Suppr超能文献

开发并验证了一种新的基于人群的风险分层工具,用于预测死亡率、住院和医疗保健费用。

A new population-based risk stratification tool was developed and validated for predicting mortality, hospital admissions, and health care costs.

机构信息

National Centre for Healthcare Research and Pharmacoepidemiology, University of Milano-Bicocca, Milan, Italy; Laboratory of Healthcare Research and Pharmacoepidemiology, Unit of Biostatistics, Epidemiology and Public Health, Department of Statistics and Quantitative Methods, University of Milano-Bicocca, Milan, Italy.

National Centre for Healthcare Research and Pharmacoepidemiology, University of Milano-Bicocca, Milan, Italy; Laboratory of Healthcare Research and Pharmacoepidemiology, Unit of Biostatistics, Epidemiology and Public Health, Department of Statistics and Quantitative Methods, University of Milano-Bicocca, Milan, Italy.

出版信息

J Clin Epidemiol. 2019 Dec;116:62-71. doi: 10.1016/j.jclinepi.2019.08.009. Epub 2019 Aug 28.

Abstract

OBJECTIVES

The aim of this study was to develop a new population-based risk stratification tool (Chronic Related Score [CReSc]) for predicting 5-year mortality and other outcomes.

STUDY DESIGN AND SETTING

The score included 31 conditions selected from a list of 65 candidates whose weights were assigned according to the Cox model coefficients. The model was built from a sample of 5.4 million National Health Service (NHS) beneficiaries from the Italian Lombardy Region and applied to the remaining 2.7 million NHS beneficiaries. Predictive performance was assessed by discrimination and calibration. CReSc ability in predicting secondary endpoints (i.e., hospital admissions and health care costs) was investigated. Finally, the relationship between CReSc and income was considered.

RESULTS

Among individuals aged 50-85 years, CReSc performance showed (1) an area under the receiver operating characteristic curve of 0.730, (2) an improved reclassification from 44% to 52% with respect to other scores, and (3) a remarkable calibration. A trend toward increasing rates of all the considered endpoints as CReSc increases was observed. Compared with individuals on low-intermediate income, NHS beneficiaries on high income showed better CReSc profile.

CONCLUSION

We developed a risk stratification tool able to predict mortality, costs, and hospital admissions. The application of CReSc may generate clinically and operationally important effects.

摘要

目的

本研究旨在开发一种新的基于人群的风险分层工具(慢性相关评分[CReSc]),用于预测 5 年死亡率和其他结局。

研究设计和设置

该评分纳入了从 65 种候选条件中选出的 31 种条件,其权重根据 Cox 模型系数分配。该模型基于意大利伦巴第地区 540 万国家卫生服务(NHS)受益人的样本构建,并应用于剩余的 270 万 NHS 受益人。通过区分度和校准来评估预测性能。研究了 CReSc 预测次要结局(即住院和医疗保健费用)的能力。最后,还考虑了 CReSc 与收入之间的关系。

结果

在 50-85 岁人群中,CReSc 的表现为:(1)受试者工作特征曲线下面积为 0.730;(2)与其他评分相比,重新分类的能力从 44%提高到 52%;(3)具有显著的校准度。观察到随着 CReSc 的增加,所有考虑的结局的发生率呈上升趋势。与中低收入的 NHS 受益人相比,高收入的 NHS 受益人具有更好的 CReSc 评分。

结论

我们开发了一种能够预测死亡率、成本和住院的风险分层工具。CReSc 的应用可能会产生重要的临床和操作效果。

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验