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

Association of excess visceral fat and severe illness in hospitalized COVID-19 patients in Japan: a retrospective cohort study

BACKGROUND/OBJECTIVES

Obesity, defined by body mass index (BMI), is a well-known risk factor for the severity of coronavirus disease 2019 (COVID-19). Adipose tissue distribution has also been implicated as an important factor in the body's response to infection, and excess visceral fat (VF), which is prevalent in Japanese, may contribute significantly to the severity. Therefore, this study aimed to evaluate the association of obesity and VF with COVID-19 severe illness in Japan.

SUBJECTS/METHODS

This retrospective cohort study involved 550 COVID-19 patients admitted to a tertiary care hospital with BMI and body composition data, including VF. The primary endpoint was severe illness, including death, due to COVID-19 during hospitalization. Logistic regression analysis was applied to examine the quartiles of BMI and VF on severe illness after adjusting for covariates such as age, sex, subcutaneous fat, paraspinal muscle radiodensity, and comorbidities affecting VF (COPD, cancer within 5 years, immunosuppressive agent use).

RESULTS

The median age was 56.0 years; 71.8% were males. During hospitalization, 82 (14.9%) experienced COVID-19 severe illness. In the multivariate logistic regression analysis, Q4 of BMI was not significantly associated with severe illness compared to Q1 of BMI (OR 1.03; 95% CI 0.37-2.86; p = 0.95). Conversely, Q3 and Q4 of VF showed a higher risk for severe illness compared to Q1 of VF (OR 2.68; 95% CI 1.01-7.11; p = 0.04, OR 3.66; 95% CI 1.30-10.26; p = 0.01, respectively). Stratified analysis by BMI and adjusted for covariates showed the positive association of VF with severe illness only in the BMI < 25 kg/m2 group.

CONCLUSIONS

High BMI was not an independent risk factor for COVID-19 severe illness in hospitalized patients in Japan, whereas excess VF significantly influenced severe illness, especially in patients with a BMI < 25 kg/m2.

Computed Tomography-Defined Body Composition as Prognostic Parameter in Acute Mesenteric Ischemia

INTRODUCTION

Body composition comprising low-skeletal muscle mass (LSMM) and subcutaneous and visceral adipose tissue (SAT and VAT) can be assessed by using cross-sectional imaging modalities. Previous analyses suggest that these parameters harbor prognostic relevance in various diseases. Aim of this study was to analyze possible associations of body composition parameters on mortality in patients with clinically suspected acute mesenteric ischemia (AMI).

METHODS

All patients with clinically suspected AMI were retrospectively assessed between 2016 and 2020. Overall, 137 patients (52 female patients, 37.9%) with a median age of 71 years were included in the present analysis. For all patients, the preoperative abdominal computed tomography (CT) was used to calculate LSMM, VAT, and SAT.

RESULTS

Overall, 94 patients (68.6%) of the patient cohort died within 30 days within a median of 2 days, range 1-39 days. Of these, 27 patients (19.7%) died within 24 h. According to the CT, 101 patients (73.7%) were classified as being visceral obese, 102 patients (74.5%) as being sarcopenic, and 69 patients (50.4%) as being sarcopenic obese. Skeletal muscle index (SMI) was lower in non-survivors compared to survivors (37.5 ± 12.4 cm2/m2 vs. 44.1 ± 13.9 cm2/m2, p = 0.01). There were no associations between body composition parameters with mortality in days (SMI r = 0.07, p = 0.48, SAT r = -0.03, p = 0.77, and VAT r = 0.04, p = 0.68, respectively). In Cox regression analysis, a nonsignificant trend for visceral obesity was observed (HR: 0.62, 95% CI: 0.36-1.05, p = 0.07).

CONCLUSION

SMI might be a valuable CT-based parameter, which could help discriminate between survivors and non-survivors. Further studies are needed to elucidate the associations between body composition and survival in patients with AMI.

Assessment of body composition in adults hospitalized with acute COVID-19: a scoping review

Introduction

Body composition (BC) assessment can supply accurate information for in-hospital nutritional evaluation. The aim of this study was to explore in the literature how the studies assessed BC, for what purpose, and investigate the role of BC findings in COVID-19 hospitalized patients' outcomes.

Methods

A scoping review was conducted according to the methodology available on the Joanna Briggs Institute website. We used the PCC acronym for the systematic search (population: adults with COVID-19, concept: assessment of BC, context: hospital setting) and performed it on PubMed, Scopus, and the Web of Science on 16 September 2022. Eligibility criteria consisted of the utilization of BC assessment tools in COVID-19 patients. Studies in which BC was solely measured with anthropometry (perimeters and skinfolds) were excluded. No language restriction was applied.

Results

Fifty-five studies were eligible for the review. Out of the 55 studies, 36 used computed tomography (CT), 13 used bioelectrical impedance (BIA), and 6 used ultrasound (US). No studies with D3-creatinine, 24  h urine excretion, dual-energy X-ray absorptiometry, or magnetic resonance were retrieved. BC was mainly assessed to test associations with adverse outcomes such as disease severity and mortality.

Discussion

Studies assessing BC in hospitalized patients with COVID-19 used mainly CT and BIA and associated the parameters with severity and mortality. There is little evidence of BC being assessed by other methods, as well as studies on BC changes during hospitalization.

CT Scan-Derived Muscle, But Not Fat, Area Independently Predicts Mortality in COVID-19

BACKGROUND

COVID-19 has demonstrated a highly variable disease course, from asymptomatic to severe illness and eventually death. Clinical parameters, as included in the 4C Mortality Score, can predict mortality accurately in COVID-19. Additionally, CT scan-derived low muscle and high adipose tissue cross-sectional areas (CSAs) have been associated with adverse outcomes in COVID-19.

RESEARCH QUESTION

Are CT scan-derived muscle and adipose tissue CSAs associated with 30-day in-hospital mortality in COVID-19, independent of 4C Mortality Score?

STUDY DESIGN AND METHODS

This was a retrospective cohort analysis of patients with COVID-19 seeking treatment at the ED of two participating hospitals during the first wave of the pandemic. Skeletal muscle and adipose tissue CSAs were collected from routine chest CT-scans at admission. Pectoralis muscle CSA was demarcated manually at the fourth thoracic vertebra, and skeletal muscle and adipose tissue CSA was demarcated at the first lumbar vertebra level. Outcome measures and 4C Mortality Score items were retrieved from medical records.

RESULTS

Data from 578 patients were analyzed (64.6% men; mean age, 67.7 ± 13.5 years; 18.2% 30-day in-hospital mortality). Patients who died within 30 days demonstrated lower pectoralis CSA (median, 32.6 [interquartile range (IQR), 24.3-38.8] vs 35.4 [IQR, 27.2-44.2]; P = .002) than survivors, whereas visceral adipose tissue CSA was higher (median, 151.1 [IQR, 93.6-219.7] vs 112.9 [IQR, 63.7-174.1]; P = .013). In multivariate analyses, low pectoralis muscle CSA remained associated with 30-day in-hospital mortality when adjusted for 4C Mortality Score (hazard ratio, 0.98; 95% CI, 0.96-1.00; P = .038).

INTERPRETATION

CT scan-derived low pectoralis muscle CSA is associated significantly with higher 30-day in-hospital mortality in patients with COVID-19 independently of the 4C Mortality Score.

The role of diet and nutrition in the management of COPD

In 2014, the European Respiratory Society published a statement on nutritional assessment and therapy in COPD. Since then, increasing research has been performed on the role of diet and nutrition in the prevention and management of COPD. Here, we provide an overview of recent scientific advances and clinical implications. Evidence for a potential role of diet and nutrition as a risk factor in the development of COPD has been accumulating and is reflected in the dietary patterns of patients with COPD. Consuming a healthy diet should, therefore, be promoted in patients with COPD. Distinct COPD phenotypes have been identified incorporating nutritional status, ranging from cachexia and frailty to obesity. The importance of body composition assessment and the need for tailored nutritional screening instruments is further highlighted. Dietary interventions and targeted single or multi-nutrient supplementation can be beneficial when optimal timing is considered. The therapeutic window of opportunity for nutritional interventions during and recovering from an acute exacerbation and hospitalisation is underexplored.

Adipokines as Diagnostic and Prognostic Markers for the Severity of COVID-19

Accumulating evidence implicates obesity as a risk factor for increased severity of disease outcomes in patients infected with severe acute respiratory syndrome coronavirus type 2 (SARS-CoV-2). Obesity is associated with adipose tissue dysfunction, which not only predisposes individuals to metabolic complications, but also substantially contributes to low-grade systemic inflammation, altered immune cell composition, and compromised immune function. This seems to impact the susceptibility and outcome of diseases caused by viruses, as obese people appear more vulnerable to developing infections and they recover later from infectious diseases than normal-weight individuals. Based on these findings, increased efforts to identify suitable diagnostic and prognostic markers in obese Coronavirus disease 2019 (COVID-19) patients to predict disease outcomes have been made. This includes the analysis of cytokines secreted from adipose tissues (adipokines), which have multiple regulatory functions in the body; for instance, modulating insulin sensitivity, blood pressure, lipid metabolism, appetite, and fertility. Most relevant in the context of viral infections, adipokines also influence the immune cell number, with consequences for overall immune cell activity and function. Hence, the analysis of the circulating levels of diverse adipokines in patients infected with SARS-CoV-2 have been considered to reveal diagnostic and prognostic COVID-19 markers. This review article summarizes the findings aimed to correlate the circulating levels of adipokines with progression and disease outcomes of COVID-19. Several studies provided insights on chemerin, adiponectin, leptin, resistin, and galectin-3 levels in SARS-CoV-2-infected patients, while limited information is yet available on the adipokines apelin and visfatin in COVID-19. Altogether, current evidence points at circulating galectin-3 and resistin levels being of diagnostic and prognostic value in COVID-19 disease.

Anthropometric Measurements and Admission Parameters as Predictors of Acute Respiratory Distress Syndrome in Hospitalized COVID-19 Patients

Aim: We aimed to single out admission predictors of acute respiratory distress syndrome (ARDS) in hospitalized COVID-19 patients and investigate the role of bioelectrical impedance (BIA) measurements in ARDS development. Method: An observational, prospective cohort study was conducted on 407 consecutive COVID-19 patients hospitalized at the University Clinical Center Kragujevac between September 2021 and March 2022. Patients were followed during the hospitalization, and ARDS was observed as a primary endpoint. Body composition was assessed using the BMI, body fat percentage (BF%), and visceral fat (VF) via BIA. Within 24 h of admission, patients were sampled for blood gas and laboratory analysis. Results: Patients with BMI above 30 kg/m², very high BF%, and/or very high VF levels were at a significantly higher risk of developing ARDS compared to nonobese patients (OR: 4.568, 8.892, and 2.448, respectively). In addition, after performing multiple regression analysis, six admission predictors of ARDS were singled out: (1) very high BF (aOR 8.059), (2) SaO₂ < 87.5 (aOR 5.120), (3) IL-6 > 59.75 (aOR 4.089), (4) low lymphocyte count (aOR 2.880), (5) female sex (aOR 2.290), and (6) age < 68.5 (aOR 1.976). Conclusion: Obesity is an important risk factor for the clinical deterioration of hospitalized COVID-19 patients. BF%, assessed through BIA measuring, was the strongest independent predictor of ARDS in hospitalized COVID-19 patients.

Prevalence and clinical implications of abnormal body composition phenotypes in patients with COVID-19: a systematic review

BACKGROUND

The impact of body composition (BC) abnormalities on coronavirus disease 2019 (COVID-19) outcomes remains to be determined.

OBJECTIVE

We summarized the evidence on BC abnormalities and their relationship with adverse clinical outcomes in patients with COVID-19.

METHODS

A systematic search was conducted up until September 26, 2022 for observational studies using BC techniques to quantify skeletal muscle mass (or related compartments), muscle radiodensity or echo intensity, adipose tissue (AT, or related compartments), and phase angle (PhA) in adults with COVID-19. Methodological quality of studies was assessed using the Newcastle-Ottawa Scale. A synthesis without meta-analysis was conducted to summarize the prevalence of BC abnormalities and their significant associations with clinical outcomes.

RESULTS

We included 62 studies (69.4% low risk of bias) with 12 to 1,138 participants, except three with up to 490,301 participants. Using computed tomography and different cut-offs, prevalence ranged approximately from 22-90% for low muscle mass, 12-85% for low muscle radiodensity, 16-70% for high visceral AT. Using bioelectrical impedance analysis (BIA), prevalence of high fat mass was 51% and low PhA was 22-88%. Mortality was inversely related to PhA (3/4 studies) and positively related to intramuscular AT (4/5 studies), muscle echo intensity (2/2 studies), and BIA-estimated fat mass (2/2 studies). Intensive care unit admission was positively related to visceral AT (6/7 studies) and total AT (2/3 studies). Disease severity and hospitalization outcomes were positively related to intramuscular AT (2/2 studies). Inconsistent associations were found for the rest of BC measures and hospitalization outcomes.

CONCLUSIONS

Abnormalities in BC were prevalent in patients with COVID-19. Although conflicting associations were observed among certain BC abnormalities and clinical outcomes, higher muscle echo intensity (reflective of myosteatosis) and lower PhA were more consistently associated with greater mortality risk. Likewise, high IMAT and VAT were associated with mortality and ICU admission, respectively.

Artificial intelligence and body composition

AIMS

Although obesity is associated with chronic disease, a large section of the population with high BMI does not have an increased risk of metabolic disease. Increased visceral adiposity and sarcopenia are also risk factors for metabolic disease in people with normal BMI. Artificial Intelligence (AI) techniques can help assess and analyze body composition parameters for predicting cardiometabolic health. The purpose of the study was to systematically explore literature involving AI techniques for body composition assessment and observe general trends.

METHODS

We searched the following databases: Embase, Web of Science, and PubMed. There was a total of 354 search results. After removing duplicates, irrelevant studies, and reviews(a total of 303), 51 studies were included in the systematic review.

RESULTS

AI techniques have been studied for body composition analysis in the context of diabetes mellitus, hypertension, cancer and many specialized diseases. Imaging techniques employed for AI methods include CT (Computerized Tomography), MRI (Magnetic Resonance Imaging), ultrasonography, plethysmography, and EKG(Electrocardiogram). Automatic segmentation of body composition by deep learning with convolutional networks has helped determine and quantify muscle mass. Limitations include heterogeneity of study populations, inherent bias in sampling, and lack of generalizability. Different bias mitigation strategies should be evaluated to address these problems and improve the applicability of AI to body composition analysis.

CONCLUSIONS

AI assisted measurement of body composition might assist in improved cardiovascular risk stratification when applied in the appropriate clinical context.

Visceral to subcutaneous fat ratio predicts short-term mortality in patients with Covid 19. A multicenter study

OBJECTIVE

To evaluate the association of body composition parameters with outcomes in Covid-19.

METHODS

173 patients hospitalized for Covid-19 infection in 6 European centers were included in this retrospective study. Measurements were performed at L3-level and comprised skeletal muscle index (SMI), muscle density (MD), and adipose tissue measurements [visceral adipose tissue (VAT), subcutaneous adipose tissue (SAT), intramuscular adipose tissue (IMAT), visceral-to-subcutaneous-adipose-tissue-area-ratio (VSR)]. The association with mortality, the need for intubation (MV), and the need for admission to ICU within 30 days were evaluated.

RESULTS

Higher SAT density was associated with a greater risk of MV (OR = 1.071, 95%CI=(1.034;1.110), p < 0.001). Higher VAT density was associated with admission to ICU (OR = 1.068, 95%CI=(1.029;1.109), p < 0.001). Higher MD was a protective factor for MV and ICU admission (OR = 0.914, 95%CI=(0.870;0.960), p < 0.001; OR = 0.882, 95%CI=(0.832;0.934), p = 0.028). Higher VSR was associated with mortality (OR = 2.147, 95%CI=(1.022;4.512), p = 0.044). Male sex showed the strongest influence on the risk of ICU admission and MV. SMI was not associated with either parameter.

CONCLUSION

In patients hospitalized for Covid-19 infection, higher VSR seems to be a strong prognostic factor of short-term mortality. Weak associations with clinical course were found for MD and adipose tissue measurements. Male sex was the strongest prognostic factor of adverse clinical course.

ADVANCES IN KNOWLEDGE

VSR is a prognostic biomarker for 30-day mortality in patients hospitalized for Covid-19 disease.

Visceral adipose tissue and risk of COVID-19 susceptibility, hospitalization, and severity: A Mendelian randomization study

Background

Coronavirus Disease 2019 (COVID-19) has rapidly evolved as a global pandemic. Observational studies found that visceral adipose tissue (VAT) increased the likelihood of worse clinical outcomes in COVID-19 patients. Whereas, whether VAT is causally associated with the susceptibility, hospitalization, or severity of COVID-19 remains unconfirmed. We aimed to investigate the causal associations between VAT and susceptibility, hospitalization, and severity of COVID-19.

Methods

We applied a two-sample Mendelian randomization (MR) study to infer causal associations between VAT and COVID-19 outcomes. Single-nucleotide polymorphisms significantly associated with VAT were derived from a large-scale genome-wide association study. The random-effects inverse-variance weighted method was used as the main MR approach, complemented by three other MR methods. Additional sensitivity analyses were also performed.

Results

Genetically predicted higher VAT mass was causally associated with higher risks of COVID-19 susceptibility [odds ratios (ORs) = 1.13; 95% confidence interval (CI), 1.09-1.17; P = 4.37 × 10^-12], hospitalization (OR = 1.51; 95% CI = 1.38-1.65; P = 4.14 × 10^-20), and severity (OR = 1.58; 95% CI = 1.38-1.82; P = 7.34 × 10^-11).

Conclusion

This study provided genetic evidence that higher VAT mass was causally associated with higher risks of susceptibility, hospitalization, and severity of COVID-19. VAT can be a useful tool for risk assessment in the general population and COVID-19 patients, as well as an important prevention target.

The Role of Bioelectrical Impedance Analysis in Predicting COVID-19 Outcome

Background

Published data regarding the impact of obesity on COVID-19 outcomes are inconsistent. However, in most studies, body composition was assessed using body mass index (BMI) alone, thus neglecting the presence and distribution of adipose tissue. Therefore, we aimed to investigate the impact of body and visceral fat on COVID-19 outcomes.

Methods

Observational, prospective cohort study included 216 consecutive COVID-19 patients hospitalized at University Clinical Center Kragujevac (Serbia) from October to December 2021. Body composition was assessed using the BMI, body fat percentage (%BF), and visceral fat (VF) via bioelectrical impedance analysis (BIA). In addition to anthropometric measurements, variables in the research were socio-demographic and medical history data, as well as admission inflammatory biomarkers. Primary end-points were fatal outcomes and intensive care unit (ICU) admission.

Results

The overall prevalence of obesity was 39.3% according to BMI and 50.9% according to % BF, while 38.4% of patients had very high VF levels. After adjusting odds ratio values for cofounding variables and obesity-related conditions, all three anthropometric parameters were significant predictors of primary end-points. However, we note that % BF and VF, compared to BMI, were stronger predictors of both mortality (aOR 3.353, aOR 3.05, and aOR 2.387, respectively) and ICU admission [adjusted odds ratio (aOR) 7.141, aOR 3.424, and aOR 3.133, respectively].

Conclusion

Obesity is linked with COVID-19 mortality and ICU admission, with BIA measurements being stronger predictors of outcome compared to BMI use alone.

Radiology Implementation Considerations for Artificial Intelligence (AI) Applied to COVID-19, From the AJR Special Series on AI Applications

Hundreds of imaging-based artificial intelligence (AI) models have been developed in response to the COVID-19 pandemic. AI systems that incorporate imaging have shown promise in primary detection, severity grading, and prognostication of outcomes in COVID-19, and have enabled integration of imaging with a broad range of additional clinical and epidemiologic data. However, systematic reviews of AI models applied to COVID-19 medical imaging have highlighted problems in the field, including methodologic issues and problems in real-world deployment. Clinical use of such models should be informed by both the promise and potential pitfalls of implementation. How does a practicing radiologist make sense of this complex topic, and what factors should be considered in the implementation of AI tools for imaging of COVID-19? This critical review aims to help the radiologist understand the nuances that impact the clinical deployment of AI for imaging of COVID-19. We review imaging use cases for AI models in COVID-19 (e.g., diagnosis, severity assessment, and prognostication) and explore considerations for AI model development and testing, deployment infrastructure, clinical user interfaces, quality control, and institutional review board and regulatory approvals, with a practical focus on what a radiologist should consider when implementing an AI tool for COVID-19.

Role of visceral fat areas defined by thoracic CT in acute pulmonary embolism

OBJECTIVE

Visceral adipose tissue (VAT) has been established as an important parameter of body composition. It can be assessed by imaging modalities like computed tomography (CT). The purpose of the present study was to analyse the prognostic role of VAT derived from thoracic CT in patients with acute pulmonary embolism (PE).

METHODS

The clinical database of our center was retrospectively screened for patients with acute PE between 2014 and 2017. Overall, 184 patients were included into the analysis. VAT was assessed on axial slices of the thoracic CT at the level of the first lumbar vertebra. Clinical scores, serological parameters, need for intubation, ICU admission and 30 days mortality were assessed.

RESULTS

Using the previously reported threshold of 100 cm² for visceral obesity definition 136 (73.9%), patients were considered as visceral obese. There was a moderate correlation between VAT and BMI (r = 0.56, p < 0.0001). There was also a moderate correlation between VAT and body height (r = 0.41, p =< 0.0001). Of all investigated clinical scores relating to acute PE, only the GENEVA score correlated weakly with VAT (r = 0.15, p = 0.04). There were significant correlations between VAT and creatinine (r = 0.38, p < 0.0001) and Glomerular filtration rate (r = -0.21, p = 0.005). No associations were identified for VAT and mortality or visceral obesity and mortality.

CONCLUSION

VAT was not associated with mortality in patients with acute pulmonary embolism.

ADVANCES IN KNOWLEDGE

Visceral obesity is frequent in patients with acute pulmonary embolism but it is not associated with mortality.

Whole-Body MRI-Derived Adipose Tissue Characterization and Relationship to Pulmonary Function Impairment

Background: Specification of adipose tissues by whole-body magnetic resonance imaging (MRI) was performed and related to pulmonary function parameters in a population-based cohort. Methods: 203 study participants underwent whole-body MRI and pulmonary function tests as part of the KORA (Cooperative Health Research in the Augsburg Region) MRI study. Both visceral adipose tissue (VAT) and subcutaneous adipose tissue (SAT) were derived from the T1-Dixon sequence, and hepatic adipose tissue from the proton density fat fraction (PDFFhepatic). Associations between adipose tissue parameters and spirometric indices such as forced vital capacity (FVC), forced expiratory volume in 1 s (FEV1) and Tiffeneau-index (FEV1/FVC) were examined using multivariate linear regression analysis excluding cofounding effects of other clinical parameters. Results: VAT (β = −0.13, p = 0.03) and SAT (β = −0.26, p < 0.001), but not PDFFhepatic were inversely associated with FEV1, while VAT (β = −0.27, p < 0.001), SAT (β = −0.41, p < 0.001), and PDFFhepatic (β = −0.17, p = 0.002) were inversely associated with FVC. PDFFhepatic was directly associated with the Tiffeneau index (β = 2.46, p < 0.001). Conclusions: In the adjusted linear regression model, VAT was inversely associated with all measured spirometric parameters, while PDFFhepatic revealed the strongest association with the Tiffeneau index. Non-invasive adipose tissue quantification measurements might serve as novel biomarkers for respiratory impairment.

Association of non-alcoholic fatty liver disease with COVID-19 severity and pulmonary thrombosis: CovidFAT, a prospective, observational cohort study

Background

Nonalcoholic fatty liver disease (NAFLD) is the most common liver disease associated with systemic changes in immune response, which might be associated with coronavirus disease 2019 (COVID-19) severity. The aim of this study was to investigate the impact of NAFLD on COVID-19 severity and outcomes.

Methods

A prospective observational study included consecutively hospitalized adult patients, hospitalized between March and June 2021, with severe COVID-19. Patients were screened for fatty liver by ultrasound and subsequently diagnosed with NAFLD. Patients were daily followed until discharge, and demographic, clinical, and laboratory data were collected and correlated to clinical outcomes.

Results

Of the 216 patients included, 120 (55.5%) had NAFLD. The NAFLD group had higher C-reactive protein (interquartile range [IQR]) (84.7 [38.6–129.8] mg/L vs 66.9 [32.2–97.3] mg/L; P = .0340), interleukin-6 (49.19 [22.66–92.04] ng/L vs 13.22 [5.29–39.75] ng/L; P < .0001), aspartate aminotransferase (58 [40–81] IU/L vs 46 [29–82] IU/L; P = .0123), alanine aminotransferase (51 [32–73] IU/L vs 40 [23–69] IU/L; P = .0345), and lactate dehydrogenase (391 [285–483] IU/L vs 324 [247–411] IU/L; P = .0027). The patients with NAFLD had higher disease severity assessed by 7-category ordinal scale, more frequently required high-flow nasal cannula or noninvasive ventilation (26, 21.66%, vs 10, 10.42%; P = .0289), had longer duration of hospitalization (IQR) (10 [8–15] days vs 9 [6–12] days; P = .0018), and more frequently had pulmonary thromboembolism (26.66% vs 13.54%; P = .0191). On multivariable analyses, NAFLD was negatively associated with time to recovery (hazard ratio, 0.64; 95% CI, 0.48 to 0.86) and was identified as a risk factor for pulmonary thrombosis (odds ratio, 2.15; 95% CI, 1.04 to 4.46).

Conclusions

NAFLD is associated with higher COVID-19 severity, more adverse outcomes, and more frequent pulmonary thrombosis.

Overweight and Obesity Are Associated With Acute Kidney Injury and Acute Respiratory Distress Syndrome, but Not With Increased Mortality in Hospitalized COVID-19 Patients: A Retrospective Cohort Study

Objective

To evaluate the association between overweight and obesity on the clinical course and outcomes in patients hospitalized with COVID-19.

Design

Retrospective, observational cohort study.

Methods

We performed a multicenter, retrospective, observational cohort study of hospitalized COVID-19 patients to evaluate the associations between overweight and obesity on the clinical course and outcomes.

Results

Out of 1634 hospitalized COVID-19 patients, 473 (28.9%) had normal weight, 669 (40.9%) were overweight, and 492 (30.1%) were obese. Patients who were overweight or had obesity were younger, and there were more women in the obese group. Normal-weight patients more often had pre-existing conditions such as malignancy, or were organ recipients. During admission, patients who were overweight or had obesity had an increased probability of acute respiratory distress syndrome [OR 1.70 (1.26-2.30) and 1.40 (1.01-1.96)], respectively and acute kidney failure [OR 2.29 (1.28-3.76) and 1.92 (1.06-3.48)], respectively. Length of hospital stay was similar between groups. The overall in-hospital mortality rate was 27.7%, and multivariate logistic regression analyses showed that overweight and obesity were not associated with increased mortality compared to normal-weight patients.

Conclusion

In this study, overweight and obesity were associated with acute respiratory distress syndrome and acute kidney injury, but not with in-hospital mortality nor length of hospital stay.