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Visceral Adiposity and Severe COVID-19 Disease: Application of an Artificial Intelligence Algorithm to Improve Clinical Risk Prediction.

Authors :
Goehler, Alexander
Hsu, Tzu-Ming Harry
Seiglie, Jacqueline A
Siedner, Mark J
Lo, Janet
Triant, Virginia
Hsu, John
Foulkes, Andrea
Bassett, Ingrid
Khorasani, Ramin
Wexler, Deborah J
Szolovits, Peter
Meigs, James B
Manne-Goehler, Jennifer
Source :
Open Forum Infectious Diseases. Jul2021, Vol. 8 Issue 7, p1-7. 7p.
Publication Year :
2021

Abstract

Background Obesity has been linked to severe clinical outcomes among people who are hospitalized with coronavirus disease 2019 (COVID-19). We tested the hypothesis that visceral adipose tissue (VAT) is associated with severe outcomes in patients hospitalized with COVID-19, independent of body mass index (BMI). Methods We analyzed data from the Massachusetts General Hospital COVID-19 Data Registry, which included patients admitted with polymerase chain reaction–confirmed severe acute respiratory syndrome coronavirus 2 infection from March 11 to May 4, 2020. We used a validated, fully automated artificial intelligence (AI) algorithm to quantify VAT from computed tomography (CT) scans during or before the hospital admission. VAT quantification took an average of 2 ± 0.5 seconds per patient. We dichotomized VAT as high and low at a threshold of ≥100 cm2 and used Kaplan-Meier curves and Cox proportional hazards regression to assess the relationship between VAT and death or intubation over 28 days, adjusting for age, sex, race, BMI, and diabetes status. Results A total of 378 participants had CT imaging. Kaplan-Meier curves showed that participants with high VAT had a greater risk of the outcome compared with those with low VAT (P  < .005), especially in those with BMI <30 kg/m2 (P  < .005). In multivariable models, the adjusted hazard ratio (aHR) for high vs low VAT was unchanged (aHR, 1.97; 95% CI, 1.24–3.09), whereas BMI was no longer significant (aHR for obese vs normal BMI, 1.14; 95% CI, 0.71–1.82). Conclusions High VAT is associated with a greater risk of severe disease or death in COVID-19 and can offer more precise information to risk-stratify individuals beyond BMI. AI offers a promising approach to routinely ascertain VAT and improve clinical risk prediction in COVID-19. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
23288957
Volume :
8
Issue :
7
Database :
Academic Search Index
Journal :
Open Forum Infectious Diseases
Publication Type :
Academic Journal
Accession number :
151803537
Full Text :
https://doi.org/10.1093/ofid/ofab275