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Visceral Adiposity and Severe COVID-19 Disease: Application of an Artificial Intelligence Algorithm to Improve Clinical Risk Prediction.
- 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]
- Subjects :
- *COVID-19
*ARTIFICIAL intelligence
*COMPUTED tomography
*MEDICAL protocols
*OBESITY
Subjects
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