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The use of hydroxyethyl starch 130/0.4 has been linked to renal injury in critically ill patients, but its impact on surgical patients remains uncertain. A retrospective cohort study. This study was conducted at one tertiary care hospital in China. We evaluated the records of 51,926 Chinese adults who underwent noncardiac surgery from 2013 to 2022. Patients given a combination of hydroxyethyl starch 130/0.4 and crystalloids were propensity-matched at a 1: 1 ratio of baseline characteristics to patients given only crystalloids (11,725 pairs). Eligible patients were divided into those given a combination of hydroxyethyl starch 130/0.4 and crystalloid during surgery and a reference crystalloid group consisting of patients who were not given any colloid. The primary outcome was the incidence of acute kidney injury. Secondarily, acute kidney injury stage, need for renal replacement therapy, intensive care unit transfer rate, and duration of postoperative hospitalization were considered. After matching, hydroxyethyl starch use [8.5 (IQR: 7.5–10.0) mL/kg] did not increase the incidence of acute kidney injury compared with that in the crystalloid group [2.0 vs. 2.2%, OR: 0.90 (0.74–1.08), P = 0.25]. Nor did hydroxyethyl starch use worsen acute kidney injury stage [OR 0.90 (0.75–1.08), P = 0.26]. No significant differences between the fluid groups were observed in renal replacement therapy [OR 0.60 (0.41–0.90), P = 0.02)] or intensive care unit transfers [OR 1.02 (0.95–1.09), P = 0.53] after Bonferroni correction. Even in a subset of patients at high risk of renal injury, hydroxyethyl starch use was not associated with worse outcomes. Hydroxyethyl starch 130/0.4 use was not significantly associated with a greater incidence of postoperative acute kidney injury compared to receiving crystalloid solutions only. • Hydroxyethyl starch 130/0.4 use was not associated with postoperative acute kidney injury. • Postoperative hospitalization slightly longer in hydroxyethyl starch group by median 0.5 days. • No significant difference was found in RRT incidence or ICU transfers. [ABSTRACT FROM AUTHOR]

Background: There has been a concerning rise in the incidence of major adverse cardiovascular and cerebrovascular events (MACCE) following noncardiac surgeries (NCS), significantly impacting surgical outcomes and patient prognosis. Glucose metabolism abnormalities induced by stress response under acute medical conditions may be a risk factor for postoperative MACCE. This study aims to explore the association between stress hyperglycemia ratio (SHR) and postoperative MACCE in patients undergoing general anesthesia for NCS., Methods: There were 12,899 patients in this perioperative cohort study. The primary outcome was MACCE within 30 days postoperatively, defined as angina, acute myocardial infarction, cardiac arrest, arrhythmia, heart failure, stroke, or in-hospital all-cause mortality. Kaplan-Meier curves visualized the cumulative incidence of MACCE. Cox proportional hazard models were utilized to assess the association between the risk of MACCE and different SHR groups. Restricted cubic spline analyses were conducted to explore potential nonlinear relationships. Additionally, exploratory subgroup analyses and sensitivity analyses were performed., Results: A total of 592 (4.59%) participants experienced MACCE within 30 days after surgery, and 1,045 (8.10%) within 90 days. After adjusting for confounding factors, compared to the SHR T2 group, the risk of MACCE within 30 days after surgery increased by 1.34 times (95% CI 1.08-1.66) in the T3 group and by 1.35 times (95% CI 1.08-1.68) in the T1 group respectively. In the non-diabetes group, the risk of MACCE within 30 days after surgery increased by 1.60 times (95% CI 1.21-2.12) in the T3 group and by 1.61 times (95% CI 1.21-2.14) in the T1 group respectively, while no statistically significant increase in risk was observed in the diabetes group. Similar results were observed within 90 days after surgery in the non-diabetes group. Additionally, a statistically significant U-shaped nonlinear relationship was observed in the non-diabetes group (30 days: P for nonlinear = 0.010; 90 days: P for nonlinear = 0.008)., Conclusion: In this large perioperative cohort study, we observed that both higher and lower SHR were associated with an increased risk of MACCE within 30 and 90 days after NCS, especially in patients without diabetes. These findings suggest that SHR potentially plays a key role in stratifying cardiovascular and cerebrovascular risk after NCS., (© 2024. The Author(s).)

Purpose: Guidelines have not recommended routine transthoracic echocardiography (TTE) for elderly patients prior to noncardiac surgery. We aimed to evaluate the significance of preoperative TTE to predict perioperative cardiac complications (PCCs) for elderly patients with coronary artery disease (CAD) undergoing noncardiac surgery. Patients and methods: We retrospectively reviewed 2204 patients over 65 years of age with CAD who underwent TTE before intermediate- or high-risk noncardiac surgery in a teaching hospital in China between September 2013 and August 2019. The revised cardiac risk index (RCRI) was assessed. PCCs comprised acute coronary syndrome, heart failure, new-onset severe arrhythmia, nonfatal cardiac arrest, and cardiac death. Logistic regression was used to build the prediction model for PCCs. Discrimination was evaluated using receiver operating characteristic curves, and a nomogram of the predictive model was constructed. Results: PCCs occurred in 189 (8.6%) patients. Multivariable analysis showed that eight clinical risk factors (age, history of myocardial infarction, insulin therapy for diabetes, New York Heart Association classification, preoperative serum creatinine, preoperative electrocardiogram ST-T abnormality and pathological Q wave, and American Society of Anesthesiologists classification) and five TTE parameters (left atrial anteroposterior dimension, left ventricular ejection fraction, left ventricular diastolic dysfunction, pulmonary hypertension, and regional ventricular wall motion abnormality) were associated with PCCs. The receiver operating characteristic curve for the clinical plus TTE model provided better discrimination for PCCs compared with the RCRI model (area under the curve: 0.731 vs 0.564; P < 0.001) and the clinical model (area under the curve: 0.731 vs 0.697, P = 0.001), respectively. The clinical plus TTE model was presented as a prognostic nomogram. Conclusion: Preoperative TTE may help predict PCCs in elderly patients with CAD undergoing noncardiac surgery, and the prognostic nomogram from this study appeared to be useful for the assessment of perioperative cardiac risk. [ABSTRACT FROM AUTHOR]

Background: Acute kidney injury (AKI) is one of the most common postoperative complications in noncardiac surgical patients, has an important impact on prognosis and is difficult to predict. Whether preoperative N-terminal pro-brain natriuretic peptide (NT-proBNP) concentrations and left ventricular ejection fraction (LVEF) levels can predict postoperative AKI in noncardiac surgical patients is unclear. Methods: We included 3,314 patients who underwent noncardiac surgery and had measurements of preoperative NT-proBNP concentrations and LVEF levels at a tertiary academic hospital in China between 2008 and 2018. Multiple logistic regression analysis was used to construct a postoperative AKI risk prediction model for this cohort. Then, NT-proBNP concentrations and LVEF levels were included in the abovementioned model as independent variables, and the predictive ability of these two models was compared. Results: Postoperative AKI occurred in 223 (6.72%) patients within 1 week after surgery. Preoperative NT-proBNP concentrations and LVEF levels were independent predictors of AKI after adjustment for clinical variables. The area under the receiver operating characteristic curve (AUROC) of the AKI risk predictive model established with clinical baseline variables was 0.767 (95% CI: 0.732, 0.802). When NT-proBNP concentrations and LVEF levels were added to the base model, the AUROC was 0.811 (95% CI: 0.779, 0.843). The addition of NT-proBNP concentrations and LVEF levels improved reclassification by 22.9% (95% CI 10.5–34.4%) for patients who developed postoperative AKI and by 36.3% (95% CI 29.5–43.9%) for those who did not, resulting in a significant overall improvement in net reclassification (NRI: 0.591, 95% CI 0.437–0.752, P < 0.000). The integral discrimination improvement was 0.100 (95% CI: 0.075, 0.125, P < 0.000).The final postoperative AKI prediction model was constructed, and had a good discriminative ability and fitted to the dataset. Conclusions: Preoperative NT-proBNP concentrations and LVEF levels were independently associated with the risk of AKI after noncardiac surgery, and they could improve the predictive ability of logistic regression models based on conventional clinical risk factors. Trial registration: The protocol was preregistered in the Chinese Clinical Trial Registry (ChiCTR1900024056). [ABSTRACT FROM AUTHOR]

To determine the sex-specific associations between postoperative haemoglobin and mortality or complications reflecting ischaemia or inadequate oxygen supply after major noncardiac surgery. A retrospective cohort study with prospective validation. A large university hospital health system in China. Men and women undergoing elective major noncardiac surgery. The primary exposure was nadir haemoglobin within 48 h after surgery. The outcome of interest was a composite of postoperative mortality or ischaemic events including myocardial injury, acute kidney injury and stroke within hospitalisation. The study included 26,049 patients (15,757 men and 10,292 women). Low postoperative haemoglobin was a strong predictor of the composite outcome in both sexes, with the risk progressively increasing as the nadir haemoglobin concentration dropped below 130 g l−1 in men and 120 g l−1 in women (adjusted odds ratio [OR] 1.43, 95% CI 1.37–1.50 in men, and OR 1.45, 95% CI 1.35–1.55 in women, per 10 g l−1 decrease in postoperative nadir haemoglobin). Above these sex-specific thresholds, the change of nadir haemoglobin was no longer associated with odds of the composite outcome in either men or women. There was no significant interaction between patient sex and the association between postoperative haemoglobin and the composite outcome (P interaction = 0.673). Validation in an external prospective cohort (n = 2120) with systematic postoperative troponin and creatinine measurement confirmed our findings. Postoperative haemoglobin levels following major noncardiac surgery were nonlinearly associated with ischaemic complications or mortality, without any clinically important interaction with patient sex. • Low postoperative haemoglobin was a strong predictor for ischaemic organ injury. • The association between postoperative haemoglobin and outcomes was nonlinear. • Sex did not modify the association between postoperative haemoglobin and outcomes. [ABSTRACT FROM AUTHOR]

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., (© Chang Liu, Kai Zhang, Xiaodong Yang, Bingbing Meng, Jingsheng Lou, Yanhong Liu, Jiangbei Cao, Kexuan Liu, Weidong Mi, Hao Li. Originally published in JMIR Aging (https://aging.jmir.org).)

Background: Perioperative myocardial injury/infarction (PMI) following noncardiac surgery is a frequent cardiac complication. This study aims to evaluate PMI risk and explore preoperative assessment tools of PMI in patients at increased cardiovascular (CV) risk who underwent noncardiac surgery under the surgical and medical co-management (SMC) model., Methods: A prospective cohort study that included consecutive patients at increased CV risk who underwent intermediate- or high-risk noncardiac surgery at the Second Medical Center, Chinese PLA General Hospital, between January 2017 and December 2022. All patients were treated with perioperative management by the SMC team. The SMC model was initiated when surgical intervention was indicated and throughout the entire perioperative period. The incidence, risk factors, and impact of PMI on 30-day mortality were analyzed. The ability of the Revised Cardiac Risk Index (RCRI), frailty, and their combination to predict PMI was evaluated., Results: 613 eligible patients (mean [standard deviation, SD] age 73.3[10.9] years, 94.6% male) were recruited consecutively. Under SMC, PMI occurred in 24/613 patients (3.9%). Patients with PMI had a higher rate of 30-day mortality than patients without PMI (29.2% vs. 0.7%, p = 0.00). The FRAIL Scale for frailty was independently associated with an increased risk for PMI (odds ratio = 5.91; 95% confidence interval [CI], 2.34-14.93; p = 0.00). The RCRI demonstrated adequate discriminatory capacity for predicting PMI (area under the curve [AUC], 0.78; 95% CI, 0.67-0.88). Combining frailty with the RCRI further increased the accuracy of predicting PMI (AUC, 0.87; 95% CI, 0.81-0.93)., Conclusions: The incidence of PMI was relatively low in high CV risk patients undergoing intermediate- or high-risk noncardiac surgery under SMC. The RCRI adequately predicted PMI. Combining frailty with the RCRI further increased the accuracy of PMI predictions, achieving excellent discriminatory capacity. These findings may aid personalized evaluation and management of high-risk patients who undergo intermediate- or high-risk noncardiac surgery., (© 2024. The Author(s).)

Perioperative neurocognitive disorders (PNDs) refer to cognitive decline identified in the preoperative or postoperative period. It has been reported that the incidence of postoperative neurocognitive impairment after noncardiac surgery in patients older than 65 at 1 week was 25.8∼41.4%, and at 3 months 9.9∼12.7%. PNDs will last months or even develop to permanent dementia, leading to prolonged hospital stays, reduced quality of life, and increased mortality within 1 year. Despite the high incidence and poor prognosis of PNDs in the aged population, no effective clinical prediction model has been established to predict postoperative cognitive decline preoperatively. To develop a clinical prediction model for postoperative neurocognitive dysfunction, a prospective observational study (Clinical trial registration number: ChiCTR2000036304) will be performed in the Shanghai General Hospital during January 2021 to October 2022. A sample size of 675 patients aged >65 years old, male or female, and scheduled for elective major noncardiac surgery will be recruited. A battery of neuropsychological tests will be used to test the cognitive function of patients at 1 week, 1 month, and 3 months postoperatively. We will evaluate the associations of PNDs with a bunch of candidate predictors including general characteristics of patients, blood biomarkers, indices associated with anesthesia and surgery, retinal nerve-fiber layer thickness, and frailty index to develop the clinical prediction model by using multiple logistic regression analysis and least absolute shrinkage and the selection operator (LASSO) method. The k-fold cross-validation method will be utilized to validate the clinical prediction model. In conclusion, this study was aimed to develop a clinical prediction model for postoperative cognitive dysfunction of old patients. It is anticipated that the knowledge gained from this study will facilitate clinical decision-making for anesthetists and surgeons managing the aged patients undergoing noncardiac surgery., (© 2021 S. Karger AG, Basel.)

Background: Abnormal High-density Lipoprotein Cholesterol Concentration is closely related to postoperative acute kidney injury (AKI) after cardiac surgeries. The purpose of this study was to analyze the relationship between High-density Lipoprotein Cholesterol Concentration and acute kidney injury after non-cardiac surgeries., Method: This was a single-center cohort study for elective non-cardiac non-kidney surgery from January 1, 2012, to December 31, 2017. The endpoint was the occurrence of acute kidney injury (AKI) 7 days postoperatively in the hospital. Preoperative serum High-density Lipoprotein Cholesterol Concentration was examined by multivariate logistic regression models before and after propensity score weighting analysis., Results: Of the 74,284 surgeries, 4.4% (3159 cases) suffered acute kidney injury. The odds ratio for HDL (0.96-1.14 as reference, < 0.96, 1.14-1.35, > 1.35) was 1.28 (1.14-1.41), P < 0.001; 0.91 (0.80-1.03), P = 0.150; 0.75 (0.64-0.85), P < 0.001, respectively. Using a dichotomized cutoff point for propensity analysis, Preoperative serum HDL <  1.03 mmol/L (> 1.03 as reference) was associated with increased risk of postoperative AKI, with odds ratio 1.40 (1.27 ~ 1.52), P < 0.001 before propensity score weighting, and 1.32 (1.21-1.46), P < 0.001 after propensity score weighting. Sensitivity analysis with other cut values of HDL showed similar results., Conclusions: Using multivariate regression analyses before and after propensity score weighting, in addition to multiple sensitivity analysis methods, this study found that following non-cardiac surgery, low HDL cholesterol levels were independent risk factors for AKI.

Objectives: To determine whether preoperative endothelial dysfunction provides risk stratification for perioperative renal injury in patients undergoing noncardiac surgery. The relationship between perioperative renal injury and myocardial injury after noncardiac surgery (MINS) was explored secondarily., Design: An observational study., Setting: Two academic medical centers., Participants: A total of 218 patients scheduled to undergo intermediate or high-risk noncardiac surgery., Interventions: None., Measurements and Main Results: Endothelial dysfunction was identified preoperatively by a Reactive Hyperemia-Peripheral Arterial Tonometry (RH-PAT) index. Renal injury was defined by peak delta serum creatinine (ΔSCr) or creatinine-based kidney disease: Improving global outcomes acute kidney injury (AKI) criteria within 7 days postoperatively. MINS was defined by peak troponin ≥0.04 µg/L within 3 days postoperatively. AKI occurred in 22 patients (10.1%). Median RH-PAT index within the study cohort was 1.64 (range 1.03-4.96) and did not differ between patients with or without AKI. When adjusted for covariates, there was no association between RH-PAT index and either AKI or peak ΔSCr. MINS occurred in 32 patients (14.7%) and was associated independently with the outcome of AKI (odds ratio [OR], 3.7; 95% confidence interval [CI], 1.2-10.8; p = 0.02) and peak ΔSCr (β-regression coefficient 23; 95% CI, 9-37; p = 0.002). Co-occurrence of AKI and MINS portended a marked increase in 30-day mortality (OR, 43; 95% CI, 6-305; p = 0.001) and delayed time to discharge (hazard ratio, 0.27; 95% CI, 0.13-0.54; p = 0.001)., Conclusions: For patients undergoing noncardiac surgery, preoperative endothelial function assessed by noninvasive peripheral arterial tonometry was not associated with perioperative AKI. Perioperative renal injury was associated strongly with MINS, and this may represent a mechanism by which AKI increases adverse outcomes., (Crown Copyright © 2015. Published by Elsevier Inc. All rights reserved.)