant clinical benefit. The summary risk score calculated as the sum of points from the six variables (one point for each variable) performed as well as the nomogram in identifying the risk of AKI (AUC 0.71, 95% CI: 0.66-0.76). CONCLUSION: This nomogram and summary risk score accurately predicted postoperative AKI using six clinically accessible variables, with potential application in facilitating the optimized perioperative renal management in older patients undergoing liver resection. TRIAL REGISTRATION: NCT04922866 , retrospectively registered on clinicaltrials.gov on June 11, 2021.

Targeting Lymphocyte Activation Gene 3 to Reverse T-Lymphocyte Dysfunction and Improve Survival in Murine Polymicrobial Sepsis.

BACKGROUND: Lymphocyte activation gene 3 (LAG-3) is one of the immune checkpoint molecules, negatively regulating the T-cell reactions. The present study investigated the role of LAG-3 in sepsis-induced T-lymphocyte disability. METHODS: Mice sepsis was induced by cecal ligation and puncture (CLP). LAG-3 expression on some immune cells were detected 24 hours after CLP. LAG-3 knockout and anti-LAG-3 antibody were applied to investigate the effects on the survival, bacterial clearance. Cytokine levels, T-cell counts, and the presence of apoptosis (in blood, spleen, and thymus) were also determined. In vitro T-cell apoptosis, interferon γ secretion, and proliferation were measured. The expression of interleukin 2 receptor on T cells was also determined after CLP. RESULTS: LAG-3 was up-regulated on CD4+/CD8+ T, CD19+ B, natural killer, CD4+CD25+ regulatory T cells and dendritic cells. Both LAG-3 knockout and anti-LAG-3 antibody had a positive effect on survival and on blood or peritoneal bacterial clearance in mice undergoing CLP. Cytokine levels and T-cell apoptosis decreased in anti-LAG-3 antibody-treated mice. Induced T-cell apoptosis decreased, whereas interferon γ secretion and proliferation were improved by anti-LAG-3 antibody in vitro. Interleukin 2 receptor was up-regulated on T cells in both wild-type and LAG-3-knockout mice undergoing CLP. CONCLUSIONS: LAG-3 knockout or anti-LAG-3 antibody blockade protected mice undergoing CLP from sepsis-associated immunodysfunction and may be a new target for the treatment.

[Design and Application of Perioperative Multi-center Data Center].

Based on 18 hospitals including the Chinese People's Liberation Army General Hospital and Peking University People's Hospital, and based on the "Specifications for Perioperative Data", explore the construction and application of perioperative multi-center data centers in the era of medical big data. The use of data ferry technology avoids hidden safety hazards in hospitals, realizes the integration and sharing of perioperative medical data of various medical institutions, and forms a complete data chain combining patient medical data and follow-up data.

Cottonseed oil alleviates ischemic stroke injury by inhibiting the inflammatory activation of microglia and astrocyte.

BACKGROUND: Ischemic stroke is the second leading cause of death globally. The narrow time window for administering effective thrombolytic therapy motivates the search for alternative prevention strategies. Microglia and astrocyte activation-mediated inflammation play a pivotal role in ischemic stroke injury. Cottonseed oil (CSO) has been shown to exert anti-inflammatory effects against peripheral tissue injury, although CSO is mostly used as a solvent for lipid-soluble drugs. However, the role of CSO in neuroprotection against stroke has not been previously reported. METHODS: We treated adult male rats with CSO (1.3 ml/kg, subcutaneous injection, once every other day for 3 weeks) and then constructed a middle cerebral artery occlusion (MCAO) model followed by 24 h of reperfusion. Then, we measured the neurological scores, infarction volume, neuronal injury, and brain edema; we also measured the levels of pro-inflammatory cytokines (IL-1ß, IL-6, TNF-α), degree of microglial and astrocytic activation, protein expression levels of Toll-like receptor 4 (TLR4), nuclear factor kappa B (NF-κB), C3d and S100A10, and the presence of A1 type astrocytes and A2 type astrocytes. RESULTS: We found that CSO treatment significantly improved the neurological deficit, reduced infarction volume, and alleviated neuronal injuries, blood-brain barrier (BBB) disruption, and brain edema. Additionally, CSO treatment significantly reduced microglial and astrocytic activation, inhibited TLR4 and NF-κB protein expression, and reduced the release of IL-1ß, IL-6, and TNF-α. Finally, CSO treatment significantly decreased the number of C3d/glial fibrillary acidic protein (GFAP)-positive cells and C3d protein expression, and increased the number of S100A10/GFAP-positive cells and S100A10 protein expression. CONCLUSION: Our results first found that CSO treatment alleviated ischemic stroke injury by reducing microglial and astrocytic activation and inflammation, which was related to the inhibition of TLR4/NF-κB pathway and the reduction of A1 phenotype neurotoxic astrocyte activation, suggesting that CSO could be a new strategy in the prevention of ischemic stroke.

Blockade of IL-17A/IL-17R Pathway Protected Mice from Sepsis-Associated Encephalopathy by Inhibition of Microglia Activation.

Sepsis-associated encephalopathy (SAE) is a poorly understood condition that leads to long-term cognitive impairment and increased mortality in survivors. Recent research revealed that IL-17A/IL-17R might serve as a checkpoint in microglia-mediated neuroinflammation. The present study was designed to determine the specific role of IL-17A-mediated microglia activation in the development of SAE. A mouse model of SAE was induced by cecal ligation and puncture (CLP), and behavior performance was evaluated by the inhibitory avoidance test and the open field test. Cytokine expression and microglia activation in brain tissue were determined at 6 h, 12 h, 24 h, 48 h, and day 7 post surgery. Further, septic mice were intracerebral ventricle- (i.c.v.-) injected with recombinant IL-17A, anti-IL-17A ab, anti-IL-17R ab, or isotype controls to evaluate the potential effects of IL-17A/IL-17R blockade in the prevention of SAE. Septic peritonitis induced significant impairment of learning memory and exploratory activity, which was associated with a higher expression of IL-17A, IL-1ß, and TNF-α in the brain homogenate. Fluorescence intensity of Iba-1 and IL-17R in the hippocampus was significantly increased following CLP. Treatment with recombinant IL-17A enhanced the neuroinflammation and microglia activation in CLP mice. On the contrary, neutralizing anti-IL-17A or anti-IL-17R antibodies mitigated the CNS inflammation and microglia activation, thus alleviating the cognitive dysfunction. Furthermore, as compared to the sham control, microglia cultured from CLP mice produced significantly higher levels of cytokines and expressed with higher fluorescence intensity of Iba-1 in response to IL-17A or LPS. Pretreatment with anti-IL-17R ab suppressed the Iba-1 expression and cytokine production in microglia stimulated by IL-17A. In conclusion, blockade of the IL-17A/IL-17R pathway inhibited microglia activation and neuroinflammation, thereby partially reversing sepsis-induced cognitive impairment. The present study suggested that the IL-17A/IL-17R signaling pathway had an important, nonredundant role in the development of SAE.

Pulse pressure variation shows a direct linear correlation with tidal volume in anesthetized healthy patients.

BACKGROUND: The settings of mechanical ventilation, like tidal volume (VT), occasionally need to be adjusted in the process of anesthesia for some special reasons. The aim of this study was therefore to assess the relationship between pulse pressure variations (PPVs) in different settings of VT in anesthetized healthy patients under mechanical ventilation. METHODS: Sixty nine ASA I-II patients scheduled for gastrointestinal surgery under general anesthesia were included in this prospective study. All the patients were ventilated at a VT of 6, 8 or 10 ml/kg (predicted body weight) with no positive end expiratory pressure (PEEP) in a random order after intubation. PPV, mean arterial blood pressure, and other hemodynamic and respiratory parameters were recorded in each VT setting respectively after Partial Pressure of End-Tidal Expiration Carbon Dioxide (PetCO2) maintained between 30 mmHg and 40 mmHg by changing Respiratory Rate (RR) before incision. RESULTS: The values of PPV at different settings of VT showed a tight correlation between each other (6 vs. 8 ml/kg: r = 0.97, P < 0.0001; 6 vs.10 ml/kg: r = 0.95, P < 0.0001; 8 vs. 10 ml/kg: r = 0.98, P < 0.0001, respectively). CONCLUSION: There is a direct linear correlation between PPVs at different tidal volumes in anesthetized ASA I-II patients. PPV in any of the 3 VT settings (6, 8 or 10 ml/kg) can deduce that in any other 2 settings. Further studies are needed to explore the effect of intraoperative confounders for this knowledge to be clinically applied. TRIAL REGISTRATION: NCT01950949 , www.clinicaltrials.gov , July 26, 2013.

Global trends in research on endothelial cells and sepsis between 2002 and 2022: A systematic bibliometric analysis.

Sepsis is a systemic syndrome involving physiological, pathological, and biochemical abnormalities precipitated by infection and is a major global public health problem. Endothelial cells (ECs) dysfunction is a major contributor to sepsis-induced multiple organ failure. This bibliometric analysis aimed to identify and characterize the status, evolution of the field, and new research trends of ECs and sepsis over the past 20 years. For this analysis, the Web of Science Core Collection database was searched to identify relevant publications on ECs in sepsis published between January 1, 2002, and December 31, 2022. Microsoft Excel 2021, VOSviewer software, CiteSpace software, and the online analysis platform of literature metrology (http://bibliometric.com) were used to visualize the trends of publications' countries/regions, institutions, authors, journals, and keywords. In total, 4200 articles were identified and screened, primarily originating from 86 countries/regions and 3489 institutions. The USA was the leading contributor to this research field, providing 1501 articles (35.74 %). Harvard University's scientists were the most prolific, with 129 articles. Overall, 21,944 authors were identified, among whom Bae Jong Sup was the most prolific, contributing 129 publications. Additionally, Levi Marcel was the most frequently co-cited author, appearing 538 times. The journals that published the most articles were SHOCK, CRITICAL CARE MEDICINE, and PLOS ONE, accounting for 10.79 % of the total. The current emerging hotspots are concentrated on "endothelial glycocalyx," "NLRP3 inflammasome," "extracellular vesicle," "biomarkers," and "COVID-19," among others. In conclusion, this study provides a comprehensive overview of the scientific productivity and emerging research trends in the field of ECs in sepsis. The evidence supporting the significant role of ECs in both physiological and pathological responses to sepsis is continuously growing. More in-depth studies of the molecular mechanisms underlying sepsis-induced endothelial dysfunction and EC-targeted therapies are warranted in the future.

Triglyceride-glucose index-A novel metabolism disorder biomarker as a promising indicator for predicting postoperative 30-day infections in elderly patients undergoing gastrointestinal-related abdominal and pelvic surgery.

BACKGROUND: The triglyceride-glucose index, a reliable surrogate biomarker of insulin resistance, has been reported to be associated with cardiovascular events and atherosclerosis. However, few studies have investigated the association of the triglyceride-glucose index with postoperative infections. This study aimed to study the clinical risk values of the preoperative triglyceride-glucose index in postoperative infection complications in elderly patients undergoing gastrointestinal-related abdominal and pelvic surgery. METHODS: This retrospective cohort study included 3,225 older patients who underwent gastrointestinal-related abdominal and pelvic surgery between 2014 and 2019. The patients were divided into groups of triglyceride-glucose index ≤8.268 and triglyceride-glucose index >8.268 according to the optimal triglyceride-glucose index cut-off value. The outcome of interest was postoperative infections within 30 days after surgery. Primary and subgroup analyses were performed to confirm that preoperative triglyceride-glucose index qualifies as a reliable, independent risk indicator. Propensity score matching analysis was further applied to address covariates' potential residual confounding effect and test the robustness of the results. RESULTS: In this study, the median age was 71 years (interquartile range, 67, 75 years), the proportion of male patients was 66.3%, and 1,058 (32.8%) were infected within 30 days after surgery. A triglyceride-glucose index >8.268 was associated with an increased risk of postoperative infections in multivariate regression analysis (odds ratio, 1.37; 95% confidence interval, 1.15-1.64; P < .001). The correlation between the triglyceride-glucose index and postoperative infections remained significantly robust (odds ratio, 1.52; 95% confidence interval, 1.21-1.92; P < .001) in the propensity score matching analysis. CONCLUSIONS: The triglyceride-glucose index elevation determined by the optimal cutoff value of 8.268 was an independent risk factor for developing postoperative infections.

Development and Validation of an Explainable Machine Learning Model for Predicting Myocardial Injury After Noncardiac Surgery in Two Centers in China: Retrospective Study.

Background: Myocardial injury after noncardiac surgery (MINS) is an easily overlooked complication but closely related to postoperative cardiovascular adverse outcomes; therefore, the early diagnosis and prediction are particularly important. Objective: We aimed to develop and validate an explainable machine learning (ML) model for predicting MINS among older patients undergoing noncardiac surgery. Methods: The retrospective cohort study included older patients who had noncardiac surgery from 1 northern center and 1 southern center in China. The data sets from center 1 were divided into a training set and an internal validation set. The data set from center 2 was used as an external validation set. Before modeling, the least absolute shrinkage and selection operator and recursive feature elimination methods were used to reduce dimensions of data and select key features from all variables. Prediction models were developed based on the extracted features using several ML algorithms, including category boosting, random forest, logistic regression, naïve Bayes, light gradient boosting machine, extreme gradient boosting, support vector machine, and decision tree. Prediction performance was assessed by the area under the receiver operating characteristic (AUROC) curve as the main evaluation metric to select the best algorithms. The model performance was verified by internal and external validation data sets with the best algorithm and compared to the Revised Cardiac Risk Index. The Shapley Additive Explanations (SHAP) method was applied to calculate values for each feature, representing the contribution to the predicted risk of complication, and generate personalized explanations. Results: A total of 19,463 eligible patients were included; among those, 12,464 patients in center 1 were included as the training set; 4754 patients in center 1 were included as the internal validation set; and 2245 in center 2 were included as the external validation set. The best-performing model for prediction was the CatBoost algorithm, achieving the highest AUROC of 0.805 (95% CI 0.778-0.831) in the training set, validating with an AUROC of 0.780 in the internal validation set and 0.70 in external validation set. Additionally, CatBoost demonstrated superior performance compared to the Revised Cardiac Risk Index (AUROC 0.636; P<.001). The SHAP values indicated the ranking of the level of importance of each variable, with preoperative serum creatinine concentration, red blood cell distribution width, and age accounting for the top three. The results from the SHAP method can predict events with positive values or nonevents with negative values, providing an explicit explanation of individualized risk predictions. Conclusions: The ML models can provide a personalized and fairly accurate risk prediction of MINS, and the explainable perspective can help identify potentially modifiable sources of risk at the patient level.

Preoperative serum ferritin as a biomarker for predicting delirium among elderly patients receiving non-cardiac surgery: a retrospective cohort study.

Iron metabolism disorder has been identified as a contributor to the pathogenesis and progression of multiple cognitive dysfunction-related diseases, including postoperative delirium. However, the association between preoperative iron reserves and postoperative delirium risk remains elusive. This retrospective cohort study aimed to explore the impact of preoperative serum ferritin levels on the risk of postoperative delirium in elderly patients undergoing non-neurosurgical and non-cardiac procedures. Conducted at the Chinese PLA General Hospital between January 2014 and December 2021, the study finally included 12,841 patients aged 65 years and above. Preoperative serum ferritin levels were assessed within 30 days before surgery, and postoperative delirium occurrence within the first seven days after surgery was determined through medical chart review. The analyses revealed that both low and high levels of serum ferritin were associated with an increased risk of postoperative delirium. Patients in the lowest quintile of serum ferritin exhibited an 81% increased risk, while those in the highest quintile faced a 91% increased risk compared to those in the second quintile. Furthermore, mediation analyses indicated that the direct effect of preoperative serum ferritin on postoperative delirium contradicted its indirect effect mediated by hemoglobin levels. These findings suggest that maintaining serum ferritin within moderate range preoperatively could be beneficial for managing postoperative delirium risk among elderly patients.

Relationship between preoperative high triglyceride-glucose index and myocardial injury following non-cardiac surgery in advanced-age patients: a retrospective cohort study.

BACKGROUND: Myocardial injury after non-cardiac surgery (MINS) is a common and insidious postoperative complication. This study aimed to evaluate the relationship between the triglyceride-glucose index (TyG) and MINS in advanced-age patients. METHODS: We performed a single-center retrospective study including patients ≥ 65 years of age who underwent non-cardiac surgery. The relationship between TyG and MINS was investigated using univariate and multivariate logistic regression analyses. Multivariate logistic regression analysis involved three models: Model I adjusted for preoperative factors, Model II adjusted for surgery-related factors, and Model III adjusted for both preoperative and surgery-related factors. Propensity score matching (PSM) was used to reduce the confounding effects of covariates. Subgroup analyses were then performed to evaluate the relationship between TyG and MINS in various subsamples. RESULTS: A total of 7789 patients were studied, among whom 481 (6.2%) developed MINS. A cut-off value of TyG of 8.57 was determined using a receiver operating characteristic (ROC) curve to be associated with the best predictive performance. Participants with TyG ≥ 8.57 were at a higher risk of developing MINS than those with TyG < 8.57 [n = 273 (7.6%) vs. n = 208 (4.9%), respectively; p < 0.001]. The univariate analysis showed that TyG ≥ 8.57 was significantly associated with MINS in elderly patients [odds ratio (OR): 1.58; 95% confidence interval (95%CI): 1.32-1.91; p < 0.001)]. In multivariate logistic regression, adjustments were made for risk factors including age, sex, body mass index (BMI), hypertension, coronary heart disease, and duration of surgery, etc. The adjusted ORs for TyG ≥ 8.57 were 1.46 (95%CI: 1.17-1.82), p = 0.001; 1.46 (95%CI: 1.19-1.77), p < 0.001; and 1.43 (95%CI: 1.13-1.81), p = 0.003, in the three multivariate models, respectively. The relationship remained after PSM (adjusted OR: 1.35, 95% CI: 1.03-1.78, p = 0.029). Furthermore, the relationship between TyG and MINS remained in a number of subgroups in the sensitivity analyses, but not in participants with peripheral vascular stenosis. CONCLUSIONS: A preoperative high TyG (≥ 8.57) is associated with a higher risk of MINS in advanced-age patients undergoing non-cardiac surgery.

Preoperative prognostic nutritional index predicts postoperative delirium in aged patients after surgery: A matched cohort study.

OBJECTIVE: Prognostic nutritional index (PNI) is an indicator to evaluate the nutritional immune status of patients. This study aimed to assess whether preoperative PNI could predict the occurrence of postoperative POD in aged patients undergoing non-neurosurgery and non-cardiac surgery. METHOD: The aged patients undergoing non-neurosurgery and non-cardiac surgery between January 2014 and August 2019 were included in the retrospective cohort study. The correlation between POD and PNI was investigated by univariate and multivariable logistic regression analysis, propensity score matching (PSM), inverse probability of treatment weighting (IPTW), and subgroup analysis. RESULTS: In the cohort (n = 29,814), the cutoff value of PNI was 46.01 determined by the receiver operating characteristic (ROC) curve. In univariate and three multivariable regression analysis, the ORs of PNI ≤ 46.01 was 2.573(95% CI:2.261-2.929, P < 0.001),1.802 (95% CI:1.567-2.071, P < 0.001),1.463(95% CI:1.246-1.718, P < 0.001),1.370(95% CI:1.165-1.611, P < 0.001). In the PSM model and IPTW model, the ORs of PNI ≤ 46.01 were 1.424(95% CI:1.172-1.734, P < 0.001) and 1.356(95% CI:1.223-1.505, P < 0.001). CONCLUSION: The PNI was found to have a predictive value for POD in patients undergoing non-neurosurgery and non-cardiac surgery. Improving preoperative nutritional status may be beneficial in preventing POD for aged patients.

Development and validation of a nomogram to predict postoperative delirium in older patients after major abdominal surgery: a retrospective case-control study.

BACKGROUND: Postoperative delirium is a common complication in older patients, with poor long-term outcomes. This study aimed to investigate risk factors and develop a predictive model for postoperative delirium in older patients after major abdominal surgery. METHODS: This study retrospectively recruited 7577 patients aged ≥ 65 years who underwent major abdominal surgery between January 2014 and December 2018 in a single hospital in Beijing, China. Patients were divided into a training cohort (n = 5303) and a validation cohort (n = 2224) for univariate and multivariate logistic regression analyses and to build a nomogram. Data were collected for 43 perioperative variables, including demographics, medical history, preoperative laboratory results, imaging, and anesthesia information. RESULTS: Age, chronic obstructive pulmonary disease, white blood cell count, glucose, total protein, creatinine, emergency surgery, and anesthesia time were associated with postoperative delirium in multivariate analysis. We developed a nomogram based on the above 8 variables. The nomogram achieved areas under the curve of 0.731 and 0.735 for the training and validation cohorts, respectively. The discriminatory ability of the nomogram was further assessed by dividing the cases into three risk groups (low-risk, nomogram score < 175; medium-risk, nomogram score 175~199; high-risk, nomogram score > 199; P < 0.001). Decision curve analysis revealed that the nomogram provided a good net clinical benefit. CONCLUSIONS: We developed a nomogram that could predict postoperative delirium with high accuracy and stability in older patients after major abdominal surgery.

Risk factors prediction of 6-month mortality after noncardiac surgery of older patients in China: a multicentre retrospective cohort study.

BACKGROUND: Identifying the risk factors associated with perioperative mortality is crucial, particularly in older patients. Predicting 6-month mortality risk in older patients based on large datasets can assist patients and surgeons in perioperative clinical decision-making. This study aimed to develop a risk prediction model of mortality within 6 months after noncardiac surgery using the clinical data from 11 894 older patients in China. MATERIALS AND METHODS: A multicentre, retrospective cohort study was conducted in 20 tertiary hospitals. The authors retrospectively included 11 894 patients (aged ≥65 years) who underwent noncardiac surgery between April 2020 and April 2022. The least absolute shrinkage and selection operator model based on linear regression was used to analyse and select risk factors, and various machine learning methods were used to build predictive models of 6-month mortality. RESULTS: The authors predicted 12 preoperative risk factors associated with 6-month mortality in older patients after noncardiac surgery. Including laboratory-associated risk factors such as mononuclear cell ratio and total blood cholesterol level, etc. Also including medical history associated risk factors such as stroke, history of chronic diseases, etc. By using a random forest model, the authors constructed a predictive model with a satisfactory accuracy (area under the receiver operating characteristic curve=0.97). CONCLUSION: The authors identified 12 preoperative risk factors associated with 6-month mortality in noncardiac surgery older patients. These preoperative risk factors may provide evidence for a comprehensive preoperative anaesthesia assessment as well as necessary information for clinical decision-making by anaesthesiologists.

Development and validation of a prediction model to predict major adverse cardiovascular events in elderly patients undergoing noncardiac surgery: A retrospective cohort study.

BACKGROUND AND AIMS: Current existing predictive tools have limitations in predicting major adverse cardiovascular events (MACEs) in elderly patients. We will build a new prediction model to predict MACEs in elderly patients undergoing noncardiac surgery by using traditional statistical methods and machine learning algorithms. METHODS: MACEs were defined as acute myocardial infarction (AMI), ischemic stroke, heart failure and death within 30 days after surgery. Clinical data from 45,102 elderly patients (≥65 years old), who underwent noncardiac surgery from two independent cohorts, were used to develop and validate the prediction models. A traditional logistic regression and five machine learning models (decision tree, random forest, LGBM, AdaBoost, and XGBoost) were compared by the area under the receiver operating characteristic curve (AUC). In the traditional prediction model, the calibration was assessed using the calibration curve and the patients' net benefit was measured by decision curve analysis (DCA). RESULTS: Among 45,102 elderly patients, 346 (0.76%) developed MACEs. The AUC of this traditional model was 0.800 (95% CI, 0.708-0.831) in the internal validation set, and 0.768 (95% CI, 0.702-0.835) in the external validation set. In the best machine learning prediction model-AdaBoost model, the AUC in the internal and external validation set was 0.778 and 0.732, respectively. Besides, for the traditional prediction model, the calibration curve of model performance accurately predicted the risk of MACEs (Hosmer and Lemeshow, p = 0.573), the DCA results showed that the nomogram had a high net benefit for predicting postoperative MACEs. CONCLUSIONS: This prediction model based on the traditional method could accurately predict the risk of MACEs after noncardiac surgery in elderly patients.