Dataset Information

Prognosing the risk of COVID-19 death through a machine learning-based routine blood panel: A retrospective study in Brazil.

ABSTRACT:

Background

Despite an extensive network of primary care availability, Brazil has suffered profoundly during the COVID-19 pandemic, experiencing the greatest sanitary collapse in its history. Thus, it is important to understand phenotype risk factors for SARS-CoV-2 infection severity in the Brazilian population in order to provide novel insights into the pathogenesis of the disease.

Objective

This study proposes to predict the risk of COVID-19 death through machine learning, using blood biomarkers data from patients admitted to two large hospitals in Brazil.

Methods

We retrospectively collected blood biomarkers data in a 24-h time window from 6,979 patients with COVID-19 confirmed by positive RT-PCR admitted to two large hospitals in Brazil, of whom 291 (4.2%) died and 6,688 (95.8%) were discharged. We then developed a large-scale exploration of risk models to predict the probability of COVID-19 severity, finally choosing the best performing model regarding the average AUROC. To improve generalizability, for each model five different testing scenarios were conducted, including two external validations.

Results

We developed a machine learning-based panel composed of parameters extracted from the complete blood count (lymphocytes, MCV, platelets and RDW), in addition to C-Reactive Protein, which yielded an average AUROC of 0.91 ± 0.01 to predict death by COVID-19 confirmed by positive RT-PCR within a 24-h window.

Conclusion

Our study suggests that routine laboratory variables could be useful to identify COVID-19 patients under higher risk of death using machine learning. Further studies are needed for validating the model in other populations and contexts, since the natural history of SARS-CoV-2 infection and its consequences on the hematopoietic system and other organs is still quite recent.

SUBMITTER: Araujo DC

PROVIDER: S-EPMC9327247 | biostudies-literature | 2022 Sep

REPOSITORIES: biostudies-literature

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Publications

Prognosing the risk of COVID-19 death through a machine learning-based routine blood panel: A retrospective study in Brazil.

Araújo Daniella Castro DC Veloso Adriano Alonso AA Borges Karina Braga Gomes KBG Carvalho Maria das Graças MDG

International journal of medical informatics 20220727

<h4>Background</h4>Despite an extensive network of primary care availability, Brazil has suffered profoundly during the COVID-19 pandemic, experiencing the greatest sanitary collapse in its history. Thus, it is important to understand phenotype risk factors for SARS-CoV-2 infection severity in the Brazilian population in order to provide novel insights into the pathogenesis of the disease.<h4>Objective</h4>This study proposes to predict the risk of COVID-19 death through machine learning, using ...[more]

PMID: 35908372

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Dataset Information

Prognosing the risk of COVID-19 death through a machine learning-based routine blood panel: A retrospective study in Brazil.

Background

Objective

Methods

Results

Conclusion

Publications

Prognosing the risk of COVID-19 death through a machine learning-based routine blood panel: A retrospective study in Brazil.

Similar Datasets

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