Preoperative Factors as Predictors of Blood Product Transfusion Requirements in Orthotopic Liver Transplantation

Ghaffaripour, Sina; Mahmoudi, Hilda; Khosravi, Mohammad Bagher; Sahmeddini, Mohammad Ali; Eghbal, Mohammad Hossein; Sattari, Hossein; Kazemi, Kourosh; Malekhosseini, Seyed Ali

doi:10.1177/152692481102100311

Cited by 6 publications

(5 citation statements)

References 18 publications

(14 reference statements)

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“…The MELD score is calculated based on the serum creatinine, bilirubin, and prothrombin time-international normalized ratio (PT-INR). According to the initiation and termination of the massive transfusion protocol [ 23 ], viscoelastic hemostatic assay-guided resuscitation is superior to conventional coagulation assay-guided resuscitation in hemorrhaging trauma patients. However, not all hospitals can use viscoelastic hemostatic assays in clinical settings due to economic and technical constraints.…”

Section: Discussionmentioning

confidence: 99%

Development of Machine Learning Models Predicting Estimated Blood Loss during Liver Transplant Surgery

Park

Lee

et al. 2022

JPM

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The incidence of major hemorrhage and transfusion during liver transplantation has decreased significantly over the past decade, but major bleeding remains a common expectation. Massive intraoperative hemorrhage during liver transplantation can lead to mortality or reoperation. This study aimed to develop machine learning models for the prediction of massive hemorrhage and a scoring system which is applicable to new patients. Data were retrospectively collected from patients aged >18 years who had undergone liver transplantation. These data included emergency information, donor information, demographic data, preoperative laboratory data, the etiology of hepatic failure, the Model for End-stage Liver Disease (MELD) score, surgical history, antiplatelet therapy, continuous renal replacement therapy (CRRT), the preoperative dose of vasopressor, and the estimated blood loss (EBL) during surgery. The logistic regression model was one of the best-performing machine learning models. The most important factors for the prediction of massive hemorrhage were the disease etiology, activated partial thromboplastin time (aPTT), operation duration, body temperature, MELD score, mean arterial pressure, serum creatinine, and pulse pressure. The risk-scoring system was developed using the odds ratios of these factors from the logistic model. The risk-scoring system showed good prediction performance and calibration (AUROC: 0.775, AUPR: 0.753).

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Section: Discussionmentioning

confidence: 99%

Development of Machine Learning Models Predicting Estimated Blood Loss during Liver Transplant Surgery

Park

Lee

et al. 2022

JPM

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“…We recognize that a single, universally applicable method to determine LVT candidates may be difficult to develop and that further validation with multicenter prospective analyses is needed. 12,18,19 Successful prediction of LVT candidates depends not only on the patient's preexisting comorbidities and pretransplant disposition but also on the status of their physiologic reserve. It is important to note that intraoperative events may alter LVT candidacy at any point, and antibody status with blood compatibility should be carefully considered to ensure that adequate reserves exist.…”

Section: Discussionmentioning

confidence: 99%

“…14 Many studies have investigated potential preoperative characteristics that are associated with massive blood loss and therefore necessitate massive blood transfusions in OLT. 1,[4][5][6]9,[12][13][14][16][17][18][19] Factors investigated vary by study and institution but include laboratory values of the recipient and donor, medical history of the organ donor, and recipient preoperative characteristics. Mondanlou and associates found that a transplant recipient's preoperative creatinine level of greater than 1.3 mg/dL positively correlated with massive blood transfusion.…”

Section: Introductionmentioning

confidence: 99%

“…4 An algorithm that is able to accurately predict the likelihood of low-volume intraoperative blood loss has yet to be developed. 6,18,19 Such a tool would enable the tailoring of blood product crossmatching, allocation, and administration to each individual patient. 6,14 The purpose of this study was to determine whether specific preoperative clinical characteristics were associated with low-volume transfusion (LVT), which we defined as transfusion of < 2100 mL of PRBCs intraoperatively.…”

Section: Introductionmentioning

confidence: 99%

“…Accurately predicting LVT would increase patient safety, decrease complications associated with transfusion, decrease blood handling, improve blood management, save time, and decrease costs. 6,8,9,16,17,19 Accurate prediction of intraoperative bleeding would not only benefit patients but would also enable better use and coordination of valuable resources, including crossmatching, PRBC allocation, and decreased transfusion department labor. 4,6,9,12,13,[17][18][19] …”

Section: Introductionmentioning

confidence: 99%

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2016

Exp Clin Transplant

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Objectives: The primary aim of this study was to determine whether specific preoperative clinical characteristics were associated with low-volume transfusion in liver transplant recipients. Low-volume transfusion was defined as transfusion of < 2100 mL of packed red blood cells intraoperatively during liver transplant. The ability to accurately predict lowvolume transfusion could increase patient safety, decrease complications associated with transfusion, improve blood management, and decrease transplant case cost. Materials and Methods: Data were retrieved by retrospective chart review of 266 patients who received a liver transplant at the Mayo Clinic (Jacksonville, FL, USA). The primary outcome was lowvolume transfusion. Associations of preoperative information with low-volume transfusion were explored using single-variable and multivariable logistic regression models; missing data were imputed with the sample median for continuous data and the most frequent category for categorical variables. Results: Low-volume transfusion occurred in 23% of first-time liver transplant recipients (62/266 patients; 95% confidence interval, 18%-29%). History of hepatitis C virus infection (P = .048), history of hepatocellular carcinoma (P = .050), short cold ischemia time (P = .006), and low international normalized ratio (P = .002) were independently associated with low-volume transfusion during liver transplant in a multivariable logistic regression model. Conclusions: Multiple studies have shown increased morbidity and mortality after orthotopic liver transplant when more than 6 U of packed red blood cells are administered within 24 hours of surgical incision. A method to identify low-volume transfusion candidates could help predict patient outcomes, decrease blood handling, and reduce costs. If patients with low-volume transfusion could be identified, fewer blood products would need to be prepared in advance. Although elevated preoperative coagulation parameters decrease the probability of low-volume transfusion, a definitive profile of a low-volume transfusion liver transplant recipient was not established.

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Hemostatic status in liver transplantation: Association between preoperative procoagulants/anticoagulants and postoperative hemorrhaging/thrombosis

et al. 2015

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The delicate rebalanced hemostatic status of liver transplant recipients may lead to both hemorrhagic and thrombotic tendencies in this population. The aim of this study was to investigate the association between pretransplant procoagulants/ anticoagulants and posttransplant bleeding and thrombosis among living donor liver transplant recipients. The study subjects were 403 consecutive recipients with chronic liver disease. Perioperative variables, including preoperative values for procoagulants and anticoagulants, were assessed to determine their association with posttransplant hemorrhaging and thrombosis. There were 35 hemorrhagic complications (9%) and 21 thrombotic complications (5%). In logistic regression analyses, a higher Model for End-Stage Liver Disease score (P 5 0.01) and a lower fibrinogen value (P < 0.001) were independently associated with hemorrhaging, whereas only a lower protein C value (P < 0.001) was independently associated with thrombosis. In a receiver operating characteristic analysis, a low preoperative protein C value (with the most accurate cutoff value being 25%) was a reliable predictor of thrombotic complications after liver transplantation (area under the curve 5 0.921, P < 0.001, sensitivity 5 0.9, specificity 5 0.8). In conclusion, the decreases in both procoagulants and anticoagulants in liver transplant recipients may additively result in a delicate hemostatic balance and predispose patients to both hemorrhagic and thrombotic complications. A lower preoperative protein C value (<25%) was demonstrated to be a significant and reliable predictor of postoperative thrombotic complications in liver transplant recipients. Liver Transpl 21:258-265, 2015. V C 2014 AASLD.

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Preoperative Factors as Predictors of Blood Product Transfusion Requirements in Orthotopic Liver Transplantation

Cited by 6 publications

References 18 publications

Development of Machine Learning Models Predicting Estimated Blood Loss during Liver Transplant Surgery

Development of Machine Learning Models Predicting Estimated Blood Loss during Liver Transplant Surgery

Untitled

Hemostatic status in liver transplantation: Association between preoperative procoagulants/anticoagulants and postoperative hemorrhaging/thrombosis

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