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

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.

A Systematic Review and Meta-analysis of Randomized Controlled Trials Comparing Intraoperative Red Blood Cell Transfusion Strategies

OBJECTIVE

The objective of this work was to carry out a meta-analysis of RCTs comparing intraoperative RBC transfusion strategies to determine their impact on postoperative morbidity, mortality, and blood product use.

SUMMARY OF BACKGROUND DATA

RBC transfusions are common in surgery and associated with widespread variability despite adjustment for casemix. Evidence-based recommendations guiding RBC transfusion in the operative setting are limited.

METHODS

The search strategy was adapted from a previous Cochrane Review. Electronic databases were searched from January 2016 to February 2021. Included studies from the previous Cochrane Review were considered for eligibility from before 2016. RCTs comparing intraoperative transfusion strategies were considered for inclusion. Co-primary outcomes were 30-day mortality and morbidity. Secondary outcomes included intraoperative and perioperative RBC transfusion. Meta-analysis was carried out using random-effects models.

RESULTS

Fourteen trials (8641 patients) were included. One cardiac surgery trial accounted for 56% of patients. There was no difference in 30-day mortality [relative risk (RR) 0.96, 95% confidence interval (CI) 0.71-1.29] and pooled postoperative morbidity among the studied outcomes when comparing restrictive and liberal protocols. Two trials reported worse composite outcomes with restrictive triggers. Intraoperative (RR 0.53, 95% CI 0.43-0.64) and perioperative (RR 0.70, 95% CI 0.62-0.79) blood transfusions were significantly lower in the restrictive group compared to the liberal group.

CONCLUSIONS

Intraoperative restrictive transfusion strategies decreased perioperative transfusions without added postoperative morbidity and mortality in 12/14 trials. Two trials reported worse outcomes. Given trial design and generalizability limitations, uncertainty remains regarding the safety of broad application of restrictive transfusion triggers in the operating room. Trials specifically designed to address intraoperative transfusions are urgently needed.