2020-2022年老年人COVID-19死亡风险的集体和个人评估

Chaobao Zhang, Hongzhi Wang, Zilu Wen, Zhijun Bao, Xiangqi Li
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引用次数: 3

摘要

2019年冠状病毒病(COVID-19)在全球范围内造成了深刻的破坏。对于一个群体或个人来说,评估死亡风险对于做出预防性决策至关重要。方法:对近1亿例患者的临床资料进行统计分析。用Python开发了一个软件和一个在线评估工具来评估死亡风险。结果:我们的分析显示,76.51%的covid -19相关死亡发生在65岁以上的人群中,其中与虚弱相关的死亡占这些病例的80%以上。此外,超过80%的报告死亡涉及未接种疫苗的个人。在衰老和虚弱相关的死亡之间观察到明显的重叠,两者都与潜在的健康状况有关。对于那些至少有两种合并症的人来说,虚弱的比例和covid -19相关死亡的比例都接近75%。随后,我们建立了一个计算死亡人数的公式,并使用来自20个国家和地区的数据对其进行了验证。利用这个公式,我们开发并验证了一个智能软件,用于预测特定人群的死亡风险。为了方便在个人层面上快速筛选风险,我们还引入了一个包含六个问题的在线评估工具。结论:本研究考察了基础疾病、虚弱程度、年龄和疫苗接种史对covid -19相关死亡率的影响,形成了一套完善的软件和用户友好的在线量表来评估死亡风险。这些工具为知情决策提供了宝贵的帮助。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Collective and Individual Assessment of the Risk of Death from COVID-19 for the Elderly, 2020-2022.

Collective and Individual Assessment of the Risk of Death from COVID-19 for the Elderly, 2020-2022.

Collective and Individual Assessment of the Risk of Death from COVID-19 for the Elderly, 2020-2022.

Collective and Individual Assessment of the Risk of Death from COVID-19 for the Elderly, 2020-2022.

Introduction: Coronavirus disease 2019 (COVID-19) has had profound disruptions worldwide. For a population or individual, it is critical to assess the risk of death for making preventative decisions.

Methods: In this study, clinical data from approximately 100 million cases were statistically analyzed. A software and an online assessment tool were developed in Python to evaluate the risk of mortality.

Results: Our analysis revealed that 76.51% of COVID-19-related fatalities occurred among individuals aged over 65 years, with frailty-associated deaths accounting for more than 80% of these cases. Furthermore, over 80% of the reported deaths involved unvaccinated individuals. A notable overlap was observed between aging and frailty-associated deaths, both of which were connected to underlying health conditions. For those with at least two comorbidities, the proportion of frailty and the proportion of COVID-19-related death were both close to 75 percent. Subsequently, we established a formula to calculate the number of deaths, which was validated using data from twenty countries and regions. Using this formula, we developed and verified an intelligent software designed to predict the death risk for a given population. To facilitate rapid risk screening on an individual level, we also introduced a six-question online assessment tool.

Conclusions: This study examined the impact of underlying diseases, frailty, age, and vaccination history on COVID-19-related mortality, resulting in a sophisticated software and a user-friendly online scale to assess mortality risk. These tools offer valuable assistance in informed decision-making.

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