Machine Learning for Preoperative Transfusion Risk Prediction in Total Knee and Hip Arthroplasty
Year: 2026
Type: article
Study design: Observational Study
Abstract: Background Unnecessary blood preparation before total knee arthroplasty (TKA) and total hip arthroplasty (THA) increases healthcare costs and resource burden. Accurate preoperative transfusion risk prediction can support clinical decision-making and optimise blood bank management. Methods We conducted a retrospective cohort study using real-world electronic health records from a tertiary medical centre in Taiwan (2020–2025). A total of 6,089 patients undergoing TKA (n = 4,311) or THA (n = 1,778) were included. Twenty-eight preoperative features were extracted, including haematological indices, demographic variables, comorbidities, and medication use. Four machine learning models (Logistic Regression, Random Forest, XGBoost, LightGBM) were trained using 5-fold stratified cross-validation on an 80% development set and evaluated on a 20% holdout set. Model calibration was assessed using the Hosmer-Lemeshow test. SHAP values were used to interpret feature contributions globally and by surgical subgroup. Results The overall transfusion rate was 18.7% (TKA: 15.3%; THA: 27.1%). LightGBM achieved the highest holdout AUROC (0.751; 95% CI: 0.714–0.787), with good calibration (Hosmer-Lemeshow p = 0.297), Brier Score of 0.128, and NPV of 0.891 at the Youden Index threshold. SHAP analysis identified preoperative haemoglobin (Hb), surgery type, and tranexamic acid (TXA) use as the top predictors. A non-linear relationship was observed: transfusion risk increased sharply when preop Hb fell below 12 g/dL. Conclusions An interpretable LightGBM model demonstrated reliable discrimination and calibration for perioperative transfusion prediction. The high NPV suggests this model can safely identify low-risk patients, potentially reducing unnecessary blood preparation in orthopaedic surgical settings. Key messages • A LightGBM model predicts perioperative transfusion risk in TKA/THA with an AUROC of 0.751 and NPV of 0.891, enabling safer reduction of unnecessary blood preparation. • Preoperative haemoglobin, surgery type, and TXA use are the strongest predictors of transfusion; risk rises sharply when Hb falls below 12 g/dL.
Language: English
Subfield: Hematology
Field: Medicine
Domain: Health Sciences
Open Access status: gold
Estimated APC paid: $3,181
OpenAlex ID: W7223657759