Olmos Carmen, Vilacosta Isidre, Habib Gilbert, Maroto Luis, Fernández Cristina, López Javier, Sarriá Cristina, Salaun Erwan, Di Stefano Salvatore, Carnero Manuel, Hubert Sandrine, Ferrera Carlos, Tirado Gabriela, Freitas-Ferraz Afonso, Sáez Carmen, Cobiella Javier, Bustamante-Munguira Juan, Sánchez-Enrique Cristina, García-Granja Pablo Elpidio, Lavoute Cecile, Obadia Benjamin, Vivas David, Gutiérrez Ángela, San Román José Alberto
Instituto Cardiovascular. Hospital Universitario Clínico San Carlos, Madrid, Spain.
Aix-Marseille Université, Marseille, France.
Heart. 2017 Sep;103(18):1435-1442. doi: 10.1136/heartjnl-2016-311093. Epub 2017 Apr 21.
To develop and validate a calculator to predict the risk of in-hospital mortality in patients with active infective endocarditis (IE) undergoing cardiac surgery.
Thousand two hundred and ninety-nine consecutive patients with IE were prospectively recruited (1996-2014) and retrospectively analysed. Left-sided patients who underwent cardiac surgery (n=671) form our study population and were randomised into development (n=424) and validation (n=247) samples. Variables statistically significant to predict in-mortality were integrated in a multivariable prediction model, the Risk-Endocarditis Score (RISK-E). The predictive performance of the score and four existing surgical scores (European System for Cardiac Operative Risk Evaluation (EuroSCORE) I and II), Prosthesis, Age ≥70, Large Intracardiac Destruction, , Urgent Surgery, Sex (Female) (PALSUSE), EuroSCORE ≥10) and Society of Thoracic Surgeons's Infective endocarditis score (STS-IE)) were assessed and compared in our cohort. Finally, an external validation of the RISK-E in a separate population was done.
Variables included in the final model were age, prosthetic infection, periannular complications, or fungi infection, acute renal failure, septic shock, cardiogenic shock and thrombocytopaenia. Area under the receiver operating characteristic curve in the validation sample was 0.82 (95% CI 0.75 to 0.88). The accuracy of the other surgical scores when compared with the RISK-E was inferior (p=0.010). Our score also obtained a good predictive performance, area under the curve 0.76 (95% CI 0.64 to 0.88), in the external validation.
IE-specific factors (microorganisms, periannular complications and sepsis) beside classical variables in heart surgery (age, haemodynamic condition and renal failure) independently predicted perioperative mortality in IE. The RISK-E had better ability to predict surgical mortality in patients with IE when compared with other surgical scores.
开发并验证一种计算器,以预测接受心脏手术的活动性感染性心内膜炎(IE)患者的院内死亡风险。
前瞻性招募了1299例连续性IE患者(1996 - 2014年)并进行回顾性分析。接受心脏手术的左侧IE患者(n = 671)构成我们的研究人群,并被随机分为开发样本(n = 424)和验证样本(n = 247)。将对预测住院死亡率有统计学意义的变量纳入多变量预测模型,即风险 - 心内膜炎评分(RISK - E)。在我们的队列中评估并比较了该评分与四个现有的手术评分(欧洲心脏手术风险评估系统(EuroSCORE)I和II)、人工瓣膜、年龄≥70岁、心内大面积破坏、急诊手术、性别(女性)(PALSUSE)、EuroSCORE≥10)以及胸外科医师协会感染性心内膜炎评分(STS - IE)的预测性能。最后,在一个单独的人群中对RISK - E进行了外部验证。
最终模型纳入的变量有年龄、人工瓣膜感染、瓣周并发症、或真菌感染、急性肾衰竭、感染性休克、心源性休克和血小板减少症。验证样本中受试者工作特征曲线下面积为0.82(95%CI 0.75至0.88)。与RISK - E相比,其他手术评分的准确性较低(p = 0.010)。在外部验证中,我们的评分也获得了良好的预测性能,曲线下面积为0.76(95%CI 0.64至0.88)。
除了心脏手术中的经典变量(年龄、血流动力学状况和肾衰竭)外,IE特异性因素(微生物、瓣周并发症和败血症)可独立预测IE患者的围手术期死亡率。与其他手术评分相比,RISK - E在预测IE患者手术死亡率方面具有更好的能力。