Wetmore James B, Roetker Nicholas S, Gilbertson David T, Liu Jiannong
Chronic Disease Research Group, Hennepin Healthcare Research Institute, Minneapolis, Minnesota, USA.
Division of Nephrology, Hennepin Healthcare Systems, University of Minnesota, Minneapolis, Minnesota, USA.
Hemodial Int. 2019 Apr;23(2):261-272. doi: 10.1111/hdi.12723. Epub 2019 Feb 11.
Whether and how factors associated with elective hemodialysis withdrawal differ from those associated with non-withdrawal death soon after maintenance hemodialysis initiation have not been well studied.
A retrospective cohort analysis was performed using USRDS data from 2011 to 2014. Patients were randomly categorized 2:1 into training and validation samples. Elective withdrawal deaths were identified using the Death Notification form. Multinomial logistic regression was used to fit a prediction model for three outcome categories (withdrawal, non-withdrawal death, survival at 6 months) as a function of demographic, comorbidity, and functional status.
The training sample comprised 80,284 hemodialysis patients. Mean age was 71.7 ± 11.4 years, 44.9% were female, 72.9% were white, and 22.8% were black. Within 6 months, 19.1% died, of whom 2099 (2.6%) withdrew and 13,223 (16.5%) died of a non-withdrawal cause; 13.7% of all deaths were withdrawals. Baseline characteristics and event rates were similar among the 40,142 patients in the validation sample. The model was calibrated adequately and could discriminate moderately well between withdrawal and survival (area under ROC curve [AUC]: 0.77) and between non-withdrawal death and survival (AUC: 0.73). However, discrimination between withdrawal and non-withdrawal death was relatively low (AUC: 0.62). Older age and white, compared with non-white, race were each associated with greater odds of death, and these associations were stronger for withdrawal than for non-withdrawal death.
Advanced age and white, as opposed to black, race were most strongly associated with early elective hemodialysis withdrawal compared with non-withdrawal death. However, it is difficult to differentiate between patients who will experience early withdrawal vs. non-withdrawal death, as many factors are similarly associated with both outcomes.
与维持性血液透析开始后不久的非退出死亡相关的因素是否以及如何不同于与选择性血液透析退出相关的因素，尚未得到充分研究。
使用2011年至2014年的美国肾脏数据系统（USRDS）数据进行回顾性队列分析。患者以2:1的比例随机分为训练样本和验证样本。使用死亡通知表确定选择性退出死亡。多项逻辑回归用于拟合一个预测模型，该模型将人口统计学、合并症和功能状态作为函数，用于三个结局类别（退出、非退出死亡、6个月存活）。
训练样本包括80284名血液透析患者。平均年龄为71.7±11.4岁，44.9%为女性，72.9%为白人，22.8%为黑人。在6个月内，19.1%的患者死亡，其中2099人（2.6%）退出，13223人（16.5%）死于非退出原因；所有死亡中有13.7%是退出。验证样本中的40142名患者的基线特征和事件发生率相似。该模型校准良好，在退出和存活之间（ROC曲线下面积[AUC]：0.77）以及非退出死亡和存活之间（AUC：0.73）能够进行适度良好的区分。然而，退出和非退出死亡之间的区分相对较低（AUC：0.62）。与非白人相比，老年和白人种族与死亡几率增加均相关，并且这些关联在退出方面比在非退出死亡方面更强。
与非退出死亡相比，高龄和白人种族与早期选择性血液透析退出的关联最为密切。然而，很难区分哪些患者会早期退出与非退出死亡，因为许多因素与这两种结局都有相似的关联。
