Contribution of medico-administrative data to the development of a comorbidity score to predict mortality in End-Stage Renal Disease patients

Author:

Pladys Adélaïde,Vigneau Cécile,Raffray Maxime,Sautenet Bénédicte,Gentile Stéphanie,Couchoud CécileORCID,Bayat Sahar

Abstract

AbstractComorbidity scores to predict mortality are very useful to facilitate decision-making for personalized patient management. This study aim was to assess the contribution of medico-administrative data in addition to French Renal Epidemiology and Information Network (REIN) data to the development of a risk score to predict the 1-year all-cause mortality in patients with End Stage Renal Disease (ESRD), and to compare it with previous scores. Data from a derivation sample (n = 6336 patients who started dialysis in 2015 in France) obtained by linking the REIN and the French National Health Insurance Information System databases were analyzed with multivariate Cox models to select risk factors to establish the score. A randomly chosen validation sample (n = 2716 patients who started dialysis in 2015) was used to validate the score and to compare it with the comorbidity indexes developed by Wright and Charlson. The ability to predict one-year mortality of the score constructed using REIN data linked to the medico-administrative database was not higher than that of the score constructed using only REIN data (i.e., Rennes score). The Rennes score included five comorbidities, albumin, and age. This score (AUC = 0.794, 95%CI: 0.768–0.821) outperformed both the Wright (AUC = 0.631, 95%CI: 0.621–0.639; p < 0.001) and Charlson (AUC = 0.703, 95%CI: 0.689–0.716; p < 0.001) indexes. Data from the REIN registry alone, collected at dialysis start, are sufficient to develop a risk score that can predict the one-year mortality in patients with ESRD. This simple score might help identifying high risk patients and proposing the most adapted care.

Publisher

Springer Science and Business Media LLC

Subject

Multidisciplinary

Cited by 1 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3