Aspirin Resistance Significantly Influences Clinical and Economic Burden in Cardiac Surgery Patients

Petricevic, Mirna; Petričević, Mate; Biočina, Bojan

doi:10.1016/j.athoracsur.2019.08.084

Cited by 3 publications

(3 citation statements)

References 5 publications

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“…We thank Petricevic et al (1) for their interest in our work (2) and their pertinent questions. Firstly, how to define aspirin resistance is contentious and to the best of our knowledge, there is still no consensus on which platelet function test is the best, let alone what cut point for each platelet function test is considered most appropriate in correlation to meaningful clinical outcomes.…”

Section: Aspirin Resistance Significantly Influences Clinical and Economic Burden In Cardiac Surgery Patients (Reply)mentioning

confidence: 94%

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Nicola

2020

The Annals of Thoracic Surgery

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Section: Aspirin Resistance Significantly Influences Clinical and Economic Burden In Cardiac Surgery Patients (Reply)mentioning

confidence: 94%

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Nicola

2020

The Annals of Thoracic Surgery

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“…Transfusion of blood components in CABG patients is primarily empiric resulting in an inevitably wide variability in transfusion rates between different cardiac surgery centers (range 7.8 to 92.8%) [7]. This, in turn, results in a significant economic burden and unnecessary expenditures, be it from transfusion costs or costs related to transfusion associated complications, as well as overhead expenses [8,9].…”

Section: Introductionmentioning

confidence: 99%

Bleeding risk stratification in coronary artery surgery: the should-not-bleed score

Petricevic

Petričević

Pašalić

et al. 2021

J Cardiothorac Surg

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Background 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. Methods 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. Results 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). Conclusion 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.

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“…Transfusion of blood components in CABG patients is primarily empiric resulting inevitably in wide variability in transfusion rates between different cardiac surgery centers (range 7.8% to 92.8%) (4). This in turn results with signi cant economic burden and unnecessary expenditures be it from transfusion costs or costs related to transfusion associated complications, as well as overhead expenses (5,6) When it comes to the hemostatic management, the focus of many researchers, including our research team was to identify the patients at high risk of bleeding who might bene t from more aggressive and more targeted haemostatic management. In patients considered to be at high risk of bleeding, the aim of hemostatic management is to provide targeted and e cient haemostatic treatment (mostly procoagulant blood components).…”

Section: Introductionmentioning

confidence: 99%

Bleeding Risk Stratification in Coronary Artery Surgery the Should-Not-Bleed Score

Petricevic

Petričević

Pašalić

et al. 2020

Preprint

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BackgroundCardiac surgery has an estimated 20% of the total blood transfusions. Of those, 11% were utilized in patients undergoing coronary artery bypass grafting (CABG) with documented wide variability in transfusion rate (7.8% to 92.8%). To address the issue of unnecessary transfusions within CABG population, we developed the model to predict the patients at low risk of bleeding who should not be transfused. Herein we present our “SHOULD-NOT-BLEED-SCORE” application developed for Windows® software platform and based on our previous research.MethodsThis study aimed to develop the user-friendly application that stratifies the 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 among CABG patients subgroup at low risk of bleeding. By identifying patients at low risk of bleeding we can define the subgroup of patients who should not be transfused. We developed the Windows platform application based on risk modelling we previously calculated on 1426 patients undergoing elective CABG from January 2010 to January 2018.ResultsThe SHOULD-NOT-BLEED-SCORE risk score is developed for Windows software platform. The mathematical model 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 (AUC). The SHOULD-NOT-BLEED-SCORE identifies/predicts patients without excessive bleeding with the strong discriminatory performance (ROC analysis AUC 72.3%, p<0.001).ConclusionThe SHOULD-NOT-BLEED risk scoring application may be useful in preoperative risk screening process. The clinical and economic burden associated with unnecessary transfusions may be adequately addressed by preoperative scoring system detecting patients at low risk of bleeding who should not be transfused.

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Aspirin Resistance Significantly Influences Clinical and Economic Burden in Cardiac Surgery Patients

Cited by 3 publications

References 5 publications

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Bleeding risk stratification in coronary artery surgery: the should-not-bleed score

Bleeding Risk Stratification in Coronary Artery Surgery the Should-Not-Bleed Score

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