在医院、初级保健和养老院环境中预测老年人群死亡风险的8种COVID-19预后模型的外部验证研究方案。

Anum Zahra, Kim Luijken, Evertine J Abbink, Jesse M van den Berg, Marieke T Blom, Petra Elders, Jan Festen, Jacobijn Gussekloo, Karlijn J Joling, René Melis, Simon Mooijaart, Jeannette B Peters, Harmke A Polinder-Bos, Bas F M van Raaij, Annemieke Smorenberg, Hannah M la Roi-Teeuw, Karel G M Moons, Maarten van Smeden
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引用次数: 0

摘要

背景:2019冠状病毒病大流行在全球范围内影响巨大,已知对老年人口的影响尤其严重。本文概述了预测老年人群出现COVID-19后死亡风险的预后模型的外部验证方案。这些预后模型最初是在成年人群中开发的,并将在三种医疗保健环境中的老年人群(≥70岁)中进行验证:医院环境、初级保健环境和养老院环境。方法:基于对COVID-19预测模型的活体系统回顾,我们确定了8种预测COVID-19感染成人死亡风险的预后模型(5种COVID-19特异性模型:GAL-COVID-19死亡率、4C死亡率评分、NEWS2 +模型、Xie模型和Wang临床模型以及3种预先存在的预后评分:APACHE-II、CURB65、SOFA)。这8个模型将在荷兰老年人口的6个不同队列中进行验证(3个医院队列、2个初级保健队列和1个养老院队列)。所有预后模型都将在医院环境中进行验证,而GAL-COVID-19死亡率模型将在医院、初级保健和养老院环境中进行验证。该研究将包括2020年3月至2020年12月(敏感度分析中至2021年12月)年龄≥70岁且高度疑似或pcr确诊的COVID-19感染的个体。预测性能将根据每个队列中每个预后模型的区分、校准和决策曲线进行评估。对于有校准错误迹象的预测模型,将执行拦截更新,之后将重新评估预测性能。讨论:深入了解现有预测模型在最脆弱人群中的表现,阐明了在将模型应用于老年人群时需要对COVID-19预测模型进行定制的程度。这种洞察力对于未来可能出现的COVID-19大流行浪潮或未来的大流行非常重要。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

A study protocol of external validation of eight COVID-19 prognostic models for predicting mortality risk in older populations in a hospital, primary care, and nursing home setting.

A study protocol of external validation of eight COVID-19 prognostic models for predicting mortality risk in older populations in a hospital, primary care, and nursing home setting.

Background: The COVID-19 pandemic has a large impact worldwide and is known to particularly affect the older population. This paper outlines the protocol for external validation of prognostic models predicting mortality risk after presentation with COVID-19 in the older population. These prognostic models were originally developed in an adult population and will be validated in an older population (≥ 70 years of age) in three healthcare settings: the hospital setting, the primary care setting, and the nursing home setting.

Methods: Based on a living systematic review of COVID-19 prediction models, we identified eight prognostic models predicting the risk of mortality in adults with a COVID-19 infection (five COVID-19 specific models: GAL-COVID-19 mortality, 4C Mortality Score, NEWS2 + model, Xie model, and Wang clinical model and three pre-existing prognostic scores: APACHE-II, CURB65, SOFA). These eight models will be validated in six different cohorts of the Dutch older population (three hospital cohorts, two primary care cohorts, and a nursing home cohort). All prognostic models will be validated in a hospital setting while the GAL-COVID-19 mortality model will be validated in hospital, primary care, and nursing home settings. The study will include individuals ≥ 70 years of age with a highly suspected or PCR-confirmed COVID-19 infection from March 2020 to December 2020 (and up to December 2021 in a sensitivity analysis). The predictive performance will be evaluated in terms of discrimination, calibration, and decision curves for each of the prognostic models in each cohort individually. For prognostic models with indications of miscalibration, an intercept update will be performed after which predictive performance will be re-evaluated.

Discussion: Insight into the performance of existing prognostic models in one of the most vulnerable populations clarifies the extent to which tailoring of COVID-19 prognostic models is needed when models are applied to the older population. Such insight will be important for possible future waves of the COVID-19 pandemic or future pandemics.

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