Prognostic utility of the chest computed tomography severity score for the requirement of mechanical ventilation and mortality in hospitalized patients with COVID-19.

Purpose: To correlate the chest computed tomography severity score (CT-SS) with the need for mechanical ventilation and mortality in hospitalized patients with COVID-19. Materials and methods: The chest CT images of 224 inpatients with COVID-19, confirmed by reverse transcriptase-polymerase chain reaction (RT-PCR), were retrospectively reviewed from April 1 to 25, 2020, in a tertiary health care center. We calculated the CT-SS (dividing each lung into 20 segments and assigning scores of 0, 1, and 2 due to opacification involving 0%, <50%, and ≥50% of each region for a global range of 0-40 points, including both lungs), and collected clinical data. The receiver operating characteristic curve and Youden Index analysis was performed to calculate the CT-SS threshold and accuracy for classification for risk of mortality or MV requirement. Results: 136 men and 88 women were recruited, with an age range of 23-91 years and a mean of 50.17 years; 79 met the MV criteria, and 53 were nonsurvivors. The optimal threshold was >27.5 points for mortality (area under ROC curve >0.96), with a sensitivity of 93% and specificity of 87%, and >25.5 points for the need for MV (area under ROC curve >0.94), with a sensitivity of 90% and specificity of 89%. The Kaplan-Meier curves show a significant difference in mortality by the CT-SS threshold (Log Rank p < 0.001). Conclusions: In our cohort of hospitalized patients with COVID-19, the CT-SS accurately discriminates the need for MV and mortality risk. In conjunction with clinical status and laboratory data, the CT-SS may be a useful imaging tool that could be included in establishing a prognosis for this population.

Prognostic performance of an index based on lactic dehydrogenase and transaminases for patients with liver steatosis and COVID-19.

BACKGROUND: Metabolic associated fatty liver disease (MAFLD) is associated with complications and mortality in patients with coronavirus disease 2019 (COVID-19). However, there are no prognostic scores aimed to evaluate the risk of severe disease specifically in patients with MAFLD, despite its high prevalence. Lactate dehydrogenase, aspartate aminotransferase and alanine aminotransferase have been used as markers of liver damage. Therefore, we propose an index based on lactate dehydrogenase, aspartate aminotransferase and alanine aminotransferase for the prediction of complications and mortality in patients with MAFLD and COVID-19. AIM: To evaluate the prognostic performance of an index based on lactate dehydrogenase and transaminases (aspartate aminotransferase/alanine aminotransferase) in patients with COVID-19 and MAFLD [liver fibrosis and nutrition (LNF)-COVID-19 index]. METHODS: In this retrospective cohort study, two cohorts from two different tertiary centers were included. The first was the derivation cohort to obtain the score cutoffs, and the second was the validation cohort. We included hospitalized patients with severe COVID-19 and MAFLD. Liver steatosis was evaluated by computed tomography scan. Area under the receiver operating characteristic (ROC) curve analysis and survival analysis were used. RESULTS: In the derivation cohort, 44.6% had MAFLD; ROC curve analysis yielded a LFN-COVID-19 index > 1.67 as the best cutoff, with a sensitivity of 78%, specificity of 63%, negative predictive value of 91% and an area under the ROC curve of 0.77. In the multivariate analysis, the LFN-COVID-19 index > 1.67 was independently associated with the development of acute kidney injury (odds ratio: 1.8, 95% confidence interval: 1.3-2.5, P < 0.001), orotracheal intubation (odds ratio: 1.9, 95% confidence interval: 1.4-2.4, P < 0.001), and death (odds ratio: 2.86, 95% confidence interval: 1.6-4.5, P < 0.001) in both cohorts. CONCLUSION: LFN-COVID-19 index has a good performance to predict prognosis in patients with MAFLD and COVID-19, which could be useful for the MAFLD population.

Serum Vitamin D Levels Are Associated With Increased COVID-19 Severity and Mortality Independent of Whole-Body and Visceral Adiposity.

INTRODUCTION: Coronavirus disease (COVID-19) is a global pandemic. Vitamin D deficiency has been associated with susceptibility to infectious disease. In this study, the association between COVID-19 outcomes and vitamin D levels in patients attending a COVID-19 reference center in Mexico City are examined. METHODS: Consecutive patients with confirmed COVID-19 were evaluated. All patients underwent clinical evaluation and follow-up, laboratory measurements and a thoracic computerized tomography, including the measurement of epicardial fat thickness. Low vitamin D was defined as levels <20 ng/ml (<50nmol/L) and deficient Vitamin D as a level ≤12 ng/ml (<30 nmol/L). RESULTS: Of the 551 patients included, low vitamin D levels were present in 45.6% and deficient levels in 10.9%. Deficient Vitamin D levels were associated with mortality (HR 2.11, 95%CI 1.24-3.58, p = 0.006) but not with critical COVID-19, adjusted for age, sex, body-mass index and epicardial fat. Using model-based causal mediation analyses the increased risk of COVID-19 mortality conferred by low vitamin D levels was partly mediated by its effect on D-dimer and cardiac ultrasensitive troponins. Notably, increased risk of COVID-19 mortality conferred by low vitamin D levels was independent of BMI and epicardial fat. CONCLUSION: Vitamin D deficiency (≤12 ng/ml or <30 nmol/L), is independently associated with COVID-19 mortality after adjustment for visceral fat (epicardial fat thickness). Low vitamin D may contribute to a pro-inflammatory and pro-thrombotic state, increasing the risk for adverse COVID-19 outcomes.

NAFLD determined by Dallas Steatosis Index is associated with poor outcomes in COVID-19 pneumonia: a cohort study.

Coronavirus disease 2019 is a worldwide health challenge. Liver steatosis diagnosis based on imaging studies has been implicated in poor outcomes of COVID-19 pneumonia, but results are inconsistent. The Dallas Steatosis Index (DSI) is an available calculator developed to identify patients with non-alcoholic fatty liver disease (NAFLD). We hypothesized that it would be associated with in-hospital mortality, intensive care unit admission (ICU), and invasive mechanical ventilation (IMV). We conducted a retrospective cohort study on inpatients with confirmed COVID-19 pneumonia between February 26 and April 11, 2020. We computed the DSI on admission, and patients with high DSI were considered with NAFLD. We employed logistic regression to study the association between NAFLD, mortality, ICU admission, and IMV. We studied the association between liver steatosis on computed tomography (CT) and these outcomes, and also between Metabolic Associated Fatty Liver Disease (MAFLD) based on CT findings and risk factors and the outcomes. 470 patients were included; 359 had NAFLD according to the DSI. They had a higher frequency of type 2 diabetes (31% vs 14%, p < 0.001), obesity (58% vs 14%, p < 0.001), and arterial hypertension (34% vs 22%, p = 0.02). In univariable analysis, NAFLD was associated with mortality, ICU admission, and IMV. Liver steatosis by CT and MAFLD were not associated with any of these outcomes. In multivariable logistic regression, high DSI remained significantly associated with IMV and death. High DSI, which can be easily computed on admission, was associated with IMV and death, and its use to better stratify the prognosis of these patients should be explored. On the other hand, liver steatosis by CT and MAFLD were not associated with poor outcomes.

Epicardial adipose tissue thickness is associated with increased COVID-19 severity and mortality.

BACKGROUND: Increased adiposity and visceral obesity have been linked to adverse COVID-19 outcomes. The amount of epicardial adipose tissue (EAT) may have relevant implications given its proximity to the heart and lungs. Here, we explored the role of EAT in increasing the risk for COVID-19 adverse outcomes. METHODS: We included 748 patients with COVID-19 attending a reference center in Mexico City. EAT thickness, sub-thoracic and extra-pericardial fat were measured using thoracic CT scans. We explored the association of each thoracic adipose tissue compartment with COVID-19 mortality and severe COVID-19 (defined as mortality and need for invasive mechanical ventilation), according to the presence or absence of obesity. Mediation analyses evaluated the role of EAT in facilitating the effect of age, body mass index and cardiac troponin levels with COVID-19 outcomes. RESULTS: EAT thickness was associated with increased risk of COVID-19 mortality (HR 1.18, 95% CI 1.01-1.39) independent of age, gender, comorbid conditions and BMI. Increased EAT was associated with lower SpO2 and PaFi index and higher levels of cardiac troponins, D-dimer, fibrinogen, C-reactive protein, and 4 C severity score, independent of obesity. EAT mediated 13.1% (95% CI 3.67-28.0%) and 5.1% (95% CI 0.19-14.0%) of the effect of age and 19.4% (95% CI 4.67-63.0%) and 12.8% (95% CI 0.03-46.0%) of the effect of BMI on requirement for intubation and mortality, respectively. EAT also mediated the effect of increased cardiac troponins on myocardial infarction during COVID-19. CONCLUSION: EAT is an independent risk factor for severe COVID-19 and mortality independent of obesity. EAT partly mediates the effect of age and BMI and increased cardiac troponins on adverse COVID-19 outcomes.

Validation of Chest Computed Tomography Artificial Intelligence to Determine the Requirement for Mechanical Ventilation and Risk of Mortality in Hospitalized Coronavirus Disease-19 Patients in a Tertiary Care Center In Mexico City.

BACKGROUND: Artificial intelligence (AI) in radiology has improved diagnostic performance and shortened reading times of coronavirus disease 2019 (COVID-19) patients' studies. OBJECTIVES: The objectives pf the study were to analyze the performance of a chest computed tomography (CT) AI quantitative algorithm for determining the risk of mortality/mechanical ventilation (MV) in hospitalized COVID-19 patients and explore a prognostic multivariate model in a tertiary-care center in Mexico City. METHODS: Chest CT images of 166 COVID-19 patients hospitalized from April 1 to 20, 2020, were retrospectively analyzed using AI algorithm software. Data were collected from their medical records. We analyzed the diagnostic yield of the relevant CT variables using the area under the ROC curve (area under the curve [AUC]). Optimal thresholds were obtained using the Youden index. We proposed a predictive logistic model for each outcome based on CT AI measures and predetermined laboratory and clinical characteristics. RESULTS: The highest diagnostic yield of the assessed CT variables for mortality was the percentage of total opacity (threshold >51%; AUC = 0.88, sensitivity = 74%, and specificity = 91%). The AUC of the CT severity score (threshold > 12.5) was 0.88 for MV (sensitivity = 65% and specificity = 92%). The proposed prognostic models include the percentage of opacity and lactate dehydrogenase level for mortality and troponin I and CT severity score for MV requirement. CONCLUSION: The AI-calculated CT severity score and total opacity percentage showed good diagnostic accuracy for mortality and met MV criteria. The proposed prognostic models using biochemical variables and imaging data measured by AI on chest CT showed good risk classification in our population of hospitalized COVID-19 patients.

Liver fibrosis in patients with metabolic associated fatty liver disease is a risk factor for adverse outcomes in COVID-19.

BACKGROUND: Metabolic diseases are risk factors for severe Coronavirus disease (COVID-19), which have a close relationship with metabolic dysfunction-associated fatty liver disease (MAFLD). AIMS: To evaluate the presence of MAFLD and fibrosis in patients with COVID-19 and its association with prognosis. METHODS: Retrospective cohort study. In hospitalized patients with COVID-19, the presence of liver steatosis was determined by computed tomography scan (CT). Liver fibrosis was assessed using the NAFLD fibrosis score (NFS score), and when altered, the AST to platelet ratio index (APRI) score. Mann-Whitney U, Student´s t-test, logistic regression analysis, Kaplan-Meier curves and Cox regression analysis were used. RESULTS: 432 patients were analyzed, finding steatosis in 40.6%. No differences in pulmonary involvement on CT scan, treatment, or number of days between the onset of symptoms and hospital admission were found between patients with and without MAFLD. The presence of liver fibrosis was associated with higher severity scores, higher levels of inflammatory markers, requirement of mechanical ventilation, incidence of acute kidney injury (AKI), and higher mortality than patients without fibrosis. CONCLUSION: The presence of fibrosis rather than the presence of MAFLD is associated with increased risk for mechanical ventilation, development of AKI, and higher mortality in COVID-19 patients.

Cardiac Computed Tomography as an Alternative Technique in the Assessment of Acute Myocardial Ischemia in the Context of COVID-19 Infection.

Coronavirus disease 2019 (COVID-19) has been shown to result in coagulation abnormalities and predisposes patients to thrombotic status, both in the venous and arterial circulations. Herein, we report the case of a 60-year-old patient with COVID-19 pneumonia confirmed by polymerase chain reaction (PCR) who experienced signs and symptoms of myocardial ischemia. A cardiac computed tomography (CT) demonstrated an extensive coronary artery multivessel disease and ischemic dilated cardiomyopathy in a non-invasively approach allowing to define the coronary obstructive involvement in the acute stage of the disease.