Dataset Information

Effects of Preoperative Statin on Acute Kidney Injury After Off-Pump Coronary Artery Bypass Grafting.

ABSTRACT: Background Although many patients with coronary artery disease are using statins before off-pump coronary artery bypass grafting ( OPCAB ) following current guidelines, recent studies have raised concerns regarding adverse effects of preoperative statins on postoperative kidney function. We evaluated the effects of preoperative statins on acute kidney injury ( AKI ) after OPCAB . Methods and Results We enrolled 1783 consecutive OPCAB patients in either a statin or nonstatin group based on preoperative use of statins. Propensity scores were used to adjust the differences between the groups. The primary outcome was incidence of postoperative AKI according to Kidney Disease: Improving Global Outcomes criteria. To evaluate the dose-related renal effects of statins, the statin group was divided into low- and moderate- or higher dose groups based on preoperative statin dose. The incidence of postoperative AKI was 15.7% and 13.5% in the nonstatin and statin groups, respectively, and preoperative statins did not increase the incidence of postoperative AKI (odds ratio: 0.84; 95% CI, 0.61-1.15; P=0.27). In dose-related analysis, the moderate- or higher dose group showed lower incidence of postoperative AKI in comparison with the nonstatin group (odds ratio: 0.61; 95% CI, 0.39-0.95; P=0.03). However, no difference was found between low-dose and nonstatin groups (odds ratio: 1.17; 95% CI, 0.75-1.84; P=0.49) or between moderate- or higher dose and low-dose statin groups (odds ratio: 0.84; 95% CI, 0.5-1.41; P=0.51) in the incidence of postoperative AKI . Conclusions Neither preoperative statin use nor statin dose increased the risk of AKI after OPCAB . Preoperative statin therapy is not harmful in patients receiving OPCAB .

SUBMITTER: Park J

PROVIDER: S-EPMC6509717 | biostudies-literature | 2019 Apr

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Effects of Preoperative Statin on Acute Kidney Injury After Off-Pump Coronary Artery Bypass Grafting.

Park Jungchan J Lee Jong-Hwan JH Kim Keoung Ah KA Lee Seung-Hwa SH Lee Young Tak YT Kim Wook Sung WS Min Jeong Jin JJ

Journal of the American Heart Association 20190401 7

Background Although many patients with coronary artery disease are using statins before off-pump coronary artery bypass grafting ( OPCAB ) following current guidelines, recent studies have raised concerns regarding adverse effects of preoperative statins on postoperative kidney function. We evaluated the effects of preoperative statins on acute kidney injury ( AKI ) after OPCAB . Methods and Results We enrolled 1783 consecutive OPCAB patients in either a statin or nonstatin group based on preope ...[more]

PMID: 30905260

Similar Datasets

Project description:BackgroundThe cardiac surgery-associated acute kidney injury (CSA-AKI) occurs in up to 1 out of 3 patients. Off-pump coronary artery bypass grafting (OPCABG) is one of the major cardiac surgeries leading to CSA-AKI. Early identification and timely intervention are of clinical significance for CSA-AKI. In this study, we aimed to establish a prediction model of off-pump coronary artery bypass grafting-associated acute kidney injury (OPCABG-AKI) after surgery based on machine learning methods.MethodsThe preoperative and intraoperative data of 1,041 patients who underwent OPCABG in Chest Hospital, Tianjin University from June 1, 2021 to April 30, 2023 were retrospectively collected. The definition of OPCABG-AKI was based on the 2012 Kidney Disease Improving Global Outcomes (KDIGO) criteria. The baseline data and intraoperative time series data were included in the dataset, which were preprocessed separately. A total of eight machine learning models were constructed based on the baseline data: logistic regression (LR), gradient-boosting decision tree (GBDT), eXtreme gradient boosting (XGBoost), adaptive boosting (AdaBoost), random forest (RF), support vector machine (SVM), k-nearest neighbor (KNN), and decision tree (DT). The intraoperative time series data were extracted using a long short-term memory (LSTM) deep learning model. The baseline data and intraoperative features were then integrated through transfer learning and fused into each of the eight machine learning models for training. Based on the calculation of accuracy and area under the curve (AUC) of the prediction model, the best model was selected to establish the final OPCABG-AKI risk prediction model. The importance of features was calculated and ranked by DT model, to identify the main risk factors.ResultsAmong 701 patients included in the study, 73 patients (10.4%) developed OPCABG-AKI. The GBDT model was shown to have the best predictions, both based on baseline data only (AUC =0.739, accuracy: 0.943) as well as based on baseline and intraoperative datasets (AUC =0.861, accuracy: 0.936). The ranking of importance of features of the GBDT model showed that use of insulin aspart was the most important predictor of OPCABG-AKI, followed by use of acarbose, spironolactone, alfentanil, dezocine, levosimendan, clindamycin, history of myocardial infarction, and gender.ConclusionsA GBDT-based model showed excellent performance for the prediction of OPCABG-AKI. The fusion of preoperative and intraoperative data can improve the accuracy of predicting OPCABG-AKI.

Project description:BACKGROUND:Brachial-ankle pulse wave velocity (baPWV) is the simple, non-invasive, gold-standard method for assessing arterial stiffness. However, baPWV has been shown to be associated with renal dyfunction, with a few reports demonstrating an association between baPWV and postoperative acute kidney injury (AKI) among surgical patients. METHODS:We retrospectively analyzed preoperative baPWV data that were prospectively collected from 164 patients who underwent off-pump coronary artery bypass grafting (CABG) between April 2013 and July 2019 (mean age: 66.2 ± 10.3 years, 29.3% females). Primarily, baPWV was investigated as an independent predictor of postoperative AKI development; secondarily, the patients were divided into high and low PWV groups according to the optimal baPWV cut-off value. Postoperative complications, mortality, and mid-term survival were compared between the two groups. RESULTS:AKI developed in 30 patients (18.3%). Univariate analysis showed that AKI was significantly associated with baPWV (20.2±7.3 vs. 16.2±2.8 m/s, p < 0.001), age, preoperative serum creatinine, and EuroSCORE. Multivariable logistic regression analysis revealed baPWV as independently associated with postoperative AKI even after adjustment for preoperative creatinine, old age (> 75 years), hypertension, diabetes under insulin therapy, and EuroSCORE. Moreover, area under the curve (AUC) analysis indicated that PWV can predict AKI better than preoperative creatinine levels (AUC, 0.781 [95% confidence interval, 0.688-0.874] vs. 0.680 [0.568-0.792]). The group-dividing baPWV cut-off value for AKI was 19 m/s. There were no 30-day mortality. The in-hospital mortality rates in the high and the low PWV groups were 2.2% (n = 1) and 0.8% (n = 1), respectively (p = 0.484). Midterm survival rates were not different between the two groups, but the rate of composite neurologic complication composed of stroke and delirium, was higher, and rate of mechanical ventilatory support was longer, in the high PWV group. CONCLUSION:Brachial-ankle pulse wave velocity was an independent predictor of postoperative AKI following off-pump CABG, and high baPWVs may affect the composite neurologic outcome and the duration of mechanical ventilatory support.

Dataset Information

Effects of Preoperative Statin on Acute Kidney Injury After Off-Pump Coronary Artery Bypass Grafting.

Publications

Effects of Preoperative Statin on Acute Kidney Injury After Off-Pump Coronary Artery Bypass Grafting.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets