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Clinical Profiles at the Time of Diagnosis of SARS-CoV-2 Infection in Costa Rica During the Pre-vaccination Period Using a Machine Learning Approach

引用

Phenomics 2022年第5期2卷 312-322页

作者： Jose Arturo Molina-Mora Alejandra González Sergio Jiménez-Morgan Estela Cordero-Laurent Hebleen Brenes claudio soto-garita Jorge Sequeira-soto Francisco Duarte-Martínez Centro de Investigación en Enfermedades Tropicales(CIET)and Facultad de Microbiología Universidad de Costa RicaSan José2060Costa Rica Instituto Costarricense de Investigación y Enseñanza en Nutrición y Salud(INCIENSA) Tres Ríos 30301Costa Rica Escuela de Medicina Universidad de Costa RicaSan José2060Costa Rica

The clinical manifestations of COVID-19,caused by the SARS-CoV-2,define a large spectrum of symptoms that are mainly dependent on the human host *** Costa Rica,more than 169,000 cases and 2185 deaths were reported during the year 2020,the pre-vaccination *** describe the clinical presentations at the time of diagnosis of SARS-CoV-2 infection in Costa Rica during the pre-vaccination period,we implemented a symptom-based clustering using machine learning to identify clusters or clinical profiles at the population level among 18,974 records of positive *** were compared based on symptoms,risk factors,viral load,and genomic features of the SARS-CoV-2 sequence.A total of 18 symptoms at time of diagnosis of SARS-CoV-2 infection were reported with a frequency>1%,and those were used to identify seven clinical profiles with a specific composition of clinical *** the comparison between clusters,a lower viral load was found for the asymptomatic group,while the risk factors and the SARS-CoV-2 genomic features were distributed among all the *** other distribution patterns were found for age,sex,vital status,and *** conclusion,during the pre-vaccination time in Costa Rica,the symptoms at the time of diagnosis of SARS-CoV-2 infection were described in clinical *** host co-morbidities and the SARS-CoV-2 genotypes are not specific of a particular profile,rather they are present in all the groups,including asymptomatic *** addition,this information can be used for decision-making by the local healthcare institutions(first point of contact with health professionals,case definition,or infrastructure).In further analyses,these results will be compared against the profiles of cases during the vaccination period.

关键词： COVID-19 Costa Rica Machine learning Diagnosis SARS-CoV-2 Clinical profiles

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