利用常规初级保健电子健康记录数据开发和外部验证电子虚弱指数2。

IF 6 2区 医学 Q1 GERIATRICS & GERONTOLOGY
Kate Best, Farag Shuweihdi, Juan Carlos Bazo Alvarez, Samuel Relton, Christina Avgerinou, Danielle Nimmons, Irene Petersen, Maria Pujades-Rodriguez, Simon Paul Conroy, Kate Walters, Robert M West, Andrew Clegg
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引用次数: 0

摘要

背景:电子虚弱指数(eFI)在英国初级保健电子健康记录系统中得到全国实施,以支持常规虚弱识别。原始的eFI存在一些局限性,如赤字变量的权重相等,已知解决变量缺乏时间约束以及脆弱类别切点的定义。我们开发并外部验证了eFI2预测模型来预测家庭护理包的综合风险;因跌倒/骨折住院;入住护理院;或一年内的死亡率,解决了原始eFI的局限性。方法:使用2018年两个独立回顾性队列中年龄≥65岁成年人的相关初级、二级和社会护理数据;布拉德福德人口使用连接布拉德福德数据集(发展队列,78760例患者)和威尔士人口,来自安全匿名信息链接数据库(外部验证队列,660417例患者)。候选预测因子包括原始的eFI变量,补充了文献综述和临床专业知识提供的变量。综合结果采用Cox回归建模。结果:经内部验证,该模型判别性好(C-index = 0.803, Nagelkerke’s R2 = 0.0971),定标效果好(定标斜率= 1.00)。在外部验证中,模型具有较好的判别性(C-index = 0.723, Nagelkerke’s R2 = 0.064),但存在一定的误校正(校正斜率= 1.104)。结论:eFI2在原始eFI的基础上,对关键的衰弱相关结果进行了强有力的预测。我们使用新颖的方法来开发和验证eFI2,将推动国际上与脆弱性相关的研究领域,建立一个新的方法标准。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Development and external validation of the electronic frailty index 2 using routine primary care electronic health record data.

Background: The electronic frailty index (eFI) is nationally implemented into UK primary care electronic health record systems to support routine identification of frailty. The original eFI has some limitations such as equal weighting of deficit variables, lack of time constraints on variables known to resolve and definition of frailty category cut-points. We have developed and externally validated the eFI2 prediction model to predict the composite risk of home care package; hospital admission for fall/fracture; care home admission; or mortality within one year, addressing the limitations of the original eFI.

Methods: Linked primary, secondary and social care data from two independent retrospective cohorts of adults aged ≥65 in 2018 was used; the population of Bradford using the Connected Bradford dataset (development cohort, 78 760 patients) and the population of Wales, from the Secure Anonymised Information Linkage databank (external validation cohort, 660 417 patients). Candidate predictors included the original eFI variables, supplemented with variables informed by literature reviews and clinical expertise. The composite outcome was modelled using Cox regression.

Results: In internal validation the model had excellent discrimination (C-index = 0.803, Nagelkerke's R2 = 0.0971) with good calibration (Calibration slope = 1.00). In external validation, the model had good discrimination (C-index = 0.723, Nagelkerke's R2 = 0.064), with some evidence of miscalibration (Calibration slope = 1.104).

Conclusions: The eFI2 demonstrates robust prediction for key frailty-related outcomes, improving on the original eFI. Our use of novel methodology to develop and validate the eFI2 will advance the field of frailty-related research internationally, setting a new methodological standard.

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来源期刊
Age and ageing
Age and ageing 医学-老年医学
CiteScore
9.20
自引率
6.00%
发文量
796
审稿时长
4-8 weeks
期刊介绍: Age and Ageing is an international journal publishing refereed original articles and commissioned reviews on geriatric medicine and gerontology. Its range includes research on ageing and clinical, epidemiological, and psychological aspects of later life.
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