Objective
Using the nomogram to intuitively predict atrial fibrillation after coronary artery bypass grafting. Identify high-risk patients with atrial fibrillation and provide preoperative protective therapy.
Methods
A total of 397 patients that underwent coronary artery bypass grafting were consecutively enrolled. Independent predictors of patients were analyzed by multivariate logistic regression. Two nomograms were constructed to predict postoperative atrial fibrillation.
Results
The incidence of postoperative atrial fibrillation in this study was 29% (115/397). Multivariate Logistic showed that Age, Operative Time > 4 h, Left Atrial Diameter > 40 mm, Mean Arterial Pressure, Body Mass Index > 23 kg/m2, Insulins, and Statins were independently associated with atrial fibrillation after isolated coronary artery bypass grafting. The nomogram of postoperative atrial fibrillation in patients was constructed using total predictor variables (AUC = 0.727, 95% CI 0.673–0.781). The model was internally validated (AUC = 0.701) by K-fold Cross-validation resampling (K = 5, Times = 400). To make an early intervention, the intraoperative information of the patients was excluded. Only 6 variables before surgery were used to establish the brief nomogram to predict postoperative atrial fibrillation (AUC = 0.707, 95% CI 0.651–0.764). The brief model was internally validated (AUC = 0.683) by resampling with K-fold Cross-validation resampling.
Conclusions
These two nomograms could be used to predict patients at high risk for atrial fibrillation after isolated coronary artery bypass grafting.
Background: Acute kidney injury (AKI) is a common complication after cardiac surgery. It is closely related to poor perioperative glycemic control. We aimed to explore the relationship between preoperative hemoglobin A1c (HbA1c) levels and cumulative postoperative insulin usage and AKI after off-pump coronary artery bypass grafting (OPCABG).
Method: The included a total of 284 patients undergoing isolated OPCABG from 2018 to 2020. According to KDIGO's diagnostic criteria, patients were divided into the AKI group and the non-AKI group. Methods included ① increase in SCr by ≥0.3 mg/dl (≥26.5 µmol/l) within 48 hours; ② increase in SCr to ≥1.5 times baseline, which is known or presumed to have occurred within the prior 7 days; ③ urine volume <0.5 ml/kg/hour for 6 hours.
Results: Fifty-one patients (17.9%) had postoperative AKI. HbA1c levels (non-AKI group 6.1 (5.8, 7.1) vs. the AKI group 7.1 (5.9, 8.6) (P = 0.014, cut-off=7.2, AUC=0.61, sensitivity 49%, specificity 76.4%) and postoperative insulin usage (non-AKI group 16.0 (4.0, 36.0) vs. the AKI group 56.0 (11.0, 132.0), P < 0.001, cut-off=39.5, AUC=0.673, sensitivity 60.8%, specificity 76.8%) were different between the two groups. Multivariate logistic regression analysis showed that HbA1c > 7.2% (OR=2.869, P = 0.04) and postoperative insulin usage > 39.5 U (OR=7.548, P < 0.001) were independently associated with AKI.
Conclusions: HbA1c levels and cumulative postoperative insulin usage could be used as independent predictors for AKI after OPCABG. Postoperative insulin usage is more predictive than preoperative HbA1c levels.
Following publication of the original article [1], there is a formatting error in Tables 2 and 3. The corrected tables are shown below:The original article has been corrected.
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