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Article

Increased Pace of Aging in COVID-Related Mortality

1
Deep Longevity, Hong Kong, China
2
Department of Emergency Medicine, Lincoln Medical and Mental Health Center, Bronx, NY 10451, USA
3
Meta-Research Innovation Center at Stanford (METRICS), Stanford University, Stanford, CA 94305, USA
4
International Center for Multimorbidity and Complexity in Medicine (ICMC), Universität Zürich, 8006 Zürich, Switzerland
5
Basic and Clinical Medicine Department, Shanghai University of Medicine and Health Sciences, Shanghai 201318, China
6
NYC Health + Hospitals, Lincoln Medical Center, Bronx, NY 10451, USA
7
Insilico Medicine, Hong Kong Science and Technology Park, Hong Kong, China
8
The Buck Institute for Research on Aging, Novato, CA 94945, USA
*
Author to whom correspondence should be addressed.
Academic Editors: K. H. Katie Chan, Ka-Chun Wong, Brian Chen and Jie Li
Life 2021, 11(8), 730; https://doi.org/10.3390/life11080730
Received: 31 May 2021 / Revised: 19 June 2021 / Accepted: 29 June 2021 / Published: 22 July 2021
Identifying prognostic biomarkers and risk stratification for COVID-19 patients is a challenging necessity. One of the core survival factors is patient age. However, chronological age is often severely biased due to dormant conditions and existing comorbidities. In this retrospective cohort study, we analyzed the data from 5315 COVID-19 patients (1689 lethal cases) admitted to 11 public hospitals in New York City from 1 March 2020 to 1 December. We calculated patients’ pace of aging with BloodAge—a deep learning aging clock trained on clinical blood tests. We further constructed survival models to explore the prognostic value of biological age compared to that of chronological age. A COVID-19 score was developed to support a practical patient stratification in a clinical setting. Lethal COVID-19 cases had higher predicted age, compared to non-lethal cases (Δ = 0.8–1.6 years). Increased pace of aging was a significant risk factor of COVID-related mortality (hazard ratio = 1.026 per year, 95% CI = 1.001–1.052). According to our logistic regression model, the pace of aging had a greater impact (adjusted odds ratio = 1.09 ± 0.00, per year) than chronological age (1.04 ± 0.00, per year) on the lethal infection outcome. Our results show that a biological age measure, derived from routine clinical blood tests, adds predictive power to COVID-19 survival models. View Full-Text
Keywords: aging; biogerontology; COVID; aging clock; prognostics aging; biogerontology; COVID; aging clock; prognostics
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    Link: https://osf.io/t6vgd/?view_only=d4155de6b192450e86fb2323e5bedab0
    Description: The cherrypy implementation of the reported COVID risk score that runs locally. You will need Python 3 and all the dependencies from the import statement of covid_risk.py After launching the script, the calculator can be accessed at localhost:9028 in any browser.
MDPI and ACS Style

Galkin, F.; Parish, A.; Bischof, E.; Zhang, J.; Mamoshina, P.; Zhavoronkov, A. Increased Pace of Aging in COVID-Related Mortality. Life 2021, 11, 730. https://doi.org/10.3390/life11080730

AMA Style

Galkin F, Parish A, Bischof E, Zhang J, Mamoshina P, Zhavoronkov A. Increased Pace of Aging in COVID-Related Mortality. Life. 2021; 11(8):730. https://doi.org/10.3390/life11080730

Chicago/Turabian Style

Galkin, Fedor, Austin Parish, Evelyne Bischof, John Zhang, Polina Mamoshina, and Alex Zhavoronkov. 2021. "Increased Pace of Aging in COVID-Related Mortality" Life 11, no. 8: 730. https://doi.org/10.3390/life11080730

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