Istituto Nazionale di Fisica Nucleare (INFN), Sezione di Bari, Via A. Orabona 4, 70125, Bari, Italy.
Dipartimento di Scienze mediche di base, Neuroscienze e organi di senso, Piazza G. Cesare 11, 70124, Bari, Italy.
Sci Rep. 2021 Dec 31;11(1):24527. doi: 10.1038/s41598-021-04162-2.
The identification of factors associated to COVID-19 mortality is important to design effective containment measures and safeguard at-risk categories. In the last year, several investigations have tried to ascertain key features to predict the COVID-19 mortality tolls in relation to country-specific dynamics and population structure. Most studies focused on the first wave of the COVID-19 pandemic observed in the first half of 2020. Numerous studies have reported significant associations between COVID-19 mortality and relevant variables, for instance obesity, healthcare system indicators such as hospital beds density, and bacillus Calmette-Guerin immunization. In this work, we investigated the role of ABO/Rh blood groups at three different stages of the pandemic while accounting for demographic, economic, and health system related confounding factors. Using a machine learning approach, we found that the "B+" blood group frequency is an important factor at all stages of the pandemic, confirming previous findings that blood groups are linked to COVID-19 severity and fatal outcome.
确定与 COVID-19 死亡率相关的因素对于设计有效的遏制措施和保护高危人群非常重要。在过去的一年中,已有多项研究试图确定关键特征,以预测与各国动态和人口结构相关的 COVID-19 死亡率。大多数研究都集中在 2020 年上半年观察到的 COVID-19 第一波疫情上。许多研究报告称,COVID-19 死亡率与肥胖症等相关变量、医疗保健系统指标(如医院床位密度)和卡介苗免疫之间存在显著关联。在这项工作中,我们研究了 ABO/Rh 血型在大流行的三个不同阶段的作用,同时考虑了人口统计学、经济和卫生系统相关的混杂因素。我们使用机器学习方法发现,“B+”血型频率在大流行的所有阶段都是一个重要因素,这证实了之前的研究结果,即血型与 COVID-19 的严重程度和致命后果有关。