Multivariable statistical models to predict red cell transfusion in elective surgery.

ABSTRACT:

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 hemoglobin, 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

SUBMITTER: Trentino KM 

PROVIDER: S-EPMC9918382 | biostudies-literature | 2023 Jan

REPOSITORIES: biostudies-literature