Development and validation of Transfusion Risk Understanding Scoring Tool (TRUST) to stratify cardiac surgery patients according to their blood transfusion needs

Safety outcomes of anti-platelet therapy post coronary artery bypass graft surgery: A systematic review and network meta-analysis of randomized control trials

BACKGROUND

Antiplatelet therapy is used to decrease the risk of graft failure post coronary artery bypass graft surgery. We aimed to compare dual antiplatelet therapy (DAPT) with monotherapy along with a comparison of Aspirin, Ticagrelor, Aspirin+Ticagrelor (A+T) and Aspirin+Clopidogrel (A+C) to determine the major and minor bleeding risk, risk of postoperative myocardial infarction (MI), stroke, and all-cause mortality (ACM).

METHODS

Randomized Controlled Trials comparing the four groups were included. Odds ratio (OR) and Absolute Risk (AR) were employed to assess the mean and standard deviation (SD) with 95% confidence intervals (CI). The Bayesian random-effects model was used for statistical analysis. Risk difference and Cochran Q tests were used to calculate rank probability (RP) and heterogeneity, respectively.

RESULTS

We included 10 trials, consisting of 21 arms and 3926 patients. For the risk of major and minor bleed, A + T and Ticagrelor showed the lowest mean value of 0.040 (0.043) and 0.067 (0.073), respectively, and the highest RP of being the safest group. While a direct comparison between DAPT and monotherapy resulted in an OR of 0.57 [0.34, 0.95] for the risk of minor bleed. A + T was found to have the highest RP and the lowest mean value in terms of ACM, MI, and stroke.

CONCLUSION

No significant difference was found between monotherapy or dual-antiplatelet therapy for the major bleeding risk safety outcome, however DAPT was found to have a significantly higher rate of minor bleeding complications post-CABG. DAPT should be considered as the antiplatelet modality of choice post-CABG.

Development and validation of a machine learning prediction model for perioperative red blood cell transfusions in cardiac surgery

OBJECTIVE

Several machine learning (ML) models have been used in perioperative red blood cell (RBC) transfusion risk for cardiac surgery with limited generalizability and no external validation. Hence, we sought to develop and comprehensively externally validate a ML model in a large dataset to estimate RBC transfusion in cardiac surgery with cardiopulmonary bypass (CPB).

DESIGN

A retrospective analysis of a multicenter clinical trial (NCT03782350).

PATIENTS

The study patients who underwent cardiac surgery with CPB came from four cardiac centers in China and Medical Information Mart for Intensive Cared (MIMIC-IV) dataset.

MEASUREMENTS

Data from Fuwai Hospital were used to develop an individualized prediction model for RBC transfusion. The model was externally validated in the data from three other centers and MIMIC-IV dataset. Twelve models were constructed.

MAIN RESULTS

A total of 11,201 eligible patients were included in the model development (2420 in Fuwai Hospital) and external validation (563 in the other three centers and 8218 in the MIMIC-IV dataset). A significant difference was observed between the Logistic Regression and CatboostClassifier (0.72 Vs. 0.74, P = 0.031) or RandomForestClassifier (0.72 Vs. 0.75 p = 0.012) in the external validation and MIMIV-IV datasets (age ≤ 70:0.63 Vs. 0.71, p < 0.001; age > 70:0.63 Vs. 0.70, 0.63 Vs. 0.71, p < 0.001). The CatboostClassifier and RandomForestClassifier model was comparable in development (0.83 Vs. 0.82, p = 0.419), external (0.74 Vs. 0.75, p = 0.268), and MIMIC-IV datasets (age ≤ 70: 0.71 Vs. 0.71, p = 0.574; age > 70: 0.70 Vs. 0.71, p = 0.981). Of note, they outperformed other ML models with excellent discrimination and calibration. The CatboostClassifier and RandomForestClassifier models achieved higher area under precision-recall curve and lower brier loss score in validation and MIMIC-IV datasets. Additionally, we confirmed that low preoperative hemoglobin, low body mass index, old age, and female sex increased the risk of RBC transfusion.

CONCLUSIONS

In our study, enrolling a broad range of cardiovascular surgeries with CPB and utilizing a restrictive RBC transfusion strategy, robustly validates the generalizability of ML algorithms for predicting RBC transfusion risk. Notably, the CatboostClassifier and RandomForestClassifier exhibit strong external clinical applicability, underscoring their potential for widespread adoption. This study provides compelling evidence supporting the efficacy and practical value of ML-based approaches in enhancing transfusion risk prediction in clinical practice.

Predicting the Need for Blood Transfusions in Cardiac Surgery: A Comparison between Machine Learning Algorithms and Established Risk Scores in the Brazilian Population

INTRODUCTION

Blood transfusion is a common practice in cardiac surgery, despite its well-known negative effects. To mitigate blood transfusion-associated risks, identifying patients who are at higher risk of needing this procedure is crucial. Widely used risk scores to predict the need for blood transfusions have yielded unsatisfactory results when validated for the Brazilian population.

METHODS

In this retrospective study, machine learning (ML) algorithms were compared to predict the need for blood transfusions in a cohort of 495 cardiac surgery patients treated at a Brazilian reference service between 2019 and 2021. The performance of the models was evaluated using various metrics, including the area under the curve (AUC), and compared to the commonly used Transfusion Risk and Clinical Knowledge (TRACK) and Transfusion Risk Understanding Scoring Tool (TRUST) scoring systems.

RESULTS

The study found that the model had the highest performance, achieving an AUC of 0.7350 (confidence interval [CI]: 0.7203 to 0.7497). Importantly, all ML algorithms performed significantly better than the commonly used TRACK and TRUST scoring systems. TRACK had an AUC of 0.6757 (CI: 0.6609 to 0.6906), while TRUST had an AUC of 0.6622 (CI: 0.6473 to 0.6906).

CONCLUSION

The findings of this study suggest that ML algorithms may offer a more accurate prediction of the need for blood transfusions than the traditional scoring systems and could enhance the accuracy of predicting blood transfusion requirements in cardiac surgery patients. Further research could focus on optimizing and refining ML algorithms to improve their accuracy and make them more suitable for clinical use.

Development and validation of a postoperative bleeding complications prediction model in infective endocarditis

OBJECTIVES

Bleeding complications are one of the most serious postoperative complications after cardiac surgery and are associated with high mortality, especially in patients with infective endocarditis (IE). Our objectives were to identify the risk factors and develop a prediction model for postoperative bleeding complications in IE patients.

METHODS

The clinical data of IE patients treated from October 2013 to January 2022 were reviewed. Multivariate logistic regression analysis was used to evaluate independent risk factors for postoperative bleeding complications and develop a prediction model accordingly. The prediction model was verified in a temporal validation cohort. The performance of the model was evaluated in terms of its discrimination power, calibration, precision, and clinical utility.

RESULTS

A total of 423 consecutive patients with IE who underwent surgery were included in the final analysis, including 315 and 108 patients in the training cohort and validation cohort, respectively. Four variables were selected for developing a prediction model, including platelet counts, systolic blood pressure, heart failure and vegetations on the mitral and aortic valves. In the training cohort, the model exhibited excellent discrimination power (AUC = 0.883), calibration (Hosmer-Lemeshow test, P = 0.803), and precision (Brier score = 0.037). In addition, the model also demonstrated good discrimination power (AUC = 0.805), calibration (Hosmer-Lemeshow test, P = 0.413), and precision (Brier score = 0.067) in the validation cohort.

CONCLUSIONS

We developed and validated a promising risk model with good discrimination power, calibration, and precision for predicting postoperative bleeding complications in IE patients.

Red Blood Cell Transfusion Requirements Before and After Implementation of a Perioperative Patient Blood Management Program in Adult Patients Undergoing Cardiac Surgery. A Before and After Observational Study

OBJECTIVES

Anemia and transfusion are common in cardiac surgery patients, and are associated with significant morbidity and mortality. Multiple perioperative interventions have been described to reduce blood transfusion, but are rarely combined altogether. The aim of this study was to compare the incidence of red blood cell (RBC) transfusion in adult patients undergoing cardiac surgery before and after the implementation of a perioperative patient blood management (PBM) program.

DESIGN

Before-and-after observational study.

SETTING

Single-center French university teaching hospital.

PARTICIPANTS

Adult patients scheduled for cardiac surgery.

INTERVENTIONS

Perioperative patient blood management program including pre-, intra-, and postoperative interventions aimed at identifying and correcting anemia, minimizing blood loss during surgery, and optimizing coagulation.

MEASUREMENTS AND MAIN RESULTS

Four hundred thirty-four patients were included in the study from January 2021 to July 2022. The incidence of perioperative RBC transfusion (intraoperatively and during the first 2 postoperative days) was significantly reduced from 43% (90/213) in the pre-PBM period to 27% (60/221) in the post-PBM period (p < 0.001). The application of a PBM program was associated with a reduction in perioperative RBC transfusion by multivariate analysis (odds ratio 0.55, 95% CI 0.36-0.85, p = 0.007), and was associated with a reduction in the median number of RBC units transfused within transfused patients (p = 0.025). These effects persisted at day 30 after surgery (p = 0.029).

CONCLUSION

A perioperative PBM program in adult patients undergoing cardiac surgery was associated with a significant reduction in perioperative RBC transfusion, which persisted at day 30.

Evaluation of the efficacy and safety of amustaline/glutathione pathogen-reduced RBCs in complex cardiac surgery: the Red Cell Pathogen Inactivation (ReCePI) study-protocol for a phase 3, randomized, controlled trial

BACKGROUND

Red blood cell (RBC) transfusion is a critical supportive therapy in cardiovascular surgery (CVS). Donor selection and testing have reduced the risk of transfusion-transmitted infections; however, risks remain from bacteria, emerging viruses, pathogens for which testing is not performed and from residual donor leukocytes. Amustaline (S-303)/glutathione (GSH) treatment pathogen reduction technology is designed to inactivate a broad spectrum of infectious agents and leukocytes in RBC concentrates. The ReCePI study is a Phase 3 clinical trial designed to evaluate the efficacy and safety of pathogen-reduced RBCs transfused for acute anemia in CVS compared to conventional RBCs, and to assess the clinical significance of treatment-emergent RBC antibodies.

METHODS

ReCePI is a prospective, multicenter, randomized, double-blinded, active-controlled, parallel-design, non-inferiority study. Eligible subjects will be randomized up to 7 days before surgery to receive either leukoreduced Test (pathogen reduced) or Control (conventional) RBCs from surgery up to day 7 post-surgery. The primary efficacy endpoint is the proportion of patients transfused with at least one study transfusion with an acute kidney injury (AKI) diagnosis defined as any increased serum creatinine (sCr) level ≥ 0.3 mg/dL (or 26.5 µmol/L) from pre-surgery baseline within 48 ± 4 h of the end of surgery. The primary safety endpoints are the proportion of patients with any treatment-emergent adverse events (TEAEs) related to study RBC transfusion through 28 days, and the proportion of patients with treatment-emergent antibodies with confirmed specificity to pathogen-reduced RBCs through 75 days after the last study transfusion. With ≥ 292 evaluable, transfused patients (> 146 per arm), the study has 80% power to demonstrate non-inferiority, defined as a Test group AKI incidence increase of no more than 50% of the Control group rate, assuming a Control incidence of 30%.

DISCUSSION

RBCs are transfused to prevent tissue hypoxia caused by surgery-induced bleeding and anemia. AKI is a sensitive indicator of renal hypoxia and a novel endpoint for assessing RBC efficacy. The ReCePI study is intended to demonstrate the non-inferiority of pathogen-reduced RBCs to conventional RBCs in the support of renal tissue oxygenation due to acute anemia and to characterize the incidence of treatment-related antibodies to RBCs.

Using machine learning to predict bleeding after cardiac surgery

OBJECTIVES

The primary objective was to predict bleeding after cardiac surgery with machine learning using the data from the Australia New Zealand Society of Cardiac and Thoracic Surgeons Cardiac Surgery Database, cardiopulmonary bypass perfusion database, intensive care unit database and laboratory results.

METHODS

We obtained surgical, perfusion, intensive care unit and laboratory data from a single Australian tertiary cardiac surgical hospital from February 2015 to March 2022 and included 2000 patients undergoing cardiac surgery. We trained our models to predict either the Papworth definition or Dyke et al.'s universal definition of perioperative bleeding. Our primary outcome was the performance of our machine learning algorithms using sensitivity, specificity, positive and negative predictive values, accuracy, area under receiver operating characteristics curve (AUROC) and area under precision-recall curve (AUPRC).

RESULTS

Of the 2000 patients undergoing cardiac surgery, 13.3% (226/2000) had bleeding using the Papworth definition and 17.2% (343/2000) had moderate to massive bleeding using Dyke et al.'s definition. The best-performing model based on AUPRC was the Ensemble Voting Classifier model for both Papworth (AUPRC 0.310, AUROC 0.738) and Dyke definitions of bleeding (AUPRC 0.452, AUROC 0.797).

CONCLUSIONS

Machine learning can incorporate routinely collected data from various datasets to predict bleeding after cardiac surgery.

A model based on electronic health records to predict transfusion events in on-pump cardiac surgery

Perioperative blood transfusion is costly and raises safety concerns. We developed and validated a model for predicting minor, moderate, or major transfusion given to patients during on-pump cardiac procedures based on two centers' database. Model performance incorporating 7 variables on the development set had an AUC of 0.803 [95% CI, 0.790-0.815] for minor transfusion; moderate transfusion, giving an AUC of 0.822 (95% CI, 0.803-0.841); and major transfusion, giving an AUC of 0.813 (95% CI, 0.759-0.866). Model performance on the validation set had an AUC of 0.739 (95% CI 0.714-0.765), 0.730 (95% CI 0.702-0.758), and 0.713 (95% CI 0.677-0.749), respectively. A model based entirely on readily available electronic health records can accurately predict intraoperative minor, moderate, or major transfusion and provide individualized transfusion risk profiles before surgery among those on-pump cardiac surgical patients, and may help guide patient management.

Impact of intraoperative blood products, fluid administration, and persistent hypothermia on bleeding leading to reexploration after cardiac surgery

OBJECTIVE

Risk factors for severe postoperative bleeding after cardiac surgery remain multiple and incompletely elucidated. We evaluated the impact of intraoperative blood product transfusions, intravenous fluid administration, and persistently low core body temperature (CBT) at intensive care unit arrival on risk of perioperative bleeding leading to reexploration.

METHODS

We retrospectively queried our tertiary care center's Society of Thoracic Surgeons Institutional Database for all index, on-pump, adult cardiac surgery patients between July 2016 and September 2022. Intraoperative fluid (crystalloid and colloid) and blood product administrations, as well as perioperative CBT data, were harvested from electronic medical records. Linear and nonlinear mixed models, treating surgeon as a random effect to account for inter-surgeon practice differences, were used to assess the association between above factors and reexploration for bleeding.

RESULTS

Of 4037 patients, 151 (3.7%) underwent reexploration for bleeding. Reexplored patients experienced remarkably greater postoperative morbidity (23% vs 6%, P < .001) and 30-day mortality (14% vs 2%, P < .001). In linear models, progressively increasing IV crystalloid administration (adjusted odds ratio, 1.11, 95% confidence interval, 1.03-1.19) and decreasing CBT on intensive care unit arrival (adjusted odds ratio, 1.20; 95% confidence interval, 1.05-1.37) were associated with greater risk of bleeding leading to reexploration. Nonlinear analysis revealed increasing risk after ∼6 L of crystalloid administration and a U-shaped relationship between CBT and reexploration risk. Intraoperative blood product transfusion of any kind was not associated with reexploration.

CONCLUSIONS

We found evidence of both dilution- and hypothermia-related effects associated with perioperative bleeding leading to reexploration in cardiac surgery. Interventions targeting modification of such risk factors may decrease the rate this complication.

Development of a Novel Prediction Model for Red Blood Cell Transfusion Risk in Cardiac Surgery

BACKGROUND

Cardiac surgery is a complex and invasive procedure that often requires blood transfusions to replace the blood lost during surgery. Blood products are a scarce and expensive resource. Therefore, it is essential to develop a standardized approach to determine the need for blood transfusions in cardiac surgery. The main objective of our study is to develop a simple prediction model for determining the risk of red blood cell transfusion in cardiac surgery.

METHODS

Retrospective cohorts of adult patients who underwent cardiac surgery between 2017 and 2019 were studied to identify hypothetical predictors of blood transfusion. Finally, a multivariable logistic regression model was developed to predict the risk of transfusion in cardiac surgery using the AUC and the Hosmer-Lemeshow goodness-of-fit test.

RESULTS

We included 1234 patients who underwent cardiac surgery. Of the entire cohort, 875 patients underwent a cardiac procedure 69.4% [CI 95% (66.8%; 72.0%)]; 119 patients 9.6% [CI 95% (8.1%; 11.4%)] underwent a combined procedure, and 258 patients 20.9% [CI 95% (18.7; 23.2)] underwent other cardiac procedures. The median perioperative hemoglobin was 13.0 mg/dL IQR (11.7; 14.2). The factors associated with the risk of transfusion were age > 60 years OR 1.37 CI 95% (1.02; 1.83); sex female OR 1.67 CI 95% (1.24; 2.24); BMI > 30 OR 1.46 (1.10; 1.93); perioperative hemoglobin < 14 OR 2.11 to 51.41 and combined surgery OR 3.97 CI 95% (2.19; 7.17). The final model shows an AUC of 80.9% for the transfusion risk prediction [IC 95% (78.5-83.3%)]; p < 0.001].

CONCLUSIONS

We have developed a model with good discriminatory ability, which is more parsimonious and efficient than other models.

A transfusion risk stratification score to facilitate quality management in cardiopulmonary bypass

BACKGROUND

Our previous showed that a blood management program in the cardiopulmonary bypass (CPB) department, reduced red blood cell (RBC) transfusion and complications, but assessing transfusion practice solely based on transfusion rates was insufficient. This study aimed to design a risk stratification score to predict perioperative RBC transfusion to guide targeted measures for on-pump cardiac surgery patients.

STUDY DESIGN AND METHODS

We analyzed data from 42,435 adult cardiac patients. Eight predictors were entered into the final model including age, sex, anemia, New York Heart Association classification, body surface area, cardiac surgery history, emergency surgery, and surgery type. We then simplified the score to an integer-based system. The area under the receiver operating characteristic curve (AUC), Hosmer-Lemeshow goodness-of-fit test, and a calibration curve were used for its performance test. The score was compared to existing scores.

RESULTS

The final score included eight predictors. The AUC for the model was 0.77 (95% CI, 0.76-0.77) and 0.77 (95% CI, 0.76-0.78) in the training and test set, respectively. The calibration curves showed a good fit. The risk score was finally grouped into low-risk (score of 0-13 points), medium-risk (14-19 points), and high-risk (more than 19 points). The score had better predictive power compared to the other two existing risk scores.

DISCUSSION

We developed an effective risk stratification score with eight variables to predict perioperative RBC transfusion for on-pump cardiac surgery. It assists perfusionists in proactively preparing blood conservation measures for high-risk patients before surgery.

Large volume acute normovolemic hemodilution in patients undergoing cardiac surgery with intermediate-high risk of transfusion: A randomized controlled trial

STUDY OBJECTIVE

To investigate whether large volume acute normovolemic hemodilution (L-ANH), compared with moderate acute normovolemic hemodilution (M-ANH), can reduce perioperative allogeneic blood transfusion in patients with intermediate-high risk of transfusion during cardiac surgery with cardiopulmonary bypass (CPB).

DESIGN

Prospective randomized controlled trial.

SETTING

University hospital.

PATIENTS

Patients with transfusion risk understanding scoring tool ("TRUST") ≥2 points undergoing cardiac surgery with CPB in the Second Affiliated Hospital of Zhejiang University from May 2020 to January 2021 were included.

INTERVENTIONS

The patients were randomly assigned with a 1:1 ratio to M-ANH (5 to 8 mL/kg) or L-ANH (12 to 15 mL/kg).

MEASUREMENTS

The primary outcome was perioperative red blood cell (RBC) transfusion units. The composite outcome included new-onset atrial fibrillation, pulmonary infection, cardiac surgery associated acute kidney injury (CSA-AKI) class ≥2, surgical incision infection, postoperative excessive bleeding, and resternotomy.

MAIN RESULTS

Total 159 patients were screened and 110 (55 L-ANH and 55 M-ANH) were included for final analysis. Removed blood volume of L-ANH is significantly higher than M-ANH (886 ± 152 vs. 395 ± 86 mL, P < 0.001). Perioperative RBC transfusion was median 0 unit ([25th, 75th] percentiles: 0-4.4) in M-ANH group vs. 0 unit ([25th, 75th] percentiles: 0-2.0) in L-ANH group (P = 0.012) and L-ANH was associated with lower incidence of transfusion (23.6% vs. 41.8%, P = 0.042, rate difference: 0.182, 95% confidence interval [0.007-0.343]). The incidence of postoperative excessive bleeding was significantly lower in L-ANH vs. M-ANH (3.6% vs. 18.2%, P = 0.029, rate difference: 0.146, 95% confidence interval [0.027-0.270]) without significant difference for other second outcomes. The volume of ANH was inversely related to perioperative RBC transfusion units (Spearman r = -0.483, 95% confidence interval [-0.708 to -0.168], P = 0.003), and L-ANH in cardiac surgery was associated with a significantly reduced risk of perioperative RBC transfusion (odds ratio: 0.43, 95% confidence interval: 0.19-0.98, P = 0.044).

CONCLUSIONS

Compared with M-ANH, L-ANH during cardiac surgery inclined to be associated with reduced perioperative RBC transfusion and the volume of RBC transfusion was inversely proportional to the volume of ANH. In addition, LANH during cardiac surgery was associated with a lower incidence of postoperative excessive bleeding.

Impact of Red Blood Cell Transfusion on In-hospital Mortality of Isolated Coronary Artery Bypass Graft Surgery: A Retrospective Observational Study of French Nationwide 3-year Cohort

OBJECTIVE

To assess the relationship between red blood cell (RBC) transfusion exposure and in-hospital mortality after isolated coronary artery bypass graft (CABG) surgery.

BACKGROUND

RBC transfusion was commonly used to treat anemia in isolated CABG surgery, but transfusion was found an independent risk factor of postoperative mortality; recent guidelines on patient blood management strategy issued in the last decade may have changed transfusion incidence and related mortality.

METHODS

A retrospective cohort study was conducted from the National database on patients' hospital discharge reports. Consecutive adult patients who underwent isolated CABG surgery in France from January 1, 2016, to December 31, 2018, were included. The primary outcome was the in-hospital mortality rate. RBC transfusion during the hospital stay was identified by specific codes and ordered as categorical variables (no, moderate, or massive transfusion).

RESULTS

A total of 37,498 participants were studied [mean (SD) age, 66.5 (9.6) years, 31,587 (84.2%) were men]. In-hospital mortality rate was 1.45% (n=541) and RBC transfusion rate was 9.4% (n=3521). In-hospital deaths were more frequent among transfused patients [1.06% (361) if no transfusion up to 10.2% (n=113) if massive transfusion]. After adjustment for confounding variables, RBC transfusion remained a significant independent factor of in-hospital mortality: odds ratio=1.66 (95% confidence interval: 1.27-2.19, P <0.001) for moderate transfusion, 6.40 (95% confidence interval: 5.07-8.09, P <0.001) if massive.

CONCLUSIONS AND RELEVANCE

Despite a modest patients' exposure to transfusion, this study suggests that RBC administration is an independent factor of in-hospital mortality in isolated CABG surgery.

Systematic review highlights high risk of bias of clinical prediction models for blood transfusion in patients undergoing elective surgery

BACKGROUND

Blood transfusion can be a lifesaving intervention after perioperative blood loss. Many prediction models have been developed to identify patients most likely to require blood transfusion during elective surgery, but it is unclear whether any are suitable for clinical practice.

STUDY DESIGN AND SETTING

We conducted a systematic review, searching MEDLINE, Embase, PubMed, The Cochrane Library, Transfusion Evidence Library, Scopus, and Web of Science databases for studies reporting the development or validation of a blood transfusion prediction model in elective surgery patients between January 1, 2000 and June 30, 2021. We extracted study characteristics, discrimination performance (c-statistics) of final models, and data, which we used to perform risk of bias assessment using the Prediction model risk of bias assessment tool (PROBAST).

RESULTS

We reviewed 66 studies (72 developed and 48 externally validated models). Pooled c-statistics of externally validated models ranged from 0.67 to 0.78. Most developed and validated models were at high risk of bias due to handling of predictors, validation methods, and too small sample sizes.

CONCLUSION

Most blood transfusion prediction models are at high risk of bias and suffer from poor reporting and methodological quality, which must be addressed before they can be safely used in clinical practice.

The effects of plasma to red blood cells transfusion ratio on in-hospital mortality in patients with acute type A aortic dissection

Background

Blood transfusion is a frequent and necessary practice in acute type A aortic dissection (AAAD) patients, but the effect of plasma/red blood cells (RBCs) ratio on mortality remains unclear. The aim of this study is to investigate the association between plasma/RBCs transfusion ratio and in-hospital mortality in patients with AAAD.

Methods

Patients were admitted to Xiangya Hospital of Central South University from January 1, 2016 to December 31, 2021. Clinical parameters were recorded. Multivariate Cox regression model was used to analyze the association between transfusion and in-hospital mortality. We used the smooth curve fitting and segmented regression model to assess the threshold effect between plasma/RBCs transfusion ratio and in-hospital mortality in patients with AAAD.

Results

The volumes of RBCs [14.00 (10.12-20.50) unit] and plasma [19.25 (14.72-28.15) unit] transfused in non-survivors were significantly higher than in survivors [RBCs: 8.00 (5.50-12.00) unit]; plasma: [10.35 (6.50-15.22) unit]. Multivariate Cox regression analysis showed plasma transfusion was an independent risk factor of in-hospital mortality. Adjusted HR was 1.03 (95% CI: 0.96-1.11) for RBCs transfusion and 1.08 (95% CI: 1.03-1.13) for plasma transfusion. In the spline smoothing plot, mortality risk increased with plasma/RBCs transfusion ratio leveling up to the turning point 1. Optimal plasma/RBCs transfusion ratio with least mortality risk was 1. When the plasma/RBCs ratio was <1 (adjusted HR per 0.1 ratio: 0.28, 95% CI per 0.1 ratio: 0.17-0.45), mortality risk decreased with the increase of ratio. When the plasma/RBCs ratio was 1-1.5 (adjusted HR per 0.1 ratio: 2.73, 95% CI per 0.1 ratio:1.13-6.62), mortality risk increased rapidly with the increase of ratio. When the plasma/RBCs ratio was >1.5 (adjusted HR per 0.1 ratio: 1.09, 95% CI per 0.1 ratio:0.97-1.23), mortality risk tended to reach saturation, and increased non-significantly with the increase of ratio.

Conclusion

A 1:1 plasma/RBCs ratio was associated with the lowest mortality in the patients with AAAD. And non-linear relationship existed between plasma/RBCs ratio and mortality.

Platelet Transfusion After Cardiac Surgery

OBJECTIVES

To investigate the independent association of platelet transfusion with hospital mortality and key relevant clinical outcomes in cardiac surgery.

DESIGN

A single-center, propensity score-matched, retrospective, cohort study.

SETTING

At an American tertiary teaching hospital data from the Medical Information Mart for Intensive Care III and IV databases from 2001 to 2019.

PARTICIPANTS

Consecutive adults undergoing coronary artery bypass graft and/or cardiac valvular surgery.

INTERVENTIONS

Platelet transfusion during perioperative intensive care unit (ICU) admission.

MEASUREMENTS AND MAIN RESULTS

Overall, 12,043 adults met the study inclusion criteria. Of these, 1,621 (13.5%) received apheresis-leukoreduced platelets, with a median of 1.19 units per recipient (IQR: 0.93-1.19) at a median of 1.78 hours (IQR: 0.75-4.25) after ICU admission. The platelet count was measured in 1,176 patients (72.5%) before transfusion, with a median count of 120 × 10⁹/L (IQR: 89.0-157.0), and only 53 (3.3%) had platelet counts below 50 × 10⁹/L. After propensity matching of 1,046 platelet recipients with 1,046 controls, perioperative platelet transfusion carried no association with in-hospital mortality (odds ratio [OR]: 1.28; 99% CI: 0.49-3.35; p = 0.4980). However, it was associated with a pattern of decreased odds of suspected infection (eg, respiratory infection, urinary tract infection, septicaemia, or other; OR: 0.70; 99% CI: 0.50-0.97; p = 0.0050), days in the hospital (adjusted mean difference [AMD]: 0.86; 99% CI: -0.27 to 1.98; p = 0.048), or days in intensive care (AMD 0.83; 99% CI: -0.15 to 1.82; p = 0.0290).

CONCLUSIONS

Platelet transfusion was not associated with hospital mortality, but it was associated with decreased odds of suspected infection and with shorter ICU and hospital stays.

Cost Analysis of Aprotinin Reintroduction in French Cardiac Surgery Centres: A Real-World Data-Based Analysis

INTRODUCTION

The European Medicines Agency restored aprotinin (APR) use for preventing blood loss in patients undergoing isolated coronary artery bypass graft (iCABG) in 2016 but requested the collection of patient and surgery data in a registry (NAPaR). The aim of this analysis was to evaluate the impact of APR reintroduction in France on the main hospital costs (operating room, transfusion and intensive unit stay) compared to the current use of tranexamic acid (TXA), which was the only antifibrinolytic available before APR reinstatement.

METHODS

A multicenter before-after post-hoc analysis to compare APR and TXA was carried out in four French university hospitals. APR use followed the ARCOTHOVA (French Association of Cardiothoracic and Vascular Anesthetists) protocol, which had framed three main indications in 2018. Data from 236 APR patients were retrieved from the NAPaR (N = 874); 223 TXA patients were retrospectively retrieved from each center database and matched to APR patients upon indication classes. Budget impact was evaluated using both direct costs associated with antifibrinolytics and transfusion products (within the first 48 h) and other costs such as surgery duration and ICU stay.

RESULTS

The 459 collected patients were distributed as: 17% on-label; 83% off-label. Mean cost per patient until ICU discharge tended to be lower in the APR group versus the TXA group, which resulted in an estimated gross saving of €3136 per patient. These savings concerned operating room and transfusion costs but were mainly driven by reduced ICU stays. When extrapolated to the whole French NAPaR population, the total savings of the therapeutic switch was estimated at around €3 million.

CONCLUSION

The budget impact projected that using APR according to ARCOTHOVA protocol resulted in decreased requirement for transfusion and complications related to surgery. Both were associated with substantial cost savings from the hospital's perspective compared with exclusive use of TXA.

Cryopreserved platelets compared with liquid-stored platelets for the treatment of surgical bleeding: protocol for two multicentre randomised controlled blinded non-inferiority trials (the CLIP-II and CLIPNZ-II trials)

INTRODUCTION

Cryopreservation at -80°C in dimethylsulphoxide extends platelet shelf-life from 7 days to 2 years. Only limited comparative trial data supports the safety and effectiveness of cryopreserved platelets as a treatment for surgical bleeding. Cryopreserved platelets are not currently registered for civilian use in most countries.

METHODS AND ANALYSIS

CLIP-II and CLIPNZ-II are harmonised, blinded, multicentre, randomised, controlled clinical non-inferiority trials comparing bleeding, transfusion, safety and cost outcomes associated with cryopreserved platelets versus conventional liquid platelets as treatment for bleeding in cardiac surgery. CLIP-II is planning to enrol patients in 12 tertiary hospitals in Australia; CLIPNZ-II will recruit in five tertiary hospitals in New Zealand. The trials use near-identical protocols aside from details of cryopreserved platelet preparation. Patients identified preoperatively as being at high risk of requiring a platelet transfusion receive up to three units of study platelets if their treating doctor considers platelet transfusion is indicated. The primary endpoint is blood loss through the surgical drains in the 24 hours following intensive care unit (ICU) admission after surgery. Other endpoints are blood loss at other time points, potential complications, adverse reactions, transfusion and fluid requirement, requirement for procoagulant treatments, time to commencement of postoperative anticoagulants, delay between platelet order and commencement of infusion, need for reoperation, laboratory and point-of-care clotting indices, cost, length of mechanical ventilation, ICU and hospital stay, and mortality. Transfusing 202 (CLIP-II) or 228 (CLIPNZ-II) patients with study platelets will provide 90% power to exclude the possibility of greater than 20% inferiority in the primary endpoint. If cryopreserved platelets are not inferior to liquid-stored platelets, the advantages of longer shelf-life would justify rapid change in clinical practice. Cost-effectiveness analyses will be incorporated into each study such that, should clinical non-inferiority compared with standard care be demonstrated, the hospitals in each country that would benefit most from changing to a cryopreserved platelet blood bank will be known.

ETHICS AND DISSEMINATION

CLIP-II was approved by the Austin Health Human Research Ethics Committee (HREC/54406/Austin-2019) and by the Australian Red Cross Lifeblood Ethics Committee (2019#23). CLIPNZ-II was approved by the New Zealand Southern Health and Disability Ethics Committee (21/STH/66). Eligible patients are approached for informed consent at least 1 day prior to surgery. There is no provision for consent provided by a substitute decision-maker. The results of the two trials will be submitted separately for publication in peer-reviewed journals.

TRIAL REGISTRATION NUMBERS

NCT03991481 and ACTRN12621000271808.

AntiPORT: adaptation of a transfusion prediction score to an Australian cardiac surgery population

Introduction: Risk scoring systems exist to predict perioperative blood transfusion risk in cardiac surgery, but none have been validated in the Australian or New Zealand population. The ACTA-PORT score was developed in the United Kingdom for this purpose. In this study, we validate and recalibrate the ACTA-PORT score in a large national database. Methods: We performed a retrospective validation study using data from the Australian and New Zealand Society of Cardiac and Thoracic Surgeons Database between 1 September 2016 and 31 December 2018. The ACTA-PORT score was calculated using an equivalent of EuroSCORE I. Discrimination and calibration was assessed using area under the receiver operating characteristic (AUROC) curves, Brier scores, and calibration plots. ACTA-PORT was then recalibrated in a development set using logistic regression and the outcome of transfusion to develop new predicted transfusion rates, termed "AntiPORT", using AusSCORE "all procedures" as the regional equivalent of EuroSCORE I. The accuracy of these new predictions was assessed as for ACTA-PORT. Results: 30 388 patients were included in the study at 37 Australian centres. The rate of red blood cell transfusion was 33%. Discrimination of ACTA-PORT was good but calibration was poor, with overprediction of transfusion (AUROC curve, 0.76; 95% CI, 0.75-0.76; Brier score, 0.19). The recalibrated AntiPORT showed significantly improved calibration in both development and validation sets without compromising discrimination (AUROC curve, 0.76; 95% CI, 0.75-0.76; Brier score, 0.18). Conclusions: The AntiPORT is the first red cell transfusion risk scoring system for cardiac surgery patients to be validated using Australian data. It is accurate and simple to calculate. The demonstrated accuracy of AntiPORT may help facilitate benchmarking and future research in patient blood management, as well as providing a useful tool to help clinicians target these resource-saving strategies.

Towards optimized red blood cells ordering prior to cardiac surgery: a single center retrospective study

Background: Cardiac surgery is associated with a high rate of intraoperative transfusion, requiring pre- ordering or ordering of packed red blood cell (PRBC) before surgery. Our institutional strategy is based on a systematic type and screen (T/S) ordering of 3 PRBCs at the blood bank then stored in a dedicated refrigerator in the operating room for each patient scheduled for cardiac surgery. However, these PRBC units are not always transfused and are therefore at risk of destruction if temperature fluctuations are detected during transport and storage processes. In addition, these orders represent a burden for the blood bank. Therefore, it is relevant to move towards a more tailored PRBC order before cardiac surgery and challenge the systematic ordering protocol. Methods: The Transfusion Understanding Scoring Tool (TRUST) and the Transfusion Risk and Clinical Knowledge (TRACK) Score are designed to stratify blood transfusion needs in cardiac surgery. We retrospectively performed both scores for each patient scheduled for cardiac surgery. Then, we compared their performance to predict PRBC transfusion and determined the optimal threshold to optimize the preoperative PRBC order reflecting the needs of our population managed with our local standards. Results: Receiver operating characteristic (ROC) curves for prediction of PRBC transfusion using the two scores were computed for the whole cohort (n=1249). Both scores performed well (areas under ROC curves: 0.81 and 0.82 (95% CI) using the TRACK Score and the TRUST, respectively). A TRUST < 3 identified a subgroup of patients (53.6%) at low risk of transfusion. The availability of 1 T/S PRBC in the OR would cover the needs of the majority (92.5%) of this group. Conclusions: In our institution, the use of the TRUST preoperatively could offer a more tailored T/S PRBC order for the intraoperative period, especially in the low-risk transfusion group.

Role of Omega-6 Fatty Acid Metabolism in Cardiac Surgery Postoperative Bleeding Risk

Cardiac surgery is frequently associated with significant postoperative bleeding. Platelet-dysfunction is the main cardiopulmonary bypass (CPB)-induced hemostatic defect. Not only the number of platelets decreases, but also the remaining are functionally impaired. Although lipid metabolism is crucial for platelet function, little is known regarding platelet metabolic changes associated with CPB-dysfunction. Our aim is to explore possible contribution of metabolic perturbations for platelet dysfunction after cardiac surgery.

DESIGN

Prospective cohort study.

SETTING

Tertiary academic cardiothoracic-surgery ICU.

PATIENTS

Thirty-three patients submitted to elective surgical aortic valve replacement.

INTERVENTIONS

Samples from patients were collected at three time points (preoperative, 6- and 24-hr postoperative). Untargeted metabolic analysis using high-performance liquid chromatography-tandem mass spectrometry was performed to compare patients with significant postoperative bleeding with patients without hemorrhage. Principal component analyses, Wilcoxon matched-pairs signed-rank tests, adjusted to FDR, and pairwise comparison were used to identify pathways of interest. Enrichment and pathway metabolomic complemented the analyses.

MEASUREMENTS AND MAIN RESULTS

We identified a platelet-related signature based on an overrepresentation of changes in known fatty acid metabolism pathways involved in platelet function. We observed that arachidonic acid (AA) levels and other metabolites from the pathway were reduced at 6 and 24 hours, independently from antiagreggation therapy and platelet count. Concentrations of preoperative AA were inversely correlated with postoperative chest tube blood loss but were not correlated with platelet count in the preoperative, at 6 or at 24 hours. Patients with significant postoperative blood-loss had considerably lower values of AA and higher transfusion rates. Values of postoperative interleukin-6 were strongly correlated with AA variability.

CONCLUSIONS AND RELEVANCE

Our observations suggest that an inflammatory-related perturbation of AA metabolism is a signature of cardiac surgery with CPB and that preoperative levels of AA may be more relevant than platelet count to anticipate and prevent postoperative blood loss in patients submitted to cardiac surgery with CPB.

Machine learning-based prediction of massive perioperative allogeneic blood transfusion in cardiac surgery

BACKGROUND

Massive perioperative allogeneic blood transfusion, that is, perioperative transfusion of more than 10 units of packed red blood cells (pRBC), is one of the main contributors to perioperative morbidity and mortality in cardiac surgery. Prediction of perioperative blood transfusion might enable preemptive treatment strategies to reduce risk and improve patient outcomes while reducing resource utilisation. We, therefore, investigated the precision of five different machine learning algorithms to predict the occurrence of massive perioperative allogeneic blood transfusion in cardiac surgery at our centre.

OBJECTIVE

Is it possible to predict massive perioperative allogeneic blood transfusion using machine learning?

DESIGN

Retrospective, observational study.

SETTING

Single adult cardiac surgery centre in Austria between 01 January 2010 and 31 December 2019.

PATIENTS

Patients undergoing cardiac surgery.

MAIN OUTCOME MEASURES

Primary outcome measures were the number of patients receiving at least 10 units pRBC, the area under the curve for the receiver operating characteristics curve, the F1 score, and the negative-predictive (NPV) and positive-predictive values (PPV) of the five machine learning algorithms used to predict massive perioperative allogeneic blood transfusion.

RESULTS

A total of 3782 (1124 female:) patients were enrolled and 139 received at least 10 pRBC units. Using all features available at hospital admission, massive perioperative allogeneic blood transfusion could be excluded rather accurately. The best area under the curve was achieved by Random Forests: 0.810 (0.76 to 0.86) with high NPV of 0.99). This was still true using only the eight most important features [area under the curve 0.800 (0.75 to 0.85)].

CONCLUSION

Machine learning models may provide clinical decision support as to which patients to focus on for perioperative preventive treatment in order to preemptively reduce massive perioperative allogeneic blood transfusion by predicting, which patients are not at risk.

TRIAL REGISTRATION

Johannes Kepler University Ethics Committee Study Number 1091/2021, Clinicaltrials.gov identifier NCT04856618.

Machine learning algorithms to predict major bleeding after isolated coronary artery bypass grafting

Objectives

Postoperative major bleeding is a common problem in patients undergoing cardiac surgery and is associated with poor outcomes. We evaluated the performance of machine learning (ML) methods to predict postoperative major bleeding.

Methods

A total of 1,045 patients who underwent isolated coronary artery bypass graft surgery (CABG) were enrolled. Their datasets were assigned randomly to training (70%) or a testing set (30%). The primary outcome was major bleeding defined as the universal definition of perioperative bleeding (UDPB) classes 3–4. We constructed a reference logistic regression (LR) model using known predictors. We also developed several modern ML algorithms. In the test set, we compared the area under the receiver operating characteristic curves (AUCs) of these ML algorithms with the reference LR model results, and the TRUST and WILL-BLEED risk score. Calibration analysis was undertaken using the calibration belt method.

Results

The prevalence of postoperative major bleeding was 7.1% (74/1,045). For major bleeds, the conditional inference random forest (CIRF) model showed the highest AUC [0.831 (0.732–0.930)], and the stochastic gradient boosting (SGBT) and random forest models demonstrated the next best results [0.820 (0.742–0.899) and 0.810 (0.719–0.902)]. The AUCs of all ML models were higher than [0.629 (0.517–0.641) and 0.557 (0.449–0.665)], as achieved by TRUST and WILL-BLEED, respectively.

Conclusion

ML methods successfully predicted major bleeding after cardiac surgery, with greater performance compared with previous scoring models. Modern ML models may enhance the identification of high-risk major bleeding subpopulations.

HEROES V-A-HEmoRrhagic cOmplications in veno-arterial Extracorporeal life Support-Development and internal validation of a multivariable prediction model in adult patients

BACKGROUND

Risk factors for bleeding complications during extracorporeal life support (ECLS) indicated for cardiac support remain poorly investigated. The aim is to develop and internally validate a prediction model to calculate the risk for bleeding complications in adult patients receiving veno-arterial (V-A) ECLS.

METHODS

Data of the Extracorporeal Life Support Organization registry of adult patients undergoing V-A ECLS between 2010 and 2020 were analyzed. The primary outcome was bleeding complications recorded during V-A ECLS. Multivariable logistic regression with backward stepwise elimination was used to develop the prediction model. Performance of the model was tested by discriminative ability and calibration with receiver operator characteristic, area under the curve, and visual inspection of the calibration plot. Internal validation was performed to detect overfitting of the model.

RESULTS

In total 28 767 adult patients were included, of which 29.0% developed bleeding complications. Sex, body mass index, surgical cannulation, pre-ECLS respiratory and hemodynamic variables, pre-ECLS support and interventions, and different type of diagnosis were included in the prediction model. This prediction model showed a predictive capability with an AUC of 0.66.

CONCLUSION

The model is based on the largest cohort of V-A ECLS patients and is the best available predictive model for bleeding events given the predictors that are available in V-A ECLS compared to current literature. The model can help in identifying patients at high risk for bleeding complications and will help in developing further research and decision-making in terms of anticoagulation management. External validation is warranted to extrapolate this model in the clinical setting.

Development and validation of a machine learning method to predict intraoperative red blood cell transfusions in cardiothoracic surgery

Accurately predicting red blood cell (RBC) transfusion requirements in cardiothoracic (CT) surgery could improve blood inventory management and be used as a surrogate marker for assessing hemorrhage risk preoperatively. We developed a machine learning (ML) method to predict intraoperative RBC transfusions in CT surgery. A detailed database containing time-stamped clinical variables for all CT surgeries from 5/2014-6/2019 at a single center (n = 2410) was used for model development. After random forest feature selection, surviving features were inputs for ML algorithms using five-fold cross-validation. The dataset was updated with 437 additional cases from 8/2019-8/2020 for validation. We developed and validated a hybrid ML method given the skewed nature of the dataset. Our Gaussian Process (GP) regression ML algorithm accurately predicted RBC transfusion amounts of 0 and 1-3 units (root mean square error, RMSE 0.117 and 1.705, respectively) and our GP classification ML algorithm accurately predicted 4 + RBC units transfused (area under the curve, AUC = 0.826). The final prediction is the regression result if classification predicted < 4 units transfused, or the classification result if 4 + units were predicted. We developed and validated an ML method to accurately predict intraoperative RBC transfusions in CT surgery using local data.

A pilot randomized clinical trial of cryopreserved versus liquid-stored platelet transfusion for bleeding in cardiac surgery: The cryopreserved versus liquid platelet-New Zealand pilot trial

BACKGROUND AND OBJECTIVES

Platelets for transfusion have a shelf-life of 7 days, limiting availability and leading to wastage. Cryopreservation at -80°C extends shelf-life to at least 1 year, but safety and effectiveness are uncertain.

MATERIALS AND METHODS

This single centre blinded pilot trial enrolled adult cardiac surgery patients who were at high risk of platelet transfusion. If treating clinicians determined platelet transfusion was required, up to three units of either cryopreserved or liquid-stored platelets intraoperatively or during intensive care unit admission were administered. The primary outcome was protocol safety and feasibility.

RESULTS

Over 13 months, 89 patients were randomized, 23 (25.8%) of whom received a platelet transfusion. There were no differences in median blood loss up to 48 h between study groups, or in the quantities of study platelets or other blood components transfused. The median platelet concentration on the day after surgery was lower in the cryopreserved platelet group (122 × 10³ /μl vs. 157 × 10³ /μl, median difference 39.5 ×10³ /μl, p = 0.03). There were no differences in any of the recorded safety outcomes, and no adverse events were reported on any patient. Multivariable adjustment for imbalances in baseline patient characteristics did not find study group to be a predictor of 24-h blood loss, red cell transfusion or a composite bleeding outcome.

CONCLUSION

This pilot randomized controlled trial demonstrated the feasibility of the protocol and adds to accumulating data supporting the safety of this intervention. Given the clear advantage of prolonged shelf-life, particularly for regional hospitals in New Zealand, a definitive non-inferiority phase III trial is warranted.

Development and Validation of a Transfusion Risk Score for Patients Receiving Maintenance Hemodialysis

BACKGROUND

In patients on dialysis with anemia, avoiding red blood cell transfusions is preferable. We sought to develop and validate a novel transfusion prediction risk score for patients receiving maintenance hemodialysis.

METHODS

This retrospective cohort study used United States Renal Data System data to create a model development cohort (patients who were point prevalent and on hemodialysis on November 1, 2012) and a validation cohort (patients who were point prevalent and on hemodialysis on August 1, 2013). We characterized comorbidity, inflammatory conditions, hospitalizations, anemia and anemia management, iron parameters, intravenous iron use, and vitamin D use during a 6-month baseline period to predict subsequent 3-month transfusion risk. We used logistic least absolute shrinkage and selection operator regression. In an exploratory analysis, model results were used to calculate a score to predict 6- and 12-month hospitalization and mortality.

RESULTS

Variables most predictive of transfusion were prior transfusion, hemoglobin, ferritin, and number of hospital days in the baseline period. The resulting c-statistic in the validation cohort was 0.74, indicating relatively good predictive power. The score was associated with a significantly increased risk of subsequent mortality (hazard ratios 1.0, 1.22, 1.26, 1.54, 1.71, grouped from lowest to highest score), but not with hospitalization.

CONCLUSIONS

We developed a transfusion prediction risk score with good performance characteristics that was associated with mortality. This score could be further developed into a clinically useful application, allowing clinicians to identify patients on hemodialysis most likely to benefit from a timely, proactive anemia treatment approach, with the goal of avoiding red blood cell transfusions and attendant risks of adverse clinical outcomes.

Risk-Prediction Model for Transfusion of Erythrocyte Concentrate During Extracorporeal Circulation in Coronary Surgery

INTRODUCTION

Our objective was to identify preoperative risk factors and to develop and validate a risk-prediction model for the need for blood (erythrocyte concentrate [EC]) transfusion during extracorporeal circulation (ECC) in patients undergoing coronary artery bypass grafting (CABG).

METHODS

This is a retrospective observational study including 530 consecutive patients who underwent isolated on-pump CABG at our Centre over a full two-year period. The risk model was developed and validated by logistic regression and bootstrap analysis. Discrimination and calibration were assessed using the area under the receiver operating characteristic curve (AUC) and the Hosmer-Lemeshow (H-L) test, respectively.

RESULTS

EC transfusion during ECC was required in 91 patients (17.2%). Of these, the majority were transfused with one (54.9%) or two (41.8%) EC units. The final model covariates (reported as odds ratios; 95% confidence interval) were age (1.07; 1.02-1.13), glomerular filtration rate (0.98; 0.96-1.00), body surface area (0.95; 0.92-0.98), peripheral vascular disease (3.03; 1.01-9.05), cerebrovascular disease (4.58; 1.29-16.18), and hematocrit (0.55; 0.48-0.63). The risk model developed has an excellent discriminatory power (AUC: 0,963). The results of the H-L test showed that the model predicts accurately both on average and across the ranges of deciles of risk.

CONCLUSIONS

A risk-prediction model for EC transfusion during ECC was developed, which performed adequately in terms of discrimination, calibration, and stability over a wide spectrum of risk. It can be used as an instrument to provide accurate information about the need for EC transfusion during ECC, and as a valuable adjunct for local improvement of clinical practice. Key Findings: Risk factors with the greatest prediction for EC transfusion. Take-Home Message: The implementation of this model would be an important step in optimizing and improving the quality of surgery.

Association of Plasma Fibrinogen and Thromboelastography With Blood Loss in Complex Cardiac Surgery

Postoperative coagulopathic bleeding is common in cardiac surgery and is associated with increased morbidity and mortality. Ideally, real-time information on in-vivo coagulation should be available. However, up to now it is unclear which perioperative coagulation parameters can be used best to accurately identify patients at increased risk of bleeding. The present study analyzed the associations of perioperative fibrinogen concentrations and whole blood viscoelastic tests with postoperative bleeding in 89 patients undergoing combined cardiac surgery procedures. Postoperative bleeding was recorded until 24 hours after surgery. Regression analyses were performed to establish associations between blood loss and coagulation parameters after cardiopulmonary bypass including a prediction model with known confounding factors for bleeding. Coagulation tests show large changes over the perioperative course with the strongest coagulopathic deviations from baseline after cardiopulmonary bypass. After adjustment for multiple confounders, viscoelastic clot strength instead of fibrinogen concentration showed a similar performance for 24 hour blood loss and a better performance for 6 hour blood loss. This makes intraoperative viscoelastic testing a useful tool to strengthen early clinical decision-making with the potential to reduce perioperative blood transfusions.

Bridging With Extracorporeal Membrane Oxygenation Under the New Heart Allocation System: A United Network for Organ Sharing Database Analysis

BACKGROUND

The effect of the new donor heart allocation system on survival following bridging to transplantation with venous-arterial extracorporeal membrane oxygenation remains unknown. The new allocation system places extracorporeal membrane oxygenation-supported candidates at the highest status.

METHODS

The United Network for Organ Sharing database was queried for adults bridged to single-organ heart transplantation with extracorporeal membrane oxygenation from October 2006 to February 2020. Association between implementation of the new system and recipient survival was analyzed using Kaplan-Meier estimates, Cox proportional hazards models, and propensity score matching.

RESULTS

Of 364 recipients included, 173 and 191 were transplanted under new and old systems, respectively. Compared with the old system, waitlist time was halved under the new system (5 versus 10 days, P<0.01); recipients also demonstrated lower rates of prior cardiac surgery (32.9% versus 44.5%, P=0.03) and preoperative ventilation (30.6% versus 42.4%, P=0.02). Unadjusted 180-day survival was 90.2% (95% CI, 84.7%-94.2%) and 69.6% (95% CI, 62.6%-76.1%) under the new and old systems, respectively. Cox proportional hazards analysis demonstrated listing and transplantation under the new system to be an independent predictor of post-transplant survival (adjusted hazard ratio, 0.34 [95% CI 0.20-0.59]). Propensity score matching demonstrated a similar trend (hazard ratio, 0.36 [95% CI, 0.19-0.66]). Candidates listed under the new system were significantly less likely to experience waitlist mortality or deterioration (subhazard ratio, 0.38 [95% CI, 0.25-0.58]) and more likely to survive to transplant (subhazard ratio, 4.29 [95% CI, 3.32-5.54]).

CONCLUSIONS

Recipients transplanted following extracorporeal membrane oxygenation bridging to transplantation under the new system achieve greater 180-day survival compared with the old and demonstrate less preoperative comorbidity. Waitlist outcomes have also improved significantly under the new allocation system.

Transfusion requirement prediction score for patients undergoing cardiac surgery: An experience from a tertiary care set-up from South India

BACKGROUND

Prediction of transfusion requirement is part of preoperative management in a surgical case. We aimed to develop one such tool for patients undergoing cardiac surgery.

METHODS

A retrospective study for a period of 3 years was done to develop the scoring tool, Transfusion Requirement Prediction Score for Cardiac Surgery (TRPS), and internal validation was done prospectively. The primary outcome was administration of allogenic red cell units to the patients during perioperative period. The outcome is dichotomized as controls and cases based on the number of Red Blood Cell units received. Independent variables were chosen based on statistical significance and clinical judgement. Receiver operating characteristic curve was used to obtain the cut-off for each independent variable, odds ratio, and regression coefficients were used to assign the score. All patients with a cumulative score below the cut-off value were categorised as 'low risk' and above the cut off as 'high risk' group.

RESULTS

During the study period, out of 602 patients, 345 met the inclusion criteria (controls: 175; cases: 170). Six variables such as age (more than 58 years), gender (female), bypass time (more than 148 min), haemoglobin (less than 12.5 g/dL), ejection fraction (less than 57%), and history of warfarin prophylaxis were chosen to develop the score. The total score value of 5 was chosen as the cut-off for the two risk groups. It predicted blood utilisation with a strength of 68% sensitivity and 79% specificity. On internal validation, the score was observed to have an accuracy of 70%.

CONCLUSION

The TRPS is a simple reliable and handy tool with high accuracy.

Preoperative anemia and transfusion in cardiac surgery: a single-centre retrospective study

Background

Preoperative anemia and transfusion are associated with worse outcomes. This study aims to identify the prevalence of preoperative anemia, transfusion rates on surgery day, and predictors of transfusion in elective cardiac surgery patients at our centre. We also aim to evaluate our preoperative intervention program, and examine the intervention window for anemia before surgery.

Methods

This study included 797 adult patients who underwent elective cardiac surgery at a tertiary hospital. Multivariable logistic regression analysis was used to identify predictors of transfusion on surgery day.

Results

Preoperative anemia was present in 15% of patients. Anemic patients had a significantly higher transfusion rate at 53% compared to 10% in non-anemic patients. Hemoglobin concentration, estimated glomerular filtration rate (eGFR), body surface area (BSA), and total cardiopulmonary bypass time were predictive of transfusion on surgery day. Patients had a median of 7 days between initial visit and surgery day, however, referral to the blood conservation clinic was only done for 8% of anemic patients and treatment was initiated in 3% of anemic patients. Among the 3 anemic patients who received treatment, 2 did not require blood transfusion on surgery day.

Conclusions

Preoperative anemia is present in 15% of patients at our centre and these patients have 53% transfusion rates on surgery day. Hemoglobin concentration, eGFR, BSA, and total cardiopulmonary bypass time were predictors of transfusion on surgery day. Patients had a median of 7 days between initial visit and surgery day. Referral and anemia treatment were infrequently initiated in preoperative anemic patient.

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

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.

Predictors of perioperative bleeding in left ventricular assist device implantation

Study objective

Early bleeding is a common source of morbidity associated with left ventricular assist device (LVAD) implantation. Our objective was to identify potential predictors of peri-implant bleeding.

Methods

We conducted a retrospective cohort study of LVAD implants at our institution between January 2010 and November 2018. A total of 210 patients were included. Data were collected for the duration of implant hospitalization, including perioperative invasive hemodynamics, echocardiography and operative details, antiplatelet and anticoagulant use, bleeding events and blood product use, and thromboembolic events. Peri-operative bleeding was defined as a transfusion requirement of >4 units of packed red blood cells in the intraoperative and first 7 days postoperative period, or a major 7-day post-implant overt bleeding event requiring procedural intervention.

Results

Perioperative bleeding occurred in 32% of patients and required surgical re-exploration in 9%. Multivariable logistic regression analysis identified history of previous sternotomy (OR 2.63, 95% CI 1.29 to 5.35, p-value 0.008), preoperative glomerular filtration rate <60 ml/min (OR 2.58, 95% CI 1.34 to 4.94, p-value 0.004), preoperative right atrial pressure >13 mm Hg (OR 2.36, 95% CI 1.19 to 4.67, p-value 0.014) and concomitant tricuspid valve repair (OR 2.48, 95% CI 1.23 to 5.01, p-value 0.011) as independent predictors of perioperative bleeding. In-hospital thromboembolic events occurred in 5% of patients, but there were no significant predictors for them.

Conclusions

Elevated right atrial pressure appears to be a reversible risk factor for early bleeding that should be targeted during pre-implant optimization of LVAD candidates.

Evaluation of a novel Cardiac Peri-Operative Transfusion Trigger Scoring system in patients with coronary artery disease

BACKGROUND

A simple and accurate scoring system to guide perioperative blood transfusion in patients with coronary artery disease (CAD) undergoing cardiac surgery is lacking. The trigger point for blood transfusions for these patients may be different from existing transfusion guidelines. This study aimed to evaluate the safety and efficacy of a new scoring strategy for use in guiding transfusion decisions in patients with CAD.

METHODS

A multicenter randomized controlled trial was conducted at three third-level grade-A hospitals from January 2015 to May 2018. Data of 254 patients in a Cardiac Peri-Operative Transfusion Trigger Score (cPOTTS) group and 246 patients in a group receiving conventional evaluation of the need for transfusion (conventional group) were analysed. The requirements for transfusion and the per capita consumption of red blood cells (RBCs) were compared between groups.

RESULTS

Baseline characteristics of the two groups were comparable. Logistic regression analyses revealed no significant differences between the two groups in primary outcomes (1-year mortality and perioperative ischemic cardiac events), secondary outcomes (shock, infections, and renal impairment), ICU admission, and ICU stay duration. However, patients in the cPOTTS group had significantly shorter hospital stays, lower hospital costs, lower utilization rate and lower per capita consumption of transfused RBCs than controls. Stratified analyses revealed no significant differences between groups in associations between baseline characteristics and perioperative ischemic cardiac events, except for hemofiltration or dialysis and NYHA class in I.

CONCLUSIONS

This novel scoring system offered a practical and straightforward guideline of perioperative blood transfusion in patients with CAD. Trial registration chiCTR1800016561(2017/7/19).

Blood Loss Kinetics During the First 12 Hours After On-Pump Cardiac Surgical Procedures

BACKGROUND

Anemia and coagulation management and a restrictive transfusion strategy are key points of blood management in patients undergoing cardiac surgical procedures. However, little consideration has been given to the kinetics of postoperative bleeding. This prospective observational study investigated bleeding kinetics from chest tubes to assess whether it was possible to predict, within the early postoperative hours, major bleeding at 12 postoperative hours.

METHODS

Adult cardiac surgical patients who were admitted consecutively to the postoperative intensive care unit in a tertiary academic hospital from January to June 2016 were included. Blood volume was collected from the chest drains, and major bleeding was defined as bleeding exceeding the 90th percentile of the volume distribution at 12 postoperative hours. Receiver operating characteristics curve analysis was performed with hourly bleeding thresholds to determine the best predictor of major bleeding.

RESULTS

In 292 patients, bleeding at 12 postoperative hours ranged from 60 to 2190 mL (median, 350 mL), and 30 patients had major bleeding, with a threshold of 675 mL. Bleeding volume declined logarithmically, 54% [IQR, 45% to 63%] within the first 4 hours. Patients with major bleeding had a higher bleeding volume every hour (P < .004). A good predictive value was observed within the first 2 hours (2.73 mL/kg; receiver operating characteristics area under the curve, 0.87 ± 0.04 [IQR, 0.79 to 0.94]; P< .001).

CONCLUSIONS

The hourly rate of chest tube blood loss seems to be relevant to predict, within the first postoperative hours after cardiac surgical procedures, major bleeding at 12 postoperative hours. Early detection of blood loss may help to improve a patient's blood conservation strategy because it may prompt preemptive treatments.

A randomized, double-blinded trial comparing the effectiveness of tranexamic acid and epsilon-aminocaproic acid in reducing bleeding and transfusion in cardiac surgery

Objectives:

To compare the effectiveness of epsilon aminocaproic acid (EACA) to tranexamic acid (TA) in reducing blood loss and transfusion requirements in patients undergone cardiac surgery under cardiopulmonary bypass.

Design:

Randomized, double blinded study. Outcome variables collected included; baseline demographic characteristics, type of surgery, amount of 24 hour chest tube drainage, amount of 24 hour blood products administered, 30 day mortality and morbidity and length of stay. We analyzed the data using parametric and non-parametric tests as appropriate.

Setting:

Single center tertiary-care university hospital setting.

Participants:

114 patients who had undergone cardiac surgery under cardiopulmonary bypass.

Interventions:

Standard dose of intra-operative EACA or TA was compared in patients undergone cardiac surgery under cardiopulmonary bypass.

Results:

There was no statistically significant difference between groups when analyzing chest tube drainage. However, there was a significant difference in the administration of any transfusion (PRBC's, FFP, platelets) intra-operatively to 24 hours postoperatively, with less transfusion in patients receiving EACA compared to TA (25% vs. 44.8%, respectively P = 0.027). Additionally, there was no significant difference in terms of adverse events during the one month follow up period.

Conclusion:

The findings of this study suggest that EACA and TA have similar effects on chest tube drainage but EACA is associated with fewer transfusions in CABG alone surgeries. Our results suggest that EACA can be used in a similar fashion to TA which may result in a cost and morbidity advantage.

Predictiveness of different preoperative risk assessments for postoperative bleeding after coronary artery bypass grafting surgery

Aim:

Postoperative bleeding is a significant cause of morbidity and mortality in patients undergoing cardiac surgery. Studies have been conducted, and guidelines have been published regarding patient blood management and aiming to prevent blood loss in the perioperative period. Various bleeding risk assessments were developed for preoperative period. We aimed to examine the correlations of scoring systems in the literature with the amount of postoperative bleeding in patients undergoing first time coronary artery bypass graft surgery, and to show the most suitable preoperative bleeding risk assessment for coronary artery bypass graft patients.

Methods:

The study included 550 consecutive patients who underwent coronary artery bypass graft operation. The inclusion criteria were considered as patients to be older than 18 years old and to undergo elective or emergent myocardial revascularization using cardiopulmonary bypass. All variables required for scoring systems were recorded. The initial results of the study were determined as the amount of chest tube drainage, the use of blood products, the change in hematocrit level, reoperation due to bleeding, duration of ventilation, duration of intensive care unit stay, and hospital stay. Mortality which occurred during first 30 days after operation was considered as operative mortality. Operative mortality was accepted as the primary endpoint. Secondary endpoints were massive bleeding and high amount of transfusion.

Results:

Data were obtained from a series of 550 consecutive patients treated with isolated coronary artery bypass graft. It was seen that PAPWORTH and WILL-BLEED risk assessments responded better for E-CABG grade 2 and 3 bleeding compared to other risk assessments. TRACK, TRUST, and ACTA-PORT scales were found to have low ability to distinguish patients with E-CABG bleeding grade 2 and 3.

Conclusion:

Predicting postoperative bleeding and transfusion rates with preoperative risk scores in patients undergoing coronary artery bypass graft surgery will provide valuable information to physicians for establishing a proper patient blood management protocol and this will decrease excessive transfusions, unnecessary reoperations as well as improve postoperative outcomes.

Evaluation of risk scores in predicting perioperative blood transfusions in adult cardiac surgery

Objective:

Allogeneic blood product transfusions are associated with an increased morbidity and mortality risk in cardiac surgery. At present, a few transfusion risk scores have been proposed for cardiac surgery patients. The present study is aimed to develop a new score and to compare with preexisting scores – Transfusion Risk and Clinical Knowledge (TRACK) and Transfusion Risk Understanding Scoring Tool (TRUST) score.

Methodology:

A total of 1014 adult patients undergoing cardiac surgery were enrolled in the retrospective study. Independent predictors of allogeneic blood transfusions were selected from TRACK and TRUST scores. A predictive score was developed from six variables using logistic regression analysis, and new score was compared to the other existing scores – TRACK and TRUST.

Results:

The new score had following predictors: age >58 years, weight <63 kg for males and <49 kg for females, gender (female), complex surgery, hemoglobin <13.5 g/dl, and creatinine >1.36 mg/dl. Validation of new score demonstrated an acceptable predictive power (area under the curve [AUC] 0.749) and a good calibration at the Hosmer–Lemeshow test. New score was comparable with TRACK score with P = 0.578 (AUC of TRACK 0.756 and AUC of new score 0.749). There was a significant difference between new score and TRUST score, P = 0.01 (AUC of TRUST 0.72 and AUC of new score 0.749).

Conclusion:

New score is a simple risk model based on six predictors having a similar accuracy and calibration in predicting the transfusion rate in cardiac surgery as compared to TRACK score.

Consensus Report on Patient Blood Management in Cardiac Surgery by Turkish Society of Cardiovascular Surgery (TSCVS), Turkish Society of Cardiology (TSC), and Society of Cardio-Vascular-Thoracic Anaesthesia and Intensive Care (SCTAIC)

Anemia, transfusion and bleeding independently increase the risk of complications and mortality in cardiac surgery. The main goals of patient blood management are to treat anemia, prevent bleeding, and optimize the use of blood products during the perioperative period. The benefit of this program has been confirmed in many studies and its utilization is strongly recommended by professional organizations. This consensus report has been prepared by the authors who are the task members appointed by the Turkish Society of Cardiovascular Surgery, Turkish Society of Cardiology (TSC), and Society of Cardio-Vascular-Thoracic Anaesthesia and Intensive Care to raise the awareness of patient blood management. This report aims to summarize recommendations for all perioperative blood- conserving strategies in cardiac surgery.

Predictive scores for major bleeding after coronary artery bypass surgery in low operative risk patients

BACKGROUND

Cardiac surgery is associated with perioperative bleeding and carries high risk of allogeneic blood transfusion. Recently new scores for prediction of severe bleeding have been developed. This study aims to compare the WILL-BLEED, CRUSADE, PAPWORTH, TRUST, TRACK and ACTION scores in predicting major bleeding after CABG in patients with low estimated operative risk.

METHODS

A multicenter observational study included 1391 patients who underwent isolated CABG from July 2015 to January 2018. We tested the hypothesis that the WILL-BLEED score, specifically designed for CABG, would perform at least as well as the CRUSADE, PAPWORTH, TRUST, TRACK and ACTION scores in predicting postoperative major bleeding in low operative risk patients. The primary endpoint was the performance of known bleeding risk scores after CABG. The secondary endpoint was the evaluation of in-hospital mortality.

RESULTS

Mean age was 68.2±9.4 years and median Euroscore II value was 1.69% (IQR 1.15-2.81%). Mean blood losses in the first 12 postoperative hours was 339.75 mL. Seventy-three (5.2%) subjects underwent administration of blood products. The rate of severe-massive bleeding according to UDPB grades 3-4 was 1.5%. WILL-BLEED, TRUST, TRACK and ACTION scores were significantly associated with severe postoperative bleeding. WILL-BLEED presented the best c-index (AUC: 0.658; 95% CI: 0.600,0.716). Reclassification analysis showed a worsening in sensitivity and significant negative reclassification of CRUSADE, PAPWORTH, TRACK and ACTION scores when compared with WILL-BEED. The combination of WILL-BLEED and TRUST scores improved the prediction ability (AUC: 0.673; 95% CI: 0.615-0.732). Overall in-hospital mortality was 1.65%. Early mortality in patients with severe versus no-severe bleeding was found to be 11.8% vs. 1.0% Severe bleeding (OR: 13.26; P value<0.001) was found to be significantly associated with early mortality.

CONCLUSIONS

Severe bleeding after CABG is a harmful event associated with adverse outcomes. WILL-BLEED Score has the better performance in predicting severe-massive bleeding after CABG. The TRUST Score, although suboptimal, represents a valuable alternative in this setting.

Optimizing Perioperative Blood and Coagulation Management During Cardiac Surgery

Bleeding and transfusion are common in cardiac surgery and associated with poorer outcome. Bleeding is frequently due to coagulopathy caused by the complex interaction between cardiopulmonary bypass, major surgical trauma, anticoagulation management, and perioperative factors. Patient blood management has emerged to improve outcome by the prediction, prevention, monitoring, and treatment of bleeding and transfusion. Each part of this chain has several individual modalities and when combined leads to result in a better outcome. This article reviews the hemostasis disturbances in cardiac surgery with cardiopulmonary bypass and gives an overview of the most important patient blood management strategies.

Predictors of blood transfusion use in robotic beating-heart totally endoscopic coronary artery bypass with anastomotic connectors

BACKGROUND

We sought to identify the independent predictors of blood transfusion requirement in robotic beating-heart patients with totally endoscopic coronary artery bypass (TECAB).

METHODS

We retrospectively reviewed patients undergoing TECAB with distal anastomotic connectors from July 2013 to May 2017 at our institution. The cohorts were divided into patients who received a blood transfusion (BT group) and patients who did not (non-blood transfusion [NBT] group).

RESULTS

Two-hundred seventy-four consecutive patients underwent TECAB, and 47 patients (17%; BT group) received BT. The BT group had a lower preoperative hemoglobin level and a higher rate of preoperative risk profiles and higher society of thoracic surgeons (STS) predicted the risk of mortality. Kaplan Meier analysis showed decreased 1-year survival in the BT group compared with the NBT group (90.9% vs 96.4%; logrank, 0.017). The Youden index identified a preoperative hemoglobin cutoff value of 12.2 g/dL (sensitivity 60.9%, specificity 79.3%) and operative time of 300 minutes (sensitivity 61.7%, specificity 59.0%) for BT requirement. Multivariate logistic regression analysis identified a preoperative hemoglobin <12.2 g/dL (odds ratio, 6.03; 95% confidence interval, 3.01-12.1) and an operative time >300 minutes (odds ratio, 2.15; 95% confidence interval, 1.07-4.33) as independent factors associated with BT requirement.

CONCLUSIONS

We found that preoperative hemoglobin and operative time were independent predictors of BT requirement during robotic beating-heart TECAB. These data would help to select patients to minimize perioperative BT as well as predict outcomes after this procedure.