Predictive Biomarkers of Intensive Care Unit and Mechanical Ventilation Duration in Critically-Ill Coronavirus Disease 2019 Patients

<h3>Introduction</h3><p dir="ltr">Detection of early metabolic changes in critically-ill coronavirus disease 2019 (COVID-19) patients under invasive mechanical ventilation (IMV) at the intensive care unit (ICU) could predict recovery patterns and help in disease managemen...

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Main Author: Sara Taleb (11264352) (author)
Other Authors: Hadi M. Yassine (4675846) (author), Fatiha M. Benslimane (6695087) (author), Maria K. Smatti (4675852) (author), Sven Schuchardt (9681428) (author), Omar Albagha (8977856) (author), Asmaa A. Al-Thani (11264355) (author), Ali Ait Hssain (9538617) (author), Ilhame Diboun (3522413) (author), Mohamed A. Elrayess (7956179) (author)
Published: 2021
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Summary:<h3>Introduction</h3><p dir="ltr">Detection of early metabolic changes in critically-ill coronavirus disease 2019 (COVID-19) patients under invasive mechanical ventilation (IMV) at the intensive care unit (ICU) could predict recovery patterns and help in disease management.</p><p><br></p><h3>Methods</h3><p dir="ltr">Targeted metabolomics of serum samples from 39 COVID-19 patients under IMV in ICU was performed within 48 h of intubation and a week later. A generalized linear model (GLM) was used to identify, at both time points, metabolites and clinical traits that predict the length of stay (LOS) at ICU (short ≤ 14 days/long >14 days) as well as the duration under IMV. All models were initially trained on a set of randomly selected individuals and validated on the remaining individuals in the cohort. Further validation in recently published metabolomics data of COVID-19 severity was performed.</p><p><br></p><h3>Results</h3><p dir="ltr">A model based on hypoxanthine and betaine measured at first time point was best at predicting whether a patient is likely to experience a short or long stay at ICU [area under curve (AUC) = 0.92]. A further model based on kynurenine, 3-methylhistidine, ornithine, p-cresol sulfate, and C24.0 sphingomyelin, measured 1 week later, accurately predicted the duration of IMV (Pearson correlation = 0.94). Both predictive models outperformed Acute Physiology and Chronic Health Evaluation II (APACHE II) scores and differentiated COVID-19 severity in published data.</p><p><br></p><h3>Conclusion</h3><p dir="ltr">This study has identified specific metabolites that can predict in advance LOS and IMV, which could help in the management of COVID-19 cases at ICU.</p><p dir="ltr"><br></p><h2>Other Information</h2><p dir="ltr">Published in: Frontiers in Medicine<br>License: <a href="https://creativecommons.org/licenses/by/4.0/" target="_blank">https://creativecommons.org/licenses/by/4.0/</a><br>See article on publisher's website: <a href="https://dx.doi.org/10.3389/fmed.2021.733657" target="_blank">https://dx.doi.org/10.3389/fmed.2021.733657</a></p>