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A Prediction Rule Including Interleukin-6 in Pericardial Drainage Improves Prediction of New-Onset Atrial Fibrillation After Coronary Artery Bypass Grafting.

Authors :
Feng, Xinwei
Wu, Fangqin
Wu, Ying
Ding, Shu
Tao, Xiangjun
Li, Jinglian
Liu, Weiwei
Ma, Ruiying
Chen, Yuling
Source :
Journal of Cardiothoracic & Vascular Anesthesia; Jul2022, Vol. 36 Issue 7, p1975-1984, 10p
Publication Year :
2022

Abstract

[Display omitted] To test the hypothesis that a prediction rule including levels of interleukin-6 in pericardial drainage (pdIL-6) would improve the discrimination in classifying patients undergoing coronary artery bypass grafting (CABG) into different postoperative atrial fibrillation (POAF) risk levels. Prospective cohort study. A university-affiliated tertiary hospital. Patients undergoing CABG. None. We prospectively recruited patients who underwent CABG into derivation and validation cohorts. The independent predictors were identified in the derivation cohort using multiple logistic regression and tested in the validation cohort. The performance of the predictive model was tested using area under the receiver operating characteristic curve (AUC) in both cohorts. A prediction rule was created by assigning points to each predictor. Patients were classified in various risk levels according to their total risk scores. We enrolled 302 and 207 patients in the derivation and validation cohorts, respectively. Multiple logistic regression analysis identified six predictors: age ≥61 y, left atrial diameter ≥49 mm, right atrial diameter ≥45 mm, number of grafts ≥3, and serum uric acid ≥226 µmol/L and pdIL-6 levels ≥166 ng/mL at postoperative 12 h. The AUC of the model was 0.78 and 0.77 for the derivation and validation cohort, respectively, which was greatly increased by adding pdIL-6. Patients were stratified into low-risk, moderate-risk and high-risk groups. A POAF prediction rule including pdIL-6 had good performance for stratifying CABG patients into various risk groups for POAF. The inclusion of pdIL-6 resulted in clinically meaningful improvement in risk prediction. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
10530770
Volume :
36
Issue :
7
Database :
Supplemental Index
Journal :
Journal of Cardiothoracic & Vascular Anesthesia
Publication Type :
Academic Journal
Accession number :
157179645
Full Text :
https://doi.org/10.1053/j.jvca.2021.09.048