Prediction of risk of blood transfusion in patients with cirrhosis.

Abstract

Background: Blood transfusion is usually required for cirrhotic patients with bleeding which is related to high risk of mortality. Identifying cirrhotic patients at high risk of bleeding and needing blood transfusions would benefit these patients, yet this remains an unmet need.

Objectives: This study aims to enhance blood transfusion management for patients with cirrhosis by developing a predictive model to assess the risk of transfusion.

Methods: We enrolled a cohort of 711 patients diagnosed with cirrhosis at The First Affiliated Hospital of Nanjing Medical University and divided into training set (n = 537) and validation set (n = 174). Each participant underwent a comprehensive clinical assessment. Data on prothrombin time (PT), platelet counts, and inflammatory markers were collected. Univariate and multivariate logistic regression analyses were performed to identify independent predictors. The nomogram was constructed. Model performance was evaluated through receiver operating characteristic curve analysis.

Results: The study successfully identified PT, platelet counts, and the mentioned inflammatory markers as significant predictors of the need for transfusion. The resulting nomogram demonstrated high predictive accuracy, with area under the curve values of 0.85 in the training set and 0.83 in the validation set.

Conclusion: The developed nomogram for predicting the need for blood transfusion in patients with cirrhosis shows promising effectiveness for clinical application. This tool can significantly contribute to optimizing transfusion practices, potentially improving patient care and outcomes through more personalized and efficient transfusion strategies.