Early detection of COVID-19 using characteristic leucocyte differential count (CLDC)

• 作者: Jessica Rogge Mark R Baker
• 来源期刊: TMR生命研究
• 学科: 医学
• 关键词: COVID-19 SARS-CoV-2 H1N1 H5N1 PANDEMIC testing Early-diagnosis Mass screening Hometesting
• 年，卷（期）: 2020,（3）
• 页码范围: 101-107
• 页数: 7页
• 分类号: R37

摘要

Background:COVID-19 is an acute infection of the respiratory tract that emerged in late 2019.Currently identified methods for identifying the severe acute respiratory syndrome coronavirus 2 virus include methods that detect the presence of the virus itself,such as reverse transcription PCR and isothermal amplification methods,and those that detect antibodies produced in response to the infection.Reverse transcription PCR and quantitative PCR are highly sensitive but have a narrow time window of sensitivity.Methods:We investigated a new method to detect the occurrence of severe acute respiratory syndrome coronavirus 2 by analyzing the early rise in leukocyte levels which has a characteristic set of ratios of leukocyte types which identify the viral pathogen and distinguish it from a number of others.We used the Albert Einstein Hospital,São Paulo data set and the Athena AI System to validate this method.Results:The sensitivity of the test is up to 98.67%prediction of positives from full blood count results.Conclusion:We have discovered an early test for SARS-CoV-2 which can be performed using a black-boxed AI to give high sensitivity prediction of COVID-19 infection.