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发展和验证预测评分,以预测过渡到透析时的早期死亡率。

Development and Validation of Prediction Scores for Early Mortality at Transition to Dialysis.

机构信息

Harold Simmons Center for Kidney Disease Research and Epidemiology, Division of Nephrology and Hypertension, University of California, Irvine Medical Center, Orange, CA.

Division of General Internal Medicine and Primary Care, University of California, Irvine Medical Center, Orange, CA.

出版信息

Mayo Clin Proc. 2018 Sep;93(9):1224-1235. doi: 10.1016/j.mayocp.2018.04.017. Epub 2018 Aug 10.

Abstract

OBJECTIVE

To develop and validate a risk prediction model that would help individualize treatment and improve the shared decision-making process between clinicians and patients.

PATIENTS AND METHODS

We developed a risk prediction tool for mortality during the first year of dialysis based on pre-end-stage renal disease characteristics in a cohort of 35,878 US veterans with incident end-stage renal disease who transitioned to dialysis treatment between October 1, 2007, and March 31, 2014 and then externally validated this tool among 4284 patients in the Kaiser Permanente Southern California (KPSC) health care system who transitioned to dialysis treatment between January 1, 2007, and September 30, 2015.

RESULTS

To ensure model goodness of fit, 2 separate models were selected for patients whose last estimated glomerular filtration rate (eGFR) before dialysis initiation was less than 15 mL/min per 1.73 m or 15 mL/min per 1.73 m or higher. Model discrimination in the internal validation cohort of veterans resulted in C statistics of 0.71 (95% CI, 0.70-0.72) and 0.66 (95% CI, 0.65-0.67) among patients with eGFR lower than 15 mL/min per 1.73 m and 15 mL/min per 1.73 m or higher, respectively. In the KPSC external validation cohort, the developed risk score exhibited C statistics of 0.77 (95% CI, 0.74-0.79) in men and 0.74 (95% CI, 0.71-0.76) in women with eGFR lower than 15 mL/min per 1.73 m and 0.71 (95% CI, 0.67-0.74) in men and 0.67 (95% CI, 0.62-0.72) in women with eGFR of 15 mL/min per 1.73 m or higher.

CONCLUSION

A new risk prediction tool for mortality during the first year after transition to dialysis (available at www.DialysisScore.com) was developed in the large national Veterans Affairs cohort and validated with good performance in the racially, ethnically, and gender diverse KPSC cohort. This risk prediction tool will help identify high-risk populations and guide management strategies at the transition to dialysis.

摘要

目的

开发并验证一种风险预测模型,以帮助个体化治疗,并改善临床医生和患者之间的共同决策过程。

患者和方法

我们基于 2007 年 10 月 1 日至 2014 年 3 月 31 日期间接受终末期肾脏疾病治疗并过渡到透析治疗的 35878 名美国退伍军人队列中终末期前肾脏疾病特征,开发了一种用于透析治疗第一年死亡率的风险预测工具,然后在 2007 年 1 月 1 日至 2015 年 9 月 30 日期间接受透析治疗的 Kaiser Permanente Southern California (KPSC) 医疗系统的 4284 名患者中对该工具进行了外部验证。

结果

为确保模型拟合度,我们为最后估计肾小球滤过率(eGFR)在透析开始前低于 15 mL/min/1.73 m 或 15 mL/min/1.73 m 或更高的患者选择了两个单独的模型。退伍军人内部验证队列中的模型区分度导致 eGFR 低于 15 mL/min/1.73 m 和 15 mL/min/1.73 m 或更高的患者的 C 统计值分别为 0.71(95%CI,0.70-0.72)和 0.66(95%CI,0.65-0.67)。在 KPSC 外部验证队列中,在 eGFR 低于 15 mL/min/1.73 m 的男性和女性中,开发的风险评分的 C 统计值分别为 0.77(95%CI,0.74-0.79)和 0.74(95%CI,0.71-0.76),在 eGFR 为 15 mL/min/1.73 m 或更高的男性和女性中,C 统计值分别为 0.71(95%CI,0.67-0.74)和 0.67(95%CI,0.62-0.72)。

结论

在大型退伍军人事务队列中开发了一种新的透析后第一年死亡率风险预测工具(可在 www.DialysisScore.com 上获得),并在种族、民族和性别多样化的 KPSC 队列中进行了良好的验证。该风险预测工具将有助于确定高危人群,并指导透析过渡期的管理策略。

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