Prediction model of platelet transfusion refractoriness in patients with hematological disorders
Journal Title: Chinese Journal of Blood Transfusion - Year 2024, Vol 37, Issue 8
Abstract
Objective To explore the risk factors for platelet transfusion refractoriness(PTR)in patients with hematological disorders, construct a prediction model and validate the model efficacy. Methods Patients with hematological disorders who received platelet transfusion therapy in the Chengdu Second People′s Hospital from December 2021 to December 2022 were retrospectively included to judge the effectiveness of platelet transfusion and screened for risk factors by univariate and multivariate logistic regression. A prediction model for PTR was constructed using receiver operating characteristic(ROC) curve, calibration curve and decision curve(DCA) to assess the differentiation, calibration and clinical value of the model, respectively. Results A total of 334 hematological patients were included, including 168 males and 176 females, with a PTR incidence of 40.4%. Univariate and multivariate logistic regression analysis showed that platelet transfusion volume, erythrocyte transfusion volume, and neutrophil ratio were risk factors for PTR(P<0.05). A prediction model for PTR in hematological patients was established based on these risk factors. The area under the model′s curve was 0.8377(95% CI: 0.723-0.772), the sensitivity was 58.52%, and the specificity was 89.95%. The calibration curve showed that the S∶P was 0.964, the maximum absolute difference Emax was 0.032, and the average absolute difference Eavg was 0.009. The DCA analysis showed that the model had clinical application value when the risk threshold ranged from 0.2 to 0.9. Conclusion The PTR prediction model based on platelet transfusion volume, erythrocyte transfusion volume and neutrophil ratio can provide a basis for effective platelet transfusion in hematological patients.
Authors and Affiliations
Shuhan YUE, Xiulan HUANG, Yan ZENG, Qiao LEI, Mengzhen HE, Liqi LU, Shisong YOU, Jingwei ZHANG
Keywords
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- EP ID EP744450
- DOI 10.13303/j.cjbt.issn.1004-549x.2024.08.008
- Views 44
- Downloads 0
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