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Visceral Adiposity and Severe COVID-19 Disease: Application of an Artificial Intelligence Algorithm to Improve
Alexander Goehler1,2, Tzu-Ming Harry Hsu1, Jacqueline A Seiglie3
1Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Boston, Massachusetts, USA.
Insights
High visceral adipose tissue (VAT) indicates a greater risk of severe COVID-19 outcomes, independent of body mass index (BMI). Artificial intelligence (AI) can help quantify VAT for better risk prediction in patients hospitalized with coronavirus disease 2019.
Area of Science:
- Medical Imaging
- Cardiovascular Science
- Infectious Diseases
Background:
- Obesity is a known risk factor for severe outcomes in patients hospitalized with coronavirus disease 2019 (COVID-19).
- The role of visceral adipose tissue (VAT), an indicator of central obesity, in COVID-19 severity is not fully understood, especially independent of body mass index (BMI).
Purpose of the Study:
- To test the hypothesis that VAT is associated with severe outcomes in patients hospitalized with COVID-19, independent of BMI.
- To evaluate the utility of artificial intelligence (AI) in quantifying VAT for risk stratification.
Main Methods:
- Analysis of data from the Massachusetts General Hospital COVID-19 Data Registry, including 378 patients with polymerase chain reaction-confirmed severe acute respiratory syndrome coronavirus 2 infection.
- Quantification of VAT using a validated, automated AI algorithm from computed tomography (CT) scans.
- Kaplan-Meier curves and Cox proportional hazards regression to assess the relationship between VAT (dichotomized as high/low at ≥100 cm²), BMI, and a composite outcome of death or intubation over 28 days, adjusting for covariates.
Main Results:
- Participants with high VAT demonstrated a significantly greater risk of death or intubation compared to those with low VAT (P < .005).
- This association remained significant, particularly in individuals with BMI <30 kg/m².
- In multivariable models, high VAT was independently associated with increased risk (adjusted hazard ratio [aHR], 1.97; 95% CI, 1.24-3.09), while BMI lost its significance (aHR for obese vs. normal BMI, 1.14; 95% CI, 0.71-1.82).
Conclusions:
- High VAT is a significant independent predictor of severe COVID-19 outcomes, including death or intubation.
- VAT quantification using AI provides more precise risk stratification for COVID-19 patients than BMI alone.
- AI-driven VAT assessment holds promise for routine clinical use in improving COVID-19 risk prediction.
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.
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