Effect of preoperative moderate-dose statin and duration on acute kidney injury after cardiac surgery: a retrospective cohort study.

BACKGROUND: The impact of preoperative statin use on postoperative acute kidney injury (AKI) is uncertain. We aimed to examine the association of statin therapy before cardiac surgery with postoperative AKI. METHODS: The retrospective cohort study consisted of 1581 patients undergoing cardiac surgery. Postoperative AKI were identified by the modified KDIGO definition. Propensity-score matching was employed to control for selection bias, and logistic regression was used to control for confounders. Subgroup and interaction analyses were performed to evaluate the robustness of the findings. RESULTS: The overall incidence of postoperative AKI and severe AKI were 42.19% and 12.27%, respectively. Preoperative moderate-dose statin was significantly associated with a reduced incidence of postoperative AKI (28.9% vs 43.0%, OR (95%CI): 0.54 (0.38, 0.77), p < 0.001) and severe AKI (6.9% vs 13.7%, OR (95%CI): 0.46 (0.26, 0.83), p = 0.009). The beneficial effect on postoperative AKI persisted after adjusting for major confounding factors (OR (95%CI): 0.47 (0.34, 0.66)). Decreased risk of postoperative AKI was observed in patients with preoperative statin duration of 7 ∼ 14 days (OR (95%CI): 0.41 (0.25, 0.65)) and over 14 days (OR (95%CI): 0.43 (0.28, 0.65)), but not in those with preoperative statin duration of <7 days. Similar favorable effects were noted in most subgroup patients, except for those with high-risk factors such as diabetes mellitus, previous congestive cardiac failure, arrhythmia, preoperative ACEI/ARB, aortic cross-clamping or IABP. CONCLUSION: Preoperative moderate-dose statin was significantly related to a decreased risk of postoperative AKI, especially in patients who received statins for a longer duration. Further large-scale multicenter randomized controlled trials are needed to ascertain the impact of statin dose, duration, and timing on postoperative AKI in cardiac surgery patients.

Interpretable machine learning models for early prediction of acute kidney injury after cardiac surgery.

OBJECTIVE: Postoperative acute kidney injury (PO-AKI) is a common complication after cardiac surgery. We aimed to evaluate whether machine learning algorithms could significantly improve the risk prediction of PO-AKI. METHODS: The retrospective cohort study included 2310 adult patients undergoing cardiac surgery in a tertiary teaching hospital, China. Postoperative AKI and severe AKI were identified by the modified KDIGO definition. The sample was randomly divided into a derivation set and a validation set based on a ratio of 4:1. Exploiting conventional logistic regression (LR) and five ML algorithms including decision tree, random forest, gradient boosting classifier (GBC), Gaussian Naive Bayes and multilayer perceptron, we developed and validated the prediction models of PO-AKI. We implemented the interpretation of models using SHapley Additive exPlanation (SHAP) analysis. RESULTS: Postoperative AKI and severe AKI occurred in 1020 (44.2%) and 286 (12.4%) patients, respectively. Compared with the five ML models, LR model for PO-AKI exhibited the largest AUC (0.812, 95%CI: 0.756, 0.860, all P < 0.05), sensitivity (0.774, 95%CI: 0.719, 0.813), accuracy (0.753, 95%CI: 0.719, 0.781) and Youden index (0.513, 95%CI: 0.451, 0.573). Regarding severe AKI, GBC algorithm showed a significantly higher AUC than the other four ML models (all P < 0.05). Although no significant difference (P = 0.173) was observed in AUCs between GBC (0.86, 95%CI: 0.808, 0.902) and conventional logistic regression (0.803, 95%CI: 0.746, 0.852), GBC achieved greater sensitivity, accuracy and Youden index than conventional LR. Notably, SHAP analyses showed that preoperative serum creatinine, hyperlipidemia, lipid-lowering agents and assisted ventilation time were consistently among the top five important predictors for both postoperative AKI and severe AKI. CONCLUSION: Logistic regression and GBC algorithm demonstrated moderate to good discrimination and superior performance in predicting PO-AKI and severe AKI, respectively. Interpretation of the models identified the key contributors to the predictions, which could potentially inform clinical interventions.

Prevalence and management of hypertension in Central China: a cross-sectional survey.

OBJECTIVE: We aimed to assess hypertension prevalence and management in Central China. METHODS: In this cross-sectional study conducted from February 2019 to February 2020, we applied stratified multistage random sampling to investigate residents aged 35 to 75 years in Dancheng county of Zhoukou city and Xincai county of Zhumadian city, both in Central China. RESULTS: We enrolled 63,940 participants in this survey. A total of 43.6% (95% confidence interval [CI]: 43.2-44.0) of participants had hypertension. Of these, 49.3% (95% CI: 48.7-49.9) were aware of their diagnosis, 36.5% (95% CI: 35.9-37.1) took antihypertensive medication, and 14.3% (95% CI: 13.9-14.7) had their blood pressure under control. Only 31.4% of hypertensive people receiving antihypertensive treatment had achieved control. The hypertension prevalence was lower in urban areas than in rural areas, with higher rates of awareness, treatment, and control. Among subgroups, rural men had the highest prevalence of hypertension. Prevalence, awareness, and treatment rates all increased with age, except for control rates, which declined in the 65- to 75-year-old group. CONCLUSIONS: People in Central China have a high hypertension prevalence but low rates of awareness, treatment, and control. Great effort is needed to improve the prevention and management of hypertension in this region.

Prediction of all-cause mortality in coronary artery disease patients with atrial fibrillation based on machine learning models.

BACKGROUND: Machine learning (ML) can include more diverse and more complex variables to construct models. This study aimed to develop models based on ML methods to predict the all-cause mortality in coronary artery disease (CAD) patients with atrial fibrillation (AF). METHODS: A total of 2037 CAD patients with AF were included in this study. Three ML methods were used, including the regularization logistic regression, random forest, and support vector machines. The fivefold cross-validation was used to evaluate model performance. The performance was quantified by calculating the area under the curve (AUC) with 95% confidence intervals (CI), sensitivity, specificity, and accuracy. RESULTS: After univariate analysis, 24 variables with statistical differences were included into the models. The AUC of regularization logistic regression model, random forest model, and support vector machines model was 0.732 (95% CI 0.649-0.816), 0.728 (95% CI 0.642-0.813), and 0.712 (95% CI 0.630-0.794), respectively. The regularization logistic regression model presented the highest AUC value (0.732 vs 0.728 vs 0.712), specificity (0.699 vs 0.663 vs 0.668), and accuracy (0.936 vs 0.935 vs 0.935) among the three models. However, no statistical differences were observed in the receiver operating characteristic (ROC) curve of the three models (all P > 0.05). CONCLUSION: Combining the performance of all aspects of the models, the regularization logistic regression model was recommended to be used in clinical practice.

Antithrombotic therapy in coronary artery disease patients with atrial fibrillation.

BACKGROUND: Coronary artery disease (CAD) and atrial fibrillation (AF) frequently coexist in clinical practice, making it challenging for the treating physician to choose anticoagulation and antiplatelet therapies. The aim of this study was to investigate antithrombotic strategies and assess related adverse outcomes in stable coronary artery disease (SCAD) and acute coronary syndrome (ACS) patients with AF when the CHA2DS2-VASc score was ≥2. METHODS: We performed a retrospective study and collected data from a computer-based patient record management system in Zhengzhou University People's Hospital in China. In total, 2978 patients with a hospital discharge diagnosis of CAD and concomitant AF who met the inclusion criteria were enrolled from January 1, 2012 to December 31, 2016, and data from 2050 patients were finally analysed. The χ2 test was used to compare the incidences of clinical endpoints between the SCAD+AF group and the ACS + AF group. Multivariable Cox regression analysis was performed to identify independent predictive factors of adverse outcomes in both groups. RESULTS: Oral anticoagulant (OAC) monotherapy was the most common antithrombotic therapy in SCAD+AF patients (49.55%), while double antiplatelet therapy (DAPT) was the most common treatment in ACS + AF patients (54.19%) at discharge. OAC monotherapy significantly increased and the use of single antiplatelet therapy (SAPT) decreased during follow-up (34 ± 13 months) when compared to their use at discharge in the SCAD+AF group (all p < 0.001). In the ACS + AF group, the proportion of patients using DAPT decreased notably, while the proportions of patients using SAPT and dual therapy (DT) combining OAC with SAPT increased significantly during follow-up (all p < 0.001) compared to the proportions at discharge. According to multivariable Cox regression analysis, age, hypertension and prior stroke were independent risk factors for ischaemic stroke in the SCAD+AF group and ACS + AF group (all p < 0.05). OAC was an independent protective factor for ischaemic stroke in both groups (all p < 0.05). Previous bleeding independently increased the risk of haemorrhage in both groups (all p < 0.01). CONCLUSIONS: In this study, the proportion of anticoagulant-antiplatelet combined therapy was low in ACS + AF patients with high stroke risk. In clinical practice, the awareness of anticoagulation needs to be strengthened regarding patients with CAD and AF.

Inhibitory Effect of Vascular Endothelial Growth Factor on the Slowly Activating Delayed Rectifier Potassium Current in Guinea Pig Ventricular Myocytes.

BACKGROUND: Vascular endothelial growth factor (VEGF) exerts a number of beneficial effects on ischemic myocardium via its angiogenic properties. However, little is known about whether VEGF has a direct effect on the electrical properties of cardiomyocytes. In the present study, we investigated the effects of different concentrations of VEGF on delayed rectifier potassium currents (IK) in guinea pig ventricular myocytes and their effects on action potential (AP) parameters. METHODS AND RESULTS: IK and AP were recorded by the whole-cell patch clamp method in ventricular myocytes. Cells were superfused with control solution or solution containing VEGF at different concentrations for 10 minutes before recording. Some ventricular myocytes were pretreated with a phosphatidylinositol 3-kinase inhibitor for 1 hour before the addition of VEGF. We found that VEGF inhibited the slowly activating delayed rectifier potassium current (IKs) in a concentration-dependent manner (18.13±1.04 versus 12.73±0.34, n=5, P=0.001; 12.73±0.34 versus 9.05±1.20, n=5, P=0.036) and prolonged AP duration (894.5±36.92 versus 746.3±33.71, n=5, P=0.021). Wortmannin, a phosphatidylinositol 3-kinase inhibitor, eliminated these VEGF-induced effects. VEGF had no significant effect on the rapidly activating delayed rectifier potassium current (IKr), resting membrane potential, AP amplitude, or maximal velocity of depolarization. CONCLUSIONS: VEGF inhibited IKs in a concentration-dependent manner through a phosphatidylinositol 3-kinase-mediated signaling pathway, leading to AP prolongation. The results indicate a promising therapeutic potential of VEGF in prevention of ventricular tachyarrhythmias under conditions of high sympathetic activity and ischemia.

Enhanced effect of VEGF165 on L-type calcium currents in guinea-pig cardiac ventricular myocytes.

The mechanisms of vascular endothelial growth factor 165 (VEGF165) on electrical properties of cardiomyocytes have not been fully elucidated. The aim of this study is to test the hypothesis that VEGF165, an angiogenesis-initiating factor, affects L-type calcium currents (ICa,L) and cell membrane potential in cardiac myocytes by acting on VEGF type-2 receptors (VEGFR2). ICa,L and action potentials (AP) were recorded by the whole-cell patch clamp method in isolated guinea-pig ventricular myocytes treated with different concentrations of VEGF165 proteins. Using a VEGFR2 inhibitor, we also tested the receptor of VEGF165 in cardiomyocytes. We found that VEGF165 increased ICa,L in a concentration-dependent manner. SU5416, a VEGFR2 inhibitor, almost completely eliminated VEGF165-induced ICa,L increase. VEGF165 had no significant influence on action potential 90 (APD90) and other properties of AP. We conclude that in guinea-pig ventricular myocytes, ICa,L can be increased by VEGF165 in a concentration-dependent manner through binding to VEGFR2 without causing any significant alteration to action potential duration. Results of this study may further expound the safety of VEGF165 when used in the intervention of heart diseases.