Journal of Peking University (Health Sciences) ›› 2021, Vol. 53 ›› Issue (6): 1139-1143. doi: 10.19723/j.issn.1671-167X.2021.06.022

Previous Articles     Next Articles

Preoperative plasma predictive factors of new-onset atrial fibrillation after coronary artery bypass graft surgery: A propensity score matching study

XU Hao,ZHANG Guo-dong,FAN Guang-pu,CHEN Yu()   

  1. Department of Cardiac Surgery, Heart Center, Peking University People’s Hospital, Beijing 100044, China
  • Received:2019-12-02 Online:2021-12-18 Published:2021-12-13
  • Contact: Yu CHEN E-mail:chenyu@pkuph.edu.cn

RICH HTML

  

Abstract:

Objective: To study the relationship between preoperative plasma interleukin-1 (IL-1), interleukin-6 (IL-6), tumor necrosis factor-α (TNF-α), homocysteine (Hcy), endothelin-1 (ET-1) levels and new-onset atrial fibrillation (AF) after coronary artery bypass grafting (CABG). Methods: In the study, 148 patients who underwent isolated CABG in Peking University People’s Hospital from January 1, 2017 to December 30, 2017 were enrolled, of whom 39 had new-onset AF. The fasting venous blood was collected within 24 hours before the surgery. The preoperative plasma IL-1, IL-6, TNF-α, Hcy, ET-1 levels were detected by enzyme-linked immunosorbent assay (ELISA). The patients were divided into AF group and non-AF group according to whether new-onset AF occurred after operation. After 1 ∶1 propensity score matching (PSM), 38 people were in each group. The paired sample t-tests were performed on the five factors’ concentrations of the matched AF group and the non-AF group respectively. If the concentration values did not conform to the normal distribution, the Wilcoxon signed rank sum test was performed. Conditional Logistic regression analysis was performed on the concentrations of the five indicators to explore the correlation between preoperative plasma concentrations of IL-1, IL-6, TNF-α, Hcy, ET-1 and postoperative new-onset AF after CABG. Results: After a 1 ∶1 propensity score matching, the AF group was comparable to the non-AF group. The concentrations of IL-1, IL-6, TNF-α, and Hcy in the AF group were higher than those in the non-AF group [(0.867±0.589) ng/L vs. (0.742±0.262) ng/L, 21.55 (6.50, 209.90) ng/L vs. 17.95 (3.60, 86.70) ng/L, 20.30 (5.70, 361.00) ng/L vs. 21.50 (7.50, 251.80) ng/L, (0.29±0.11) μmol/L vs. (0.27±0.09) μmol/L], but the differences were not statistically significant (P=0.165, P=0.891, P=0.817, P=0.285). After the conditional Logistic regression analysis, the above four variables were not predictors of new-onset AF after CABG. The concentrations of ET-1 in the matched AF group and non-AF group were (25.80±6.20) ng/L and (29.10±8.54) ng/L, respectively. The correlation between preoperative low plasma ET-1 concentration and the new-onset AF after CABG were statistically significant (P=0.003). After conditional Logistic regression analysis, preoperative plasma ET-1 concentration was correlated with postoperative new-onset AF after CABG (P=0.039, adjusted OR=0.637, 95%CI: 0.415-0.977). Conclusion: The levels of preoperative plasma IL-1, IL-6, TNF-α and Hcy in the patients with new-onset AF after CABG were higher than those in the patients without AF, but the difference was not statistically significant. Preoperative plasma low ET-1 concentration was statistically associated with new-onset AF after CABG.

Key words: Coronary artery disease, Coronary artery bypass, Atrial fibrillation, Risk factors

CLC Number: 

  • R541.75

Table 1

Baseline characteristics of patients before and after propensity score matching"

Items Before matched After matched
AF group (n=39) non-AF group (n=109) P AF group (n=38) non-AF group (n=38) P
Age/years 63.10±8.52 63.50±9.52 0.800 62.68±8.61 62.86±10.99 0.363
Male 27 (69.2) 80 (73.4) 0.618 27 (71.1) 29 (76.3) 0.602
Body mass index/(kg/m2) 26.79±4.44 25.10±4.16 0.034 26.03±4.54 25.75±5.32 0.816
Smoking 21 (53.8) 49 (45.0) 0.340 18 (47.4) 17 (44.7) 0.818
Diabetes mellitus 18 (46.2) 31 (28.4) 0.044 16 (42.1) 11 (28.9) 0.231
Hypertension 27 (69.2) 63 (57.8) 0.209 27 (71.1) 25 (65.8) 0.622
Hyperlipidemia 4 (10.3) 10 (9.2) 0.843 4 (10.5) 5 (13.2) >0.999
Left atrium diameter/mm 38.00±5.48 38.21±5.19 0.812 38.79±6.00 38.04±4.19 0.530
LVEF/% 60.75±14.33 61.04±12.84 0.910 61.20±8.99 62.21±11.21 0.725
NYHA class 0.332 0.602
0 (0) 1 (0.9) 0 (0) 0 (0)
30 (76.9) 91 (83.5) 27 (71.1) 29 (76.3)
9 (23.1) 15 (13.8) 11 (28.9) 9 (23.7)
0 (0) 2 (1.8) 0 (0) 0 (0)
Prior cardiac surgery/PCI 6 (15.4) 16 (14.7) 0.915 6 (15.8) 8 (21.1) 0.554
Preoperative laboratory parameters
Creatinine/(μmol/L) 69.0 (46.0, 214.0) 69.5 (38.0, 173.0) 0.029 72.0 (46.0, 214.0) 66.5 (42.0, 173.0) 0.939
Total cholesterol/(mmol/L) 4.05±1.45 3.85±1.17 0.379 4.05±1.46 4.00±1.00 0.872
LDL/(mmol/L) 2.18 (1.17, 6.00) 2.40 (0.64, 6.51) 0.237 2.45 (1.00, 6.00) 2.09 (1.00, 4.00) 0.858
Blood glucose/(mmol/L) 6.22 (4.23, 13.20) 5.48 (3.79, 14.71) 0.337 5.76 (4.00, 11.00) 5.50 (4.00, 13.00) 0.534
Cardiopulmonary bypass 0.935 0.798
On-pump 11 (28.2) 30 (27.5) 11 (28.9) 10 (26.3)
Off-pump 28 (71.8) 79 (72.5) 27 (71.1) 28 (73.7)
IABP 3 (7.7) 5 (4.6) 0.746 1 (2.6) 3 (7.9) 0.607
Blood transfusion 20 (51.3) 50 (45.9) 0.561 17 (44.7) 19 (50.0) 0.646
Ventilation time 13 (5, 283) 12 (3, 253) 0.794 12 (5, 250) 10 (5, 222) 0.392
Re-intubation 1 (2.6) 1 (0.9) 0.459 0 (0) 0 (0) >0.999
ICU time/h 23 (7, 293) 20 (6, 288) 0.088 21 (7, 271) 23 (8, 263) 0.564
Preoperative medication
Nitroglycerin 35 (89.7) 98 (89.9) >0.999 35 (92.1) 34 (89.5) >0.999
Catecholamine 0 (0) 0 (0) >0.999 0 (0) 0 (0) >0.999
Beta-blocker 36 (92.3) 103 (94.5) 0.920 36 (94.7) 35 (92.1) >0.999
ACEI/ARB 8 (20.5) 17 (15.6) 0.482 8 (21.1) 8 (21.1) >0.999
Statin 37 (94.9) 109 (100.0) 0.116 37 (97.4) 38 (100.0) >0.999
Asprin 37 (94.9) 98 (89.9) 0.542 36 (94.7) 33 (86.8) 0.428
Clopidogrel 4 (10.3) 10 (9.2) >0.999 2 (5.3) 4 (10.5) 0.671
Ticagrelor 0 (0) 0 (0) >0.999 0 (0) 0 (0) >0.999
Postoperative medication
Catecholamine 37 (94.9) 105 (96.3) >0.999 36 (94.7) 36 (94.7) >0.999
Nitroglycerin 37 (94.9) 104 (95.4) >0.999 36 (94.7) 38 (100.0) 0.474
Beta-blocker 38 (25.6) 109 (100.0) 0.590 37 (97.4) 38 (100.0) >0.999
ACEI/ARB 10 (7.7) 16 (14.7) 0.194 8 (21.1) 8 (21.1) >0.999
Statin 38 (97.4) 106 (97.2) >0.999 37 (97.4) 36 (94.7) >0.999
Asprin 38 (97.4) 107 (98.2) >0.999 37 (97.4) 38 (100.0) >0.999
Clopidogrel 9 (23.1) 24 (22.0) 0.892 6 (15.8) 6 (15.8) >0.999
Ticagrelor 0 (0) 0 (0) >0.999 0 (0) 0 (0) >0.999

Table 2

Preoperative plasma levels of factors"

Items AF group non-AF group P
IL-1/(ng/L) 0.867±0.589 0.742±0.262 0.165
IL-6/(ng/L) 21.55 (6.50, 209.90) 17.95 (3.60, 86.70) 0.891
TNF-α/(ng/L) 20.30 (5.70, 361.00) 21.50 (7.50, 251.80) 0.817
Hcy/(μmol/L) 0.29±0.11 0.27±0.09 0.285
ET-1/(ng/L) 25.80±6.20 29.10±8.54 0.003

Table 3

Conditional Logistic regression analysis results"

Items P Adjusted OR 95%CI
IL-1 0.573 2.131 0.153-29.612
IL-6 0.366 0.978 0.933-1.026
TNF-α 0.131 1.026 0.992-1.061
Hcy 0.413 4.333 0.111-168.320
ET-1 0.039 0.637 0.415-0.977
[1] El-Chami MF, Kilgo P, Thourani V, et al. New-onset atrial fibrillation predicts long-term mortality after coronary artery bypass graft[J]. J Am Coll Cardiol, 2010, 55(13):1370-1376.
doi: 10.1016/j.jacc.2009.10.058 pmid: 20338499
[2] 孙源君. 心房颤动与肺栓塞的关系及治疗[J]. 中国循环杂志, 2018, 33(3):307-309.
[3] Hak L, Mysliwska J, Wieckiewicz J, et al. Interleukin-2 as a predictor of early postoperative atrial fibrillation after cardiopulmonary bypass graft (CABG)[J]. J Interferon Cytokine Res, 2009, 29(6):327-332.
doi: 10.1089/jir.2008.0082.2906
[4] Wu ZK, Laurikka J, Vikman S, et al. High postoperative interleukin-8 levels related to atrial fibrillation in patients undergoing coronary artery bypass surgery[J]. World J Surg, 2008, 32(12):2643-2649.
doi: 10.1007/s00268-008-9758-7
[5] 王淑娟, 林祥灿. 血浆NT-proBNP水平与同型半胱氨酸对糖尿病合并心房颤动的相关性研究[J]. 医学信息, 2018, 31(14):169-171.
[6] 刘明, 魏兰芳, 薛洋, 等. 血清同型半胱氨酸与心房颤动的关系[J]. 中国循证心血管医学杂志, 2017, 9(1):117-118.
[7] Wang H, Liu J, Fang P, et al. Big endothelin-1 as a predictor of atrial fibrillation recurrence after primary ablation only in patients with paroxysmal atrial fibrillation[J]. Herz, 2012, 37(8):919-925.
doi: 10.1007/s00059-012-3626-9 pmid: 22669310
[8] 徐颖. 高敏C反应蛋白、脑钠肽、内皮素1与非瓣膜性心房颤动关系的探讨[D]. 天津: 天津医科大学, 2011.
[9] 洪钰杰, 钟国强, 蒋智渊, 等. 内皮素-1在心房颤动发生中的机制探讨[J]. 中国循环杂志, 2016, 31(2):146-150.
[10] 郭瑾. 焦虑抑郁患者血清NO、ET-1、vWF表达水平研究[D]. 太原: 山西医科大学, 2018.
[11] 邓晓雯. KL-6、ET-1在OSAHS患者中的血清水平及其意义[D]. 湖南衡阳: 南华大学, 2014.
[12] 马朝晖, 张仁福, 姜辉, 等. 三种心脏停搏液对心肌保护的对比研究[J]. 中国循环杂志, 2000, 15(1):40-42.
[1] Zhicun LI, Tianyu WU, Lei LIANG, Yu FAN, Yisen MENG, Qian ZHANG. Risk factors analysis and nomogram model construction of postoperative pathological upgrade of prostate cancer patients with single core positive biopsy [J]. Journal of Peking University (Health Sciences), 2024, 56(5): 896-901.
[2] Ye YAN,Xiaolong LI,Haizhui XIA,Xuehua ZHU,Yuting ZHANG,Fan ZHANG,Ke LIU,Cheng LIU,Lulin MA. Analysis of risk factors for long-term overactive bladder after radical prostatectomy [J]. Journal of Peking University (Health Sciences), 2024, 56(4): 589-593.
[3] Yan CHEN,Kuangmeng LI,Kai HONG,Shudong ZHANG,Jianxing CHENG,Zhongjie ZHENG,Wenhao TANG,Lianming ZHAO,Haitao ZHANG,Hui JIANG,Haocheng LIN. Retrospective study on the impact of penile corpus cavernosum injection test on penile vascular function [J]. Journal of Peking University (Health Sciences), 2024, 56(4): 680-686.
[4] Bo PANG,Tongjun GUO,Xi CHEN,Huaqi GUO,Jiazhang SHI,Juan CHEN,Xinmei WANG,Yaoyan LI,Anqi SHAN,Hengyi YU,Jing HUANG,Naijun TANG,Yan WANG,Xinbiao GUO,Guoxing LI,Shaowei WU. Personal nitrogen oxides exposure levels and related influencing factors in adults over 35 years old in Tianjin and Shanghai [J]. Journal of Peking University (Health Sciences), 2024, 56(4): 700-707.
[5] Ying WEI,Ming CUI,Shuwang LIU,Haiyi YU,Wei GAO,Lei LI. Different levels and clinical significance of growth differentiation factor-15 in patients with atrial fibrillation [J]. Journal of Peking University (Health Sciences), 2024, 56(4): 715-721.
[6] Jing HE,Zhongze FANG,Ying YANG,Jing LIU,Wenyao MA,Yong HUO,Wei GAO,Yangfeng WU,Gaoqiang XIE. Relationship between lipid metabolism molecules in plasma and carotid atheroscle-rotic plaques, traditional cardiovascular risk factors, and dietary factors [J]. Journal of Peking University (Health Sciences), 2024, 56(4): 722-728.
[7] Shan CAI,Yihang ZHANG,Ziyue CHEN,Yunfe LIU,Jiajia DANG,Di SHI,Jiaxin LI,Tianyu HUANG,Jun MA,Yi SONG. Status and pathways of factors influencing physical activity time among elementary and junior high school students in Beijing [J]. Journal of Peking University (Health Sciences), 2024, 56(3): 403-410.
[8] Zuhong ZHANG,Tianjiao CHEN,Jun MA. Associations between puberty timing and cardiovascular metabolic risk factors among primary and secondary students [J]. Journal of Peking University (Health Sciences), 2024, 56(3): 418-423.
[9] Yuting LIN,Huali WANG,Yu TIAN,Litong GONG,Chun CHANG. Factors influencing cognitive function among the older adults in Beijing [J]. Journal of Peking University (Health Sciences), 2024, 56(3): 456-461.
[10] Jinrong ZHU,Yana ZHAO,Wei HUANG,Weiwei ZHAO,Yue WANG,Song WANG,Chunyan SU. Clinical characteristics of COVID-19 infection in patients undergoing hemodialysis [J]. Journal of Peking University (Health Sciences), 2024, 56(2): 267-272.
[11] Zhanhong LAI,Jiachen LI,Zelin YUN,Yonggang ZHANG,Hao ZHANG,Xiaoyan XING,Miao SHAO,Yuebo JIN,Naidi WANG,Yimin LI,Yuhui LI,Zhanguo LI. A unicenter real-world study of the correlation factors for complete clinical response in idiopathic inflammatory myopathies [J]. Journal of Peking University (Health Sciences), 2024, 56(2): 284-292.
[12] Xiaoqian SI,Xiujuan ZHAO,Fengxue ZHU,Tianbing WANG. Risk factors for acute respiratory distress syndrome in patients with traumatic hemorrhagic shock [J]. Journal of Peking University (Health Sciences), 2024, 56(2): 307-312.
[13] Yangyang LI,Lin HOU,Zijun MA,Shanyamei HUANG,Jie LIU,Chaomei ZENG,Jiong QIN. Association of pregnancy factors with cow's milk protein allergy in infants [J]. Journal of Peking University (Health Sciences), 2024, 56(1): 144-149.
[14] Xiaoqiang LIU,Yin ZHOU. Risk factors of perioperative hypertension in dental implant surgeries with bone augmentation [J]. Journal of Peking University (Health Sciences), 2024, 56(1): 93-98.
[15] Liang LUO,Yun LI,Hong-yan WANG,Xiao-hong XIANG,Jing ZHAO,Feng SUN,Xiao-ying ZHANG,Ru-lin JIA,Chun LI. Anti-endothelial cell antibodies in predicting early miscarriage [J]. Journal of Peking University (Health Sciences), 2023, 55(6): 1039-1044.
Viewed
Full text


Abstract

Cited

  Shared   
  Discussed   
No Suggested Reading articles found!