Background: Patients undergoing cardiac surgery are subject to severe alterations of the coagulation system. The four cardiac surgery centers in Tuscany (Italy)structured and shared an algorithm (Granducato Patient Blood Management algorithm, G-PBMa)with predefined interventions for patient blood management. The aim of the study is to analyze the impact of that algorithm on the transfusion needs and bleeding-related outcomes in a large patient population. Methods: Multicenter retrospective observational study on 3839 patients undergoing cardiac surgery at the four cardiac centers in Tuscany. The G-PBMa was released at the end of 2015 and it was structured in three parts: pre-, intra-, and post-operative. The year 2014, before the G-PBMa (1955 patients)and the year 2016 (1884 patients)after the G-PBMa in place were compared. Logistic regression analyses were used. Results: The main changes introduced were the routine application of viscoelastic tests in bleeding patients (+72%)and the use of fibrinogen and prothrombin complex concentrate (+67%). The G-PBMa resulted in a significant reduction in the overall transfusion rate and in the transfusion rate of the separate blood products (relative risk for transfusions: 0.75, 95% confidence interval 0.65–0.85, P = 0.001). For preoperative hemoglobin values of between 8 and 10 g/dL, the absolute difference in RBC transfusion rate before and after the G-PBMa introduction ranged around 15%–17%. The G-PBMa introduction determined lower (P = 0.02)chest drain blood loss, lower (P = 0.001)postoperative acute kidney injury and shorter (P = 0.001)hospital stay. Conclusions: The G-PBMa was effective in reducing blood loss, transfusion requirements, and resulted in a better outcome.

Scolletta, S., Simioni, P., Campagnolo, V., Celiento, M., Fontanari, P., Guadagnucci, A., et al. (2019). Patient blood management in cardiac surgery: The “Granducato algorithm”. INTERNATIONAL JOURNAL OF CARDIOLOGY, 289, 37-42 [10.1016/j.ijcard.2019.01.025].

Patient blood management in cardiac surgery: The “Granducato algorithm”

Scolletta S.;
2019-01-01

Abstract

Background: Patients undergoing cardiac surgery are subject to severe alterations of the coagulation system. The four cardiac surgery centers in Tuscany (Italy)structured and shared an algorithm (Granducato Patient Blood Management algorithm, G-PBMa)with predefined interventions for patient blood management. The aim of the study is to analyze the impact of that algorithm on the transfusion needs and bleeding-related outcomes in a large patient population. Methods: Multicenter retrospective observational study on 3839 patients undergoing cardiac surgery at the four cardiac centers in Tuscany. The G-PBMa was released at the end of 2015 and it was structured in three parts: pre-, intra-, and post-operative. The year 2014, before the G-PBMa (1955 patients)and the year 2016 (1884 patients)after the G-PBMa in place were compared. Logistic regression analyses were used. Results: The main changes introduced were the routine application of viscoelastic tests in bleeding patients (+72%)and the use of fibrinogen and prothrombin complex concentrate (+67%). The G-PBMa resulted in a significant reduction in the overall transfusion rate and in the transfusion rate of the separate blood products (relative risk for transfusions: 0.75, 95% confidence interval 0.65–0.85, P = 0.001). For preoperative hemoglobin values of between 8 and 10 g/dL, the absolute difference in RBC transfusion rate before and after the G-PBMa introduction ranged around 15%–17%. The G-PBMa introduction determined lower (P = 0.02)chest drain blood loss, lower (P = 0.001)postoperative acute kidney injury and shorter (P = 0.001)hospital stay. Conclusions: The G-PBMa was effective in reducing blood loss, transfusion requirements, and resulted in a better outcome.
2019
Scolletta, S., Simioni, P., Campagnolo, V., Celiento, M., Fontanari, P., Guadagnucci, A., et al. (2019). Patient blood management in cardiac surgery: The “Granducato algorithm”. INTERNATIONAL JOURNAL OF CARDIOLOGY, 289, 37-42 [10.1016/j.ijcard.2019.01.025].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11365/1119999
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