Kudaiberdiev Taalaibek, Joshibayev Seitkhan, Imanalieva Gulzada, Beishenaliev Alimkadir S, Ashinaliev Abdulin A, Baisekeev Taalaibek A, Chinaliev Sergei
Scientific Research Institute of Heart Surgery and Organ Transplantation, Bishkek, Kyrgyzstan.
Department of General Surgery, Faculty of Medicine, Kyrgyz State Medical Academy, Bishkek, Kyrgyzstan.
Int J Cardiol Heart Vasc. 2016 Aug 3;12:75-81. doi: 10.1016/j.ijcha.2016.07.005. eCollection 2016 Sep.
The aim of our study was to define predictors of cardiac compression development including clinical, electrocardiographic, echocardiographic, chest-X-ray and perioperative parameters and their diagnostic value.
Overall 243 patients with pericardial disease, among them 123 with compression (tamponade, constriction) and 120 without signs of compression were included in the study. Clinical, laboratory, electrocardiographic, chest-X-Ray, echocardiographic and perioperative data were included in the logistic regression analysis to define predictors of tamponade/constriction development.
Logistic regression analysis demonstrated large effusion (> 20 mm) (OR 5.393, 95%CI 1.202-24.199, p = 0.028), cardiac chamber collapse (OR 31.426, 95%CI 1.609-613-914, p = 0.023) and NYHA class > 3 (OR 8.671, 95%CI 1.730-43.451, p = 0.009) were multivariable predictors of compression development. The model including these three variables allowed predicting compression in 91.7% of cases. ROC analyses demonstrated that all three variables had significant diagnostic value with sensitivity of 75.6% and specificity of 74.2% for large effusion, low sensitivity and high specificity for cardiac chamber collapse (35% and 92%) and NYHA class (32.5% and 94.2%).
The independent predictors of compression development are presence of large effusion > 20 mm, cardiac chamber collapse and high NYHA class. The model including all three parameters allows correctly predicting compression in 91.4% of cases. The diagnostic accuracy of each parameter is characterized by high sensitivity and specificity of large effusion, high specificity of cardiac chamber collapse and NYHA class.
本研究旨在确定心脏受压发展的预测因素，包括临床、心电图、超声心动图、胸部X线及围手术期参数及其诊断价值。
本研究共纳入243例心包疾病患者，其中123例存在心脏受压（心包填塞、缩窄性心包炎），120例无心脏受压体征。将临床、实验室、心电图、胸部X线、超声心动图及围手术期数据纳入逻辑回归分析，以确定心包填塞/缩窄性心包炎发展的预测因素。
逻辑回归分析显示，大量心包积液（>20mm）（比值比5.393，95%可信区间1.202 - 24.199，p = 0.028）、心腔塌陷（比值比31.426，95%可信区间1.609 - 613.914，p = 0.023）及纽约心脏协会（NYHA）心功能分级>3级（比值比8.671，95%可信区间1.730 - 43.451，p = 0.009）是心脏受压发展的多变量预测因素。包含这三个变量的模型可在91.7%的病例中预测心脏受压。ROC分析表明，所有三个变量均具有显著诊断价值，大量心包积液的敏感性为75.6%，特异性为74.2%；心腔塌陷的敏感性低、特异性高（35%和92%）；NYHA分级的敏感性为32.5%，特异性为94.2%。
心脏受压发展的独立预测因素为存在>20mm的大量心包积液、心腔塌陷及NYHA心功能分级高。包含所有三个参数的模型可在91.4%的病例中正确预测心脏受压。每个参数的诊断准确性表现为大量心包积液具有高敏感性和特异性，心腔塌陷及NYHA分级具有高特异性。
