Construction of the nomogram model for predicting platelet transfusion refractoriness
SU Gaofan1,CHEN Jingsi1, ZHENG Tingting1, JIN Fangsi1, JIANG Minghua2
1.Department of Blood Transfusion, the Second Affiliated Hospital & Yuying Children’s Hospital of Wenzhou Medical University, Wenzhou 325027,China; 2.Department of Clinical Laboratory, the Second Affiliated Hospital & Yuying Children’s Hospital of Wenzhou Medical University, Wenzhou 325027, China
SU Gaofan,CHEN Jingsi,ZHENG Tingting, et al. Construction of the nomogram model for predicting platelet transfusion refractoriness[J]. JOURNAL OF WEZHOU MEDICAL UNIVERSITY, 2021, 51(9): 741-745.
Abstract：Objective: To construct and validate a nomogram that can be used to predict platelet transfusion refractoriness in patients who received platelet transfusions. Methods: A total of 174 patients who received platelet transfusions were selected from the Second Affiliated Hospital & Yuying Children’s Hospital of Wenzhou Medical University from January 2019 to December 2019. Among 174 patients, 46 (26.4%) were platelet transfusion refractoriness. Pertinent clinical data were collected including patient age, gender, multiple pregnancies,active bleeding, skin and mucous membrane bleeding, splenomegaly, fever, ABO blood group, number of platelet transfusions, platelet antibody and platelet count. Multivariate logistic regression was used to screen independent factors and to construct the nomogram. Results: Multivariate logistic regression indicated that female (OR=2.43,95%CI=1.08-5.44, P=0.0310), platelet antibody (OR=4.46, 95%CI=1.11-17.85, P=0.035), infection (OR=2.42,95%CI=1.03-5.71, P=0.042), splenomegaly (OR=2.14, 95%CI=1.01-5.92, P=0.045), infusion times (OR=4.90,95%CI=2.10-11.42, P=0.002) were associated with higher odds of platelet transfusion refractoriness. Afterwards,the above variables were incorporated into the nomogram. Bootstrap test (Bootstrap resampling times=500),used for internal validation, revealed that the AUC was 0.858. Conclusion: The constructed nomogram could potentially predict platelet transfusion refractoriness in patients who received platelet transfusion.
