Gu Jiwei, Andreasen Jan J, Melgaard Jacob, Lundbye-Christensen Søren, Hansen John, Schmidt Erik B, Thorsteinsson Kristinn, Graff Claus
Department of Cardiothoracic Surgery, Aalborg University Hospital, Aalborg, Denmark; Department of Clinical Medicine, Aalborg University, Aalborg, Denmark; Department of Cardiovascular Surgery, Heart Centre of General Hospital, Ningxia Medical University, Yinchuan, Ningxia, Peoples Republic of China; Atrial Fibrillation Study Group, Aalborg University Hospital, Aalborg, Denmark.
Department of Cardiothoracic Surgery, Aalborg University Hospital, Aalborg, Denmark; Department of Clinical Medicine, Aalborg University, Aalborg, Denmark; Atrial Fibrillation Study Group, Aalborg University Hospital, Aalborg, Denmark.
J Cardiothorac Vasc Anesth. 2017 Feb;31(1):69-76. doi: 10.1053/j.jvca.2016.05.036. Epub 2016 May 24.
To investigate if electrocardiogram (ECG) markers from routine preoperative ECGs can be used in combination with clinical data to predict new-onset postoperative atrial fibrillation (POAF) following cardiac surgery.
Retrospective observational case-control study.
Single-center university hospital.
One hundred consecutive adult patients (50 POAF, 50 without POAF) who underwent coronary artery bypass grafting, valve surgery, or combinations.
Retrospective review of medical records and registration of POAF.
Clinical data and demographics were retrieved from the Western Denmark Heart Registry and patient records. Paper tracings of preoperative ECGs were collected from patient records, and ECG measurements were read by two independent readers blinded to outcome. A subset of four clinical variables (age, gender, body mass index, and type of surgery) were selected to form a multivariate clinical prediction model for POAF and five ECG variables (QRS duration, PR interval, P-wave duration, left atrial enlargement, and left ventricular hypertrophy) were used in a multivariate ECG model. Adding ECG variables to the clinical prediction model significantly improved the area under the receiver operating characteristic curve from 0.54 to 0.67 (with cross-validation). The best predictive model for POAF was a combined clinical and ECG model with the following four variables: age, PR-interval, QRS duration, and left atrial enlargement.
ECG markers obtained from a routine preoperative ECG may be helpful in predicting new-onset POAF in patients undergoing cardiac surgery.
探讨常规术前心电图(ECG)的标记物是否可与临床数据相结合,以预测心脏手术后新发的术后心房颤动(POAF)。
回顾性观察性病例对照研究。
单中心大学医院。
100例连续接受冠状动脉搭桥术、瓣膜手术或联合手术的成年患者(50例发生POAF,50例未发生POAF)。
回顾病历并记录POAF情况。
从丹麦西部心脏登记处和患者病历中获取临床数据和人口统计学资料。从患者病历中收集术前心电图的纸质记录,由两名对结果不知情的独立阅片者读取心电图测量值。选择四个临床变量(年龄、性别、体重指数和手术类型)的子集来构建POAF的多变量临床预测模型,并在多变量心电图模型中使用五个心电图变量(QRS时限、PR间期、P波时限、左心房扩大和左心室肥厚)。将心电图变量添加到临床预测模型中可使受试者工作特征曲线下面积从0.54显著提高到0.67(交叉验证)。POAF的最佳预测模型是一个包含以下四个变量的临床与心电图联合模型:年龄、PR间期、QRS时限和左心房扩大。
从常规术前心电图获得的心电图标记物可能有助于预测接受心脏手术患者新发的POAF。