Lung Injury Prediction Model in Bone Marrow Transplantation: A Multicenter Cohort Study.
Lung Injury Prediction Model in Bone Marrow Transplantation: A Multicenter Cohort Study.
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骨髓移植中的肺损伤预测模型：多中心队列研究。
DOI：
10.1164/rccm.202308-1524oc
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发表时间：
2024
影响因子：
24.7
通讯作者：
Yadav,Hemang
中科院分区：
文献类型：
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作者：
Herasevich,Svetlana;Schulte,PhillipJ;Hogan,WilliamJ;Alkhateeb,Hassan;Zhang,Zhenmei;White,BradleyA;Khera,Nandita;Roy,Vivek;Gajic,Ognjen;Yadav,Hemang
理论基础：在造血干细胞移植(HCT)后，肺部并发症对无复发死亡率有显著影响。识别高危患者有助于将此类患者纳入临床研究，以更好地了解、预防和治疗移植后呼吸衰竭综合征。目的：开发和验证预测模型，以确定HCT后急性呼吸衰竭的高危患者。方法：在2019年1月1日至2021年12月31日期间，三家机构之一的患者接受了HCT。在明尼苏达州罗切斯特接受治疗的患者形成衍生队列，在亚利桑那州斯科茨代尔或佛罗里达州杰克逊维尔接受治疗的患者形成验证队列。主要结果是发生急性呼吸窘迫综合征(ARDS)，次要结果包括需要有创机械通气(IMV)和/或无创机械通气(NIV)。预测因素基于先前的病例对照研究。测量和主要结果：在2450名接受干细胞移植的患者中，训练队列中有1718人(888人)住院，测试队列中有1005人(470人)。建立了一个22点模型，其中11点来自院前预测，11点来自移植后或早期(24小时)院内预测。该模型在预测急性呼吸窘迫综合征(C-统计量，0.905；95%可信区间[CI]，0.870-0.941)和是否需要IMV和/或NIV(C-统计量，0.863；95%CI，0.828-0.898)方面表现良好。测试队列在人口学、医学和血液学特征上有显著差异。该模型在预测急性呼吸窘迫综合征(C统计量，0.841；95%可信区间，0.782-0.900)和是否需要IMV和/或非静脉输注(C统计量，0.872；95%可信区间，0.831-0.914)方面也表现良好。结论：一个新的预测模型结合了移植前、移植后和早期院内领域的数据元素，可以可靠地预测HCT后急性呼吸衰竭的发展。
Rationale:Pulmonary complications contribute significantly to nonrelapse mortality following hematopoietic stem cell transplantation (HCT). Identifying patients at high risk can help enroll such patients into clinical studies to better understand, prevent, and treat posttransplantation respiratory failure syndromes.Objectives:To develop and validate a prediction model to identify those at increased risk of acute respiratory failure after HCT.Methods:Patients underwent HCT between January 1, 2019, and December 31, 2021, at one of three institutions. Those treated in Rochester, MN, formed the derivation cohort, and those treated in Scottsdale, AZ, or Jacksonville, FL, formed the validation cohort. The primary outcome was the development of acute respiratory distress syndrome (ARDS), with secondary outcomes including the need for invasive mechanical ventilation (IMV) and/or noninvasive ventilation (NIV). Predictors were based on prior case-control studies.Measurements and Main Results:Of 2,450 patients undergoing stem cell transplantation, there were 1,718 hospitalizations (888 patients) in the training cohort and 1,005 hospitalizations (470 patients) in the test cohort. A 22-point model was developed, with 11 points from prehospital predictors and 11 points from posttransplantation or early (<24-h) in-hospital predictors. The model performed well in predicting ARDS (C-statistic, 0.905; 95% confidence interval [CI], 0.870–0.941) and the need for IMV and/or NIV (C-statistic, 0.863; 95% CI, 0.828–0.898). The test cohort differed markedly in demographic, medical, and hematologic characteristics. The model also performed well in this setting in predicting ARDS (C-statistic, 0.841; 95% CI, 0.782–0.900) and the need for IMV and/or NIV (C-statistic, 0.872; 95% CI, 0.831–0.914).Conclusions:A novel prediction model incorporating data elements from the pretransplantation, posttransplantation, and early in-hospital domains can reliably predict the development of post-HCT acute respiratory failure.