Department of Medicine, Faculdade de Medicina de São José do Rio Preto, São José do Rio Preto, São Paulo, Brazil.
Duke Biostatistics, Epidemiology and Research Design Core, Duke University School of Medicine, Durham, NC, United States of America.
Blood Transfus. 2024 Sep;22(5):420-428. doi: 10.2450/BloodTransfus.722. Epub 2024 Jul 19.
In hospitalized patients undergoing therapeutic plasma exchange (TPE), it is not known how TPE-associated bleeding risk is impacted by a prior bleeding episode. Therefore, to assess the prevalence and predictors of bleeding recurrence, we analyzed data from the Recipient Epidemiology and Donor Evaluation Study-III (REDS-III).
Using a retrospective cross-sectional analysis of REDS-III public use files, we identified hospitalized adults who had a major bleeding episode prior to their first TPE procedure. Patients were classified into two cohorts based on bleeding recurrence (no-recurrence vs recurrence). After identifying potential predictors, we used multiple imputation by chained equations to impute variables with <30% missing data. Variable selection was optimized using a 10-fold cross validated least absolute shrinkage and selection operator. Final predictors were identified by fitting a logistic regression model.
In 310 patients with major bleeding prior to TPE initiation, bleeding recurred in 121 (39.0%). We identified the following seven unique predictors: 1) >10 TPE procedures (OR 2.23); 2) intensive care unit stay (OR 1.35); 3) thrombocytopenia (OR 1.26); 4) surgery (OR 1.22); 5) hepatic disease (OR 1.21); 6) 6-10 TPE procedures (OR 1.04); and 7) Asian race (OR 1.01). We also identified the following five interactions: 1) surgery and therapeutic anticoagulation (OR 1.50); 2) 6-10 TPE procedures and therapeutic anticoagulation (OR 1.05); 3) 6-10 TPE procedures and antiplatelets (OR 1.02); 4) >10 TPE procedures and antiplatelets (OR 1.00); and 5) albumin-only TPE and antiplatelets (OR 0.53). When assessed for adjusted performance, the prediction model had a C-statistic of 0.617 (95% CI 0.613-0.619) and Brier Score of 0.342 (95% CI 0.340-0.347).
In this study assessing predictors of bleeding recurrence among hospitalized patients undergoing TPE, we identified seven variables and five interactions. These findings should be validated in future studies.
在接受治疗性血浆置换(TPE)的住院患者中,尚不清楚先前的出血事件如何影响 TPE 相关出血风险。因此,为了评估出血复发的患病率和预测因素,我们分析了来自受体流行病学和供者评估研究-III(REDS-III)的数据。
使用 REDS-III 公共使用文件的回顾性横断面分析,我们确定了在首次 TPE 程序前发生重大出血事件的住院成年患者。根据出血复发情况(无复发 vs 复发),将患者分为两组。在确定潜在的预测因素后,我们使用链式方程的多重插补来插补 <30%缺失数据的变量。使用 10 折交叉验证最小绝对收缩和选择算子优化变量选择。通过拟合逻辑回归模型确定最终预测因素。
在 310 例 TPE 前发生重大出血的患者中,121 例(39.0%)出血复发。我们确定了以下七个独特的预测因素:1)>10 次 TPE 治疗(OR 2.23);2)重症监护病房住院(OR 1.35);3)血小板减少症(OR 1.26);4)手术(OR 1.22);5)肝脏疾病(OR 1.21);6)6-10 次 TPE 治疗(OR 1.04);7)亚洲人种(OR 1.01)。我们还确定了以下五个相互作用:1)手术和治疗性抗凝(OR 1.50);2)6-10 次 TPE 治疗和治疗性抗凝(OR 1.05);3)6-10 次 TPE 治疗和抗血小板药物(OR 1.02);4)>10 次 TPE 治疗和抗血小板药物(OR 1.00);5)白蛋白单采 TPE 和抗血小板药物(OR 0.53)。当评估调整后的性能时,预测模型的 C 统计量为 0.617(95%CI 0.613-0.619),Brier 评分 0.342(95%CI 0.340-0.347)。
在这项评估接受 TPE 的住院患者出血复发预测因素的研究中,我们确定了七个变量和五个相互作用。这些发现应在未来的研究中得到验证。