Petricevic Mirna, Petricevic Mate, Pasalic Marijan, Golubic Cepulic Branka, Raos Mirela, Vasicek Vesna, Goerlinger Klaus, Rotim Kresimir, Gasparovic Hrvoje, Biocina Bojan
Department of Cardiac Surgery, University Hospital Center Zagreb, Zagreb, Croatia.
University Department of Health Studies, University of Split, Split, Croatia.
J Cardiothorac Surg. 2021 Apr 21;16(1):103. doi: 10.1186/s13019-021-01473-3.
An estimated 20% of allogeneic blood transfusions in the United States are associated with cardiac surgery. It is estimated that 11% of red cell resources were used for transfusion support of patients undergoing coronary artery bypass grafting (CABG) with a documented wide variability in transfusion rate (7.8 to 92.8%). To address the issue of unnecessary transfusions within the CABG population, we developed a model to predict which patients are at low risk of bleeding for whom transfusion treatment might be considered unnecessary. Herein we present our "SHOULD-NOT-BLEED-SCORE" application developed for the Windows® software platform which is based on our previous research.
This study is aimed to develop a user-friendly application that stratifies patients with respect to bleeding risk. The statistical model we used in our previous research was focused on detection of CABG patients at low risk of bleeding. The rationale behind such an approach was to identify a CABG patient subgroup at low risk of bleeding. By identifying patients at low risk of bleeding we can define a subgroup of patients for whom transfusion treatment might be considered unnecessary. We developed a Windows platform application based on risk modelling which we previously calculated for 1426 patients undergoing elective CABG from January 2010 to January 2018.
The SHOULD-NOT-BLEED-SCORE risk score is developed for the Windows software platform. A mathematical model that is based on multivariate analysis was used for app development. The variables that entered the scoring system were: Age; Body Mass Index; Chronic Renal Failure; Preoperative Clopidogrel Exposure; Preoperative Red Blood Cells Count; Preoperative Fibrinogen Level; Preoperative Multiplate ASPI test area under the curve (AUC) units. The SHOULD-NOT-BLEED-SCORE identifies/predicts patients without a risk for excessive bleeding with strong discriminatory performance (Receiver Operating Curve (ROC) analysis AUC 72.3%, p < 0.001).
The SHOULD-NOT-BLEED risk scoring application may be useful in the preoperative risk screening process. The clinical and economic burden associated with unnecessary transfusions may be adequately addressed by a preoperative scoring system detecting patients at low risk of bleeding for whom transfusion treatment might be considered unnecessary.
在美国，估计所有异体输血中有20%与心脏手术相关。据估计，11%的红细胞资源用于为接受冠状动脉旁路移植术（CABG）的患者提供输血支持，输血率存在明显差异（7.8%至92.8%）。为解决CABG人群中不必要输血的问题，我们开发了一个模型，以预测哪些患者出血风险较低，可能无需进行输血治疗。在此，我们展示我们基于先前研究为Windows®软件平台开发的“SHOULD-NOT-BLEED-SCORE”应用程序。
本研究旨在开发一个用户友好的应用程序，对患者的出血风险进行分层。我们在先前研究中使用的统计模型侧重于检测出血风险较低的CABG患者。这种方法背后的基本原理是识别出出血风险较低的CABG患者亚组。通过识别出血风险较低的患者，我们可以定义一个可能无需进行输血治疗的患者亚组。我们基于风险建模开发了一个Windows平台应用程序，该模型是我们先前对2010年1月至2018年1月期间接受择期CABG的1426例患者计算得出的。
SHOULD-NOT-BLEED-SCORE风险评分是为Windows软件平台开发的。应用程序开发使用了基于多变量分析的数学模型。进入评分系统的变量包括：年龄；体重指数；慢性肾功能衰竭；术前氯吡格雷暴露情况；术前红细胞计数；术前纤维蛋白原水平；术前Multiplate ASPI检测曲线下面积（AUC）单位。SHOULD-NOT-BLEED-SCORE能够识别/预测无过度出血风险的患者，具有很强的鉴别性能（受试者操作特征曲线（ROC）分析AUC为72.3%，p < 0.001）。
SHOULD-NOT-BLEED风险评分应用程序可能有助于术前风险筛查过程。术前评分系统可以充分解决与不必要输血相关的临床和经济负担，该系统可检测出出血风险较低、可能无需进行输血治疗的患者。
