Predicting mortality risk on dialysis and conservative care: development and internal validation of a prediction tool for older patients with advanced chronic kidney disease.
Predicting mortality risk on dialysis and conservative care: development and internal validation of a prediction tool for older patients with advanced chronic kidney disease.
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预测透析和保守护理的死亡率风险:针对患有晚期慢性肾脏疾病的老年患者的预测工具的开发和内部验证。
DOI:
10.1093/ckj/sfaa021
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发表时间:
2021-01
影响因子:
4.6
通讯作者:
van Diepen M
中科院分区:
文献类型:
--
作者:
Ramspek CL;Verberne WR;van Buren M;Dekker FW;Bos WJW;van Diepen M
Conservative care (CC) may be a valid alternative to dialysis for certain older patients with advanced chronic kidney disease (CKD). A model that predicts patient prognosis on both treatment pathways could be of value in shared decision-making. Therefore, the aim is to develop a prediction tool that predicts the mortality risk for the same patient for both dialysis and CC from the time of treatment decision. CKD Stage 4/5 patients aged ≥70 years, treated at a single centre in the Netherlands, were included between 2004 and 2016. Predictors were collected at treatment decision and selected based on literature and an expert panel. Outcome was 2-year mortality. Basic and extended logistic regression models were developed for both the dialysis and CC groups. These models were internally validated with bootstrapping. Model performance was assessed with discrimination and calibration. In total, 366 patients were included, of which 126 chose CC. Pre-selected predictors for the basic model were age, estimated glomerular filtration rate, malignancy and cardiovascular disease. Discrimination was moderate, with optimism-corrected C-statistics ranging from 0.675 to 0.750. Calibration plots showed good calibration. A prediction tool that predicts 2-year mortality was developed to provide older advanced CKD patients with individualized prognosis estimates for both dialysis and CC. Future studies are needed to test whether our findings hold in other CKD populations. Following external validation, this prediction tool could be used to compare a patient’s prognosis on both dialysis and CC, and help to inform treatment decision-making.
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影响因子:
6.1
作者:
Singh, Pooja;Germain, Michael J.;Unruh, Mark
通讯作者:
Unruh, Mark
DOI:
10.2215/cjn.03860609
发表时间:
2010-01-01
影响因子:
9.8
作者:
Cohen, Lewis M.;Ruthazer, Robin;Germain, Michael J.
通讯作者:
Germain, Michael J.
影响因子:
2.8
作者:
Burns, Aine;Carson, Rachel
通讯作者:
Carson, Rachel
影响因子:
3.9
作者:
Ramspek CL;Voskamp PW;van Ittersum FJ;Krediet RT;Dekker FW;van Diepen M
通讯作者:
van Diepen M
影响因子:
2.3
作者:
Austin PC;Steyerberg EW
通讯作者:
Steyerberg EW