Multivariable statistical models to predict red cell transfusion in elective surgery

Kevin M Trentino, Frank M Sanfilippo, Michael F Leahy, Shannon L Farmer, Hamish Mace, Adam Lloyd, Kevin Murray

Research output: Contribution to journalArticlepeer-review

2 Citations (Scopus)


BACKGROUND: Predicting red cell transfusion may assist in identifying those most likely to benefit from patient blood management strategies. Our objective was to identify a simple statistical model to predict transfusion in elective surgery from routinely available data.

MATERIALS AND METHODS: Our final multicentre cohort consisted of 42,546 patients and contained the following potential predictors of red cell transfusion known prior to admission: patient age, sex, pre-admission haemoglobin, surgical procedure, and comorbidities. Missing data were handled by multiple imputation methods. The outcome measure of interest was administration of a red cell transfusion. We used multivariable logistic regression models to predict transfusion, and evaluated the performance by applying a 10-fold cross-validation. Model accuracy was assessed by comparing the area under the receiver operating characteristics curve. After applying an optimal probability cut-off we measured model accuracy, sensitivity, specificity, positive predictive value, and negative predictive value.

RESULTS: 7.0% (n=2,993) of the study population received a red cell transfusion. Our most simple model predicted red cell transfusion based on admission haemoglobin and surgical procedure with a multiply imputed estimated area under the curve of 0.862 (0.856, 0.864). The estimated accuracy, sensitivity, specificity, positive predictive, and negative predictive values at the probability cut-off of 0.4 were 0.934, 0.257, 0.986, 0.573, and 0.946 respectively.

DISCUSSION: A small number of variables available prior to admission can predict red cell transfusion with very good accuracy. Our model can be used to flag high-risk patients most likely to benefit from pre-operative patient blood management measures.

Original languageEnglish
Pages (from-to)42-49
Number of pages8
JournalBlood transfusion = Trasfusione del sangue
Issue number1
Early online date11 Mar 2022
Publication statusPublished - 1 Jan 2023


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