The impact of chest CT body composition parameters on clinical outcomes in COVID-19 patients

Validating a Practical Correction for Intravenous Contrast on Computed Tomography-Based Muscle Density

OBJECTIVE

Computed tomography (CT) measured muscle density is prognostic of health outcomes. However, the use of intravenous contrast obscures prognoses by artificially increasing CT muscle density. We previously established a correction to equalize contrast and noncontrast muscle density measurements. While this correction was validated internally, the objective of this study was to obtain external validation using different patient cohorts, muscle regions, and CT series.

METHODS

CT images from 109 patients with kidney tumors who received abdominal CT scans with a multiphase intravenous contrast protocol were analyzed. Paraspinal muscle density measurements taken during noncontrast, venous phase, and delayed phase contrast scans were collected. An a priori correction of -7.5 Hounsfield units (HU) was applied to muscle measurements. Equivalence testing was utilized to determine statistical similarity.

RESULTS

In the sample of 109 patients (mean age: 63 years [SD: 14.3]; 41.3% female), densities in smaller regions of interest within the paraspinal muscles and the entire paraspinal muscle density (PS) in venous and delayed phase contrast scans were higher than in noncontrast. Equivalence testing showed that average corrected contrast and noncontrast muscle densities were within 3 HU for both muscle measures for the total patient sample, and for a majority of male and female subsamples. The correction is suitable for regions of interests of venous contrast (90% CI: -1.90, -0.69 HU) and delayed contrast scans (90% CI: 0.075, 1.29 HU) and within the PS measures of venous contrast (90% CI: -2.04, -0.94 HU) and delayed contrast scans (90% CI: -0.11, 0.89 HU).

CONCLUSIONS

The previously established correction for contrast of -7.5 HU was applied in a new patient population, axial muscle region, muscle measurement size, and expanded on previously studied contrast phases. The correction produced contrast-corrected muscle densities that were statistically equivalent to noncontrast muscle densities. The simplicity of the correction gives clinicians a tool that seamlessly integrates into practice or research to improve harmonization of data between contrast and noncontrast scans.

CT scan-derived pectoralis muscle parameters are closely associated with COVID-19 outcomes: A systematic review and meta-analysis

BACKGROUND

The relationships between pectoralis muscle parameters and outcomes in patients with coronavirus disease 2019 (COVID-19) remain uncertain.

METHODS

We systematically searched PubMed, Embase, Web of Science and the Cochrane Library from 1 January 2019 to 1 May 2024 to identify non-overlapping studies evaluating pectoralis muscle-associated index on chest CT scan with clinical outcome in COVID-19 patients. Random-effects and fixed-effects meta-analyses were performed, and heterogeneity between studies was quantified using the I2 statistic. The risk of study bias was assessed using the Newcastle-Ottawa scale. Funnel plots for detecting small-study effects.

RESULTS

A total of 9 studies with 4109 COVID-19 patients were included. The meta-analysis findings revealed a correlation between pectoralis muscle parameters and COVID-19 prognosis. Specifically, patients with higher pectoralis muscle density (PMD) exhibited a lower mortality risk, with an odds ratio (OR) of 0.95 (95% CI: 0.92-0.99). The rate of intubation was lower in COVID-19 patients with a high pectoralis muscle index (PMI) (OR =  0.96, 95% CI: 0.92-1.00).

CONCLUSION

In summary, a low PMD is associated with a marginally elevated risk of mortality, whereas a decreased PMI represents a risk factor for intubation in COVID-19 patients. These findings suggest that pectoralis muscle parameters on chest CT may be a useful prognostic tool for COVID-19 patients.

Subcutaneous adipose tissue measured by computed tomography could be an independent predictor for early outcomes of patients with severe COVID-19

Background

Patients with severe Coronavirus Disease 2019 (COVID-19) can experience protein loss due to the inflammatory response and energy consumption, impairing immune function. The presence of excessive visceral and heart fat leads to chronic long-term inflammation that can adversely affect immune function and, thus, outcomes for these patients. We aimed to explore the roles of prognostic nutrition index (PNI) and quantitative fat assessment based on computed tomography (CT) scans in predicting the outcomes of patients with severe COVID-19.

Methods

A total of 130 patients with severe COVID-19 who were treated between December 1, 2022, and February 28, 2023, were retrospectively enrolled. The patients were divided into survival and death groups. Data on chest CT examinations following admission were collected to measure cardiac adipose tissue (CAT), visceral adipose tissue (VAT), and subcutaneous adipose tissue (SAT) and to analyze the CT score of pulmonary lesions. Clinical information and laboratory examination data were collected. Univariate and multivariate logistic regression analyses were used to explore the risk factors associated with death, and several multivariate logistic regression models were established.

Results

Of the 130 patients included in the study (median age, 80.5 years; males, 32%), 68 patients died and 62 patients survived. PNI showed a strong association with the outcome of severe COVID-19 (p < 0.001). Among each part of the fat volume obtained based on a CT scan, SAT showed a significant association with the mortality of severe COVID-19 patients (p = 0.007). However, VAT and CAT were not significantly correlated with the death of patients. In the multivariate models, SAT had a higher predictive value than PNI; the area under the curve (AUC) of SAT was 0.844, which was higher than that of PNI (AUC = 0.833), but in the model of the combination of the two indexes, the prediction did not improve (AUC = 0.830), and SAT lost its significance (p = 0.069).

Conclusion

Subcutaneous adipose tissue measured by computed tomography and PNI were found to be independent predictors of death in patients with severe COVID-19.

Effect of sarcopenia on mortality in acute stroke patients receiving endovascular treatment

BACKGROUND

To investigate the effect of sarcopenia on mortality in patients with acute ischemic stroke caused by anterior circulation large artery occlusion who underwent endovascular treatment.

METHODS

Acute ischemic stroke patients (n = 194) treated with mechanical thrombectomy who underwent chest computed tomography between 2019 and 2022 (median age, 69 [interquartile range: 61-77], 95 females, 99 males) were evaluated retrospectively. The cross-sectional area and density of the pectoralis muscle [pectoralis muscle area (PMA) and pectoralis muscle density (PMD)] at the level of the aortic arch and the erector spinae muscle at the T12 level [erector spinae muscle area (ESMA) and erector spinae muscle density (ESMD)] were measured. The association between skeletal muscle parameters and mortality outcomes was investigated using the receiver operating characteristic (ROC) curve and multivariable logistic regression analyses.

RESULTS

The 90-day mortality rate was 32% in the study population (n = 62). The ROC analysis revealed that ESMD [area under the curve (AUC): 0.765] and PMD (AUC: 0.759) performed best in the prediction of 90-day mortality. In the multivariable logistic regression analysis, PMD [odds ratio (OR): 0.896; 95% confidence interval (CI): 0.846-0.948; p < 0.001], ESMA (OR: 0.929; 95% CI: 0.878-0.983; p = 0.011), and ESMD (OR: 0.947; 95% CI: 0.913-0.983; p = 0.004), but not PMA, were independent risk factors for 90-day mortality.

CONCLUSION

PMD, ESMA, and ESMD may be risk factors for 90-day mortality after mechanical thrombectomy for acute ischemic stroke.

Unveiling the detrimental vicious cycle linking skeletal muscle and COVID-19: A systematic review and meta-analysis

OBJECTIVE

Skeletal muscle catabolism supports multiple organs and systems during severe trauma and infection, but its role in COVID-19 remains unclear. This study investigates the interactions between skeletal muscle and COVID-19.

METHODS

The PubMed, EMbase, and The Cochrane Library databases were systematically searched from January 2020 to August 2023 for cohort studies focusing on the impact of skeletal muscle on COVID-19 prevalence and outcomes, and longitudinal studies examining skeletal muscle changes caused by COVID-19. Skeletal muscle quantity (SMQN) and quality (SMQL) were assessed separately. The random-effect model was predominantly utilized for statistical analysis.

RESULTS

Seventy studies with moderate to high quality were included. Low SMQN/SMQL was associated with an increased risk of COVID-19 infection (OR = 1.62, p < 0.001). Both the low SMQN and SMQL predicted COVID-19-related mortality (OR = 1.53, p = 0.016; OR = 2.18, p = 0.001, respectively). Mortality risk decreased with increasing SMQN (OR = 0.979, p = 0.009) and SMQL (OR = 0.972, p = 0.034). Low SMQN and SMQL were also linked to the need for intensive care unit/mechanical ventilation, increased COVID-19 severity, and longer hospital stays. Significant skeletal muscle wasting, characterized by reduced volume and strength, was observed during COVID-19 infection and the pandemic.

CONCLUSIONS

This study reveals a detrimental vicious circle between skeletal muscle and COVID-19. Effective management of skeletal muscle could be beneficial for treating COVID-19 infections and addressing the broader pandemic. These findings have important implications for the management of future virus pandemics.

SYSTEMATIC REVIEW REGISTRATION

PROSPERO CRD42023395476.

Inflammation, but not skeletal muscle index, is associated with coronavirus disease 2019 mortality in patients with cancer

BACKGROUND & AIMS

Patients with cancer and coronavirus disease 2019 (COVID-19) have characteristics that can cause the most severe forms of the disease and higher mortality. We aimed to assess the association between computed tomography (CT)-derived muscle abnormalities, anthropometric parameters, inflammation, and mortality in patients with cancer and COVID-19.

METHODS

This retrospective study included patients with cancer and COVID-19 admitted between March 1st and December 31st, 2020. All information was collected from medical records (clinical and nutritional parameters, serum albumin, and C-reactive protein [CRP]). Weight loss and body mass index (BMI) were assessed using Global Leadership Initiative on Malnutrition phenotypic criteria. Skeletal muscle index (SMI) and skeletal muscle radiodensity (SMD) at the fourth thoracic vertebra level were assessed using computed tomography scans.

RESULTS

This study included 80 patients (61% men, mean age: 58 ± 17 years). Of the patients analyzed, 49% had weight loss >5%, and 14% had low BMI. The median length of hospital stay was 7 (interquartile range: 4-14 days), 27% needed mechanical ventilation, 34% died as a direct consequence of COVID-19 infection and 15% to complications associated with cancer condition. In multivariate logistic regression analysis, low SMI was associated with increased in-hospital mortality [odds ratio (OR): 4.81; 95% confidence interval (95% CI): 1.63; 14.2; p = 0.005), while CRP was associated with COVID-19-related mortality (OR: 1.08; 95% CI: 1.01; 1.15, p = 0.018).

CONCLUSION

SMI independently predicts in-hospital mortality in patients with cancer and COVID-19. Additionally, an independent association was observed between CRP and mortality specifically related to COVID-19.

The Link between Inflammation, Lipid Derivatives, and Microbiota Metabolites in COVID-19 Patients: Implications on Eating Behaviors and Nutritional Status

Extreme inflammation that continues even after infections can lead to a cytokine storm. In recent times, one of the most common causes of cytokine storm activation has been SARS-CoV-2 infection. A cytokine storm leads to dysregulation and excessive stimulation of the immune system, producing symptoms typical of post-COVID syndrome, including chronic fatigue, shortness of breath, joint pain, trouble concentrating (known as "brain fog"), and even direct organ damage in the heart, lungs, kidneys, and brain. This work summarizes the current knowledge regarding inflammation and the cytokine storm related to SARS-CoV-2 infection. Additionally, changes in lipid metabolism and microbiota composition under the influence of inflammation in COVID-19, along with the possible underlying mechanisms, are described. Finally, this text explores potential health implications related to changes in eating behaviors and nutritional status in COVID-19 patients. Although research on the cytokine storm is still ongoing, there is convincing evidence suggesting that severe immune and inflammatory responses during the acute phase of COVID-19 may lead to long-term health consequences. Understanding these links is key to developing treatment strategies and supporting patients after infection.

Abdominal adipose tissue distribution assessed by computed tomography and mortality in hospitalised patients with COVID-19: a retrospective longitudinal cohort study

BACKGROUND

Visceral adiposity has been associated with an increased risk of critical illness in COVID-19 patients. However, if it also associates to a poor survival is still not well established. The aim of the study was to assess the relationship between abdominal fat distribution and COVID-19 mortality.

METHODS

In this six-month longitudinal cohort study, abdominal visceral (VAT) and subcutaneous adipose tissues (SAT) were measured by computed tomography in a cohort of 174 patients admitted to the emergency department with a diagnosis of COVID-19, during the first wave of pandemic. The primary exposure and outcome measures were VAT and SAT at hospital admission, and death at 30 and 180 days, respectively.

RESULTS

Overall survival was not different according to VAT (p = 0.94), SAT (p = 0.32) and VAT/SAT ratio (p = 0.64). However, patients in the lowest SAT quartile (thickness ≤ 11.25 mm) had a significantly reduced survival compared to those with thicker SAT (77 vs. 94% at day 30; 74 vs. 91% at day 180, p = 0.01). Similarly, a thinner SAT was associated with lower survival in Intensive Care Unit (ICU) admitted patients, independently of sex or age (p = 0.02). The VAT/SAT ratio showed a non-linear increased risk of ICU admission, which plateaued out and tended for inversion at values greater than 1.9 (p = 0.001), although was not associated with increased mortality rate.

CONCLUSIONS

In our cohort, visceral adiposity did not increase mortality in patients with COVID-19, but low SAT may be associated with poor survival.

The identification of an optimal body size parameter to adjust skeletal muscle area on chest CT in COVID-19 patients

Objectives

The most efficient way to adjust skeletal muscle area (SMA) derived from chest CT to body size remains unclear. We hypothesized that vertebral body area (VBA) measurement would allow such efficient adjustment.

Methods

We conducted a retrospective observational study of chest CT imaging in a cohort of critically ill COVID-19 patients. We measured paravertebral SMA at T5 level and T5 vertebral body anteroposterior length, width, and area. We used linear regression and multivariable modelling to assess the association of VBA with SMA.

Results

In 48 COVID-19 patients in ICU, T5 VBA could be easily derived from simple width and anteroposterior length linear measurements. T5 VBA (measured manually or estimated from width and length) performed similarly to height (R2 of 0.22) as an adjustment variable for SMA, with R2 of 0.23 and 0.22, respectively. Gender had the strongest correlation with SMA (R2 = 0.28). Adding height or age to a model using gender and VBA did not improve correlation.

Conclusions

Gender and estimated VBA from simple linear measurements at T5 level on CT images can be utilized for adjustment of SMA without the need for height. Validation of these findings in larger cohorts of critically ill patients is now needed.

CCL18, CHI3L1, ANG2, IL-6 systemic levels are associated with the extent of lung damage and radiomic features in SARS-CoV-2 infection

OBJECTIVE AND DESIGN

We aimed to identify cytokines whose concentrations are related to lung damage, radiomic features, and clinical outcomes in COVID-19 patients.

MATERIAL OR SUBJECTS

Two hundred twenty-six patients with SARS-CoV-2 infection and chest computed tomography (CT) images were enrolled.

METHODS

CCL18, CHI3L1/YKL-40, GAL3, ANG2, IP-10, IL-10, TNFα, IL-6, soluble gp130, soluble IL-6R were quantified in plasma samples using Luminex assays. The Mann-Whitney U test, the Kruskal-Wallis test, correlation and regression analyses were performed. Mediation analyses were used to investigate the possible causal relationships between cytokines, lung damage, and outcomes. AVIEW lung cancer screening software, pyradiomics, and XGBoost classifier were used for radiomic feature analyses.

RESULTS

CCL18, CHI3L1, and ANG2 systemic levels mainly reflected the extent of lung injury. Increased levels of every cytokine, but particularly of IL-6, were associated with the three outcomes: hospitalization, mechanical ventilation, and death. Soluble IL-6R showed a slight protective effect on death. The effect of age on COVID-19 outcomes was partially mediated by cytokine levels, while CT scores considerably mediated the effect of cytokine levels on outcomes. Radiomic-feature-based models confirmed the association between lung imaging characteristics and CCL18 and CHI3L1.

CONCLUSION

Data suggest a causal link between cytokines (risk factor), lung damage (mediator), and COVID-19 outcomes.

Correcting Posterior Paraspinal Muscle Computed Tomography Density for Intravenous Contrast Material Independent of Sex and Vascular Phase

PURPOSE

Intravenous contrast poses challenges to computed tomography (CT) muscle density analysis. We developed and tested corrections for contrast-enhanced CT muscle density to improve muscle analysis and the utility of CT scans for the assessment of myosteatosis.

MATERIALS AND METHODS

Using retrospective images from 240 adults who received routine abdominal CT imaging from March to November 2020 with weight-based iodine contrast, we obtained paraspinal muscle density measurements from noncontrast (NC), arterial, and venous-phase images. We used a calibration sample to develop 9 different mean and regression-based corrections for the effect of contrast. We applied the corrections in a validation sample and conducted equivalence testing.

RESULTS

We evaluated 140 patients (mean age 52.0 y [SD: 18.3]; 60% female) in the calibration sample and 100 patients (mean age 54.8 y [SD: 18.9]; 60% female) in the validation sample. Contrast-enhanced muscle density was higher than NC by 8.6 HU (SD: 6.2) for the arterial phase (female, 10.4 HU [SD: 5.7]; male, 6.0 HU [SD:6.0]) and by 6.4 HU [SD:8.1] for the venous phase (female, 8.0 HU [SD: 8.6]; male, 4.0 HU [SD: 6.6]). Corrected contrast-enhanced and NC muscle density was equivalent within 3 HU for all correctionns. The -7.5 HU correction, independent of sex and phase, performed well for arterial (95% CI: -0.18, 1.80 HU) and venous-phase data (95% CI: -0.88, 1.41 HU).

CONCLUSIONS

Our validated correction factor of -7.5 HU renders contrast-enhanced muscle density statistically similar to NC density and is a feasible rule-of-thumb for clinicians to implement.

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.

Altered Anti-Viral Immune Responses in Monocytes in Overweight Heavy Drinkers

Alcohol abuse causes increased susceptibility to respiratory syndromes like bacterial pneumonia and viral infections like SARS-CoV-2. Heavy drinkers (HD) are at higher risk of severe COVID-19 if they are also overweight, yet the molecular mechanisms are unexplored. Single-cell RNA-seq (scRNA-seq) was performed on peripheral blood mononuclear cells from lean or overweight HD and healthy controls (HC) after challenge with a dsRNA homopolymer (PolyI:C) to mimic a viral infection and/or with lipopolysaccharide (LPS). All monocyte populations responded to both PolyI:C and LPS with pro-inflammatory gene expression. However, expression of interferon stimulated genes, essential for inhibiting viral pathogenesis, was greatly reduced in overweight patients. Interestingly, the number of upregulated genes in response to PolyI:C challenge was far greater in monocytes from HD compared to HC, including much stronger pro-inflammatory cytokine and interferon-γ signaling responses. These results suggest increased body weight reduced anti-viral responses while heavy drinking increased pro-inflammatory cytokines.

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.

[Routine computed tomography body composition analysis-experience in intensive care patients]

The assessment of the nutritional status of patients in the intensive care unit is recommended in current guidelines and should include the assessment of muscle status. A suitable method is the analysis of routine computed tomography (CT) scans, which are frequently performed in critically ill patients. With the help of special software, individual CT slices are processed and various parameters such as muscle area, muscle density or even the percentage of adipose tissue are displayed and quantified. It has been shown that cross-sectional acquisition of skeletal muscle in the lumbar spine correlates very well with total body muscle. There are defined, albeit population-based, cut-off values that can be used to establish diagnosis of sarcopenia. Monitoring of individualized nutritional therapy can be accomplished by assessment of repetitive CT examinations. The steadily growing body of data confirms that the method can make a valuable contribution to the assessment of body composition in intensive care medicine. Most of the currently available software requires time-consuming processing of the CT. Automated programs, which are now occasionally available and eliminate the need for most manual processing, may make the method even more attractive in the future. Ultimately, the risk of intensive transport to the CT or radiation exposure may be only justified for medical indications. Nevertheless, whenever CT is available for medical reasons, it should also be exploited for composition analysis.

Which Body Composition Parameters on Computed Tomography Are More Successful in Predicting the Prognosis of COVID-19 Patients?

OBJECTIVES

The aims of the study are to compare the body composition parameters (BCPs), which have been reported to have a prognostic impact, in COVID-19 patients, and to determine the most influential BCP(s) on the prognosis.

METHODS

Unenhanced chest computed tomography examinations of COVID-19 cases were assessed regarding the severity of pneumonia, pectoralis muscle area and density (PMA, PMD), visceral adipose tissue area (VAA), waist circumference, waist to paravertebral muscle circumference ratio, coronary artery calcification severity, and paravertebral muscle area at the T5 vertebral level. A second observer repeated measurements and an intraclass correlation coefficient score were used for interobserver agreement. The relationship between data and patient outcomes (intubation, death) was investigated using multivariable logistic regression analysis. The area under the receiver operating characteristic curve (AUC) was used to evaluate the performance of BCPs in predicting outcomes.

RESULTS

A total of 238 (121 males, median age, 48 years [interquartile range, 36-63 years]) consecutive COVID-19 patients with chest computed tomography were investigated. Twenty-four patients (10.08%) were intubated, and 15 patients (6.3%) died during at least 1 month of follow-up. Waist to paravertebral muscle circumference ratio, PMA, PMD, and T5 vertebral level were significantly associated with intubation in the multivariable analysis. Pectoralis muscle density and PMA were significantly associated with death. Pectoralis muscle density showed the highest AUC for the prediction of intubation and death (AUC of 0.814 and 0.871, respectively). There was a good to excellent agreement between observers (intraclass correlation coefficient range, 0.899-0.998).

CONCLUSIONS

Pectoralis muscle density is the most influential BCP in predicting intubation and death in COVID-19 patients.

Low muscle mass in COVID-19 critically-ill patients: Prognostic significance and surrogate markers for assessment

INTRODUCTION

Low muscle mass is a common condition in the critically ill population and is associated with adverse clinical outcomes. The primary aim of this study was to analyze the prognostic significance of low muscle mass using computed tomography (CT) scans in COVID-19 critically ill patients. A second objective was to determine the accuracy and agreement in low muscle mass identification using diverse markers compared to CT as the gold standard.

METHODS

This was a prospective cohort study of COVID-19 critically ill patients. Skeletal muscle area at the third lumbar vertebra was measured. Clinical outcomes (intensive care unit [ICU] and hospital length of stay [LOS], tracheostomy, days on mechanical ventilation [MV], and in-hospital mortality) were assessed. Phase angle, estimated fat-free mass index, calf circumference, and mid-upper arm circumference were measured as surrogate markers of muscle mass.

RESULTS

Eighty-six patients were included (mean age ± SD: 48.6 ± 12.9; 74% males). Patients with low muscle mass (48%) had a higher rate of tracheostomy (50 vs 20%, p = 0.01), prolonged ICU (adjusted HR 0.53, 95%CI 0.30-0.92, p = 0.024) and hospital LOS (adjusted HR 0.50, 95% CI 0.29-0.86, p = 0.014). Bedside markers of muscle mass showed poor to fair agreement and accuracy compared to CT-assessed low muscle mass.

CONCLUSION

Low muscle mass at admission was associated with prolonged length of ICU and hospital stays. Further studies are needed to establish targeted nutritional interventions to halt and correct the catabolic impact of COVID-19 in critically ill patients, based on standardized and reliable measurements of body composition.

Internal calibration for opportunistic computed tomography muscle density analysis

INTRODUCTION

Muscle weakness can lead to reduced physical function and quality of life. Computed tomography (CT) can be used to assess muscle health through measures of muscle cross-sectional area and density loss associated with fat infiltration. However, there are limited opportunities to measure muscle density in clinically acquired CT scans because a density calibration phantom, allowing for the conversion of CT Hounsfield units into density, is typically not included within the field-of-view. For bone density analysis, internal density calibration methods use regions of interest within the scan field-of-view to derive the relationship between Hounsfield units and bone density, but these methods have yet to be adapted for muscle density analysis. The objective of this study was to design and validate a CT internal calibration method for muscle density analysis.

METHODOLOGY

We CT scanned 10 bovine muscle samples using two scan protocols and five scan positions within the scanner bore. The scans were calibrated using internal calibration and a reference phantom. We tested combinations of internal calibration regions of interest (e.g., air, blood, bone, muscle, adipose).

RESULTS

We found that the internal calibration method using two regions of interest, air and adipose or blood, yielded accurate muscle density values (< 1% error) when compared with the reference phantom. The muscle density values derived from the internal and reference phantom calibration methods were highly correlated (R2 > 0.99). The coefficient of variation for muscle density across two scan protocols and five scan positions was significantly lower for internal calibration (mean = 0.33%) than for Hounsfield units (mean = 6.52%). There was no difference between coefficient of variation for the internal calibration and reference phantom methods.

CONCLUSIONS

We have developed an internal calibration method to produce accurate and reliable muscle density measures from opportunistic computed tomography images without the need for calibration phantoms.

COVID-19, obesity, and immune response 2 years after the pandemic: A timeline of scientific advances

In the 2 years since the COVID-19 pandemic was officially declared, science has made considerable strides in understanding the disease's pathophysiology, pharmacological treatments, immune response, and vaccination, but there is still much room for further advances, especially in comprehending its relationship with obesity. Science has not yet described the mechanisms that explain how obesity is directly associated with a poor prognosis. This paper gathers all published studies over the past 2 years that have described immune response, obesity, and COVID-19, a historical and chronological record for researchers and the general public alike. In summary, these studies describe how the cytokine/adipokine levels and inflammatory markers, such as the C-reactive protein, are associated with a higher body mass index in COVID-19-positive patients, suggesting that the inflammatory background and immune dysregulation in individuals with obesity may be expressed in the results and that adiposity may influence the immune response. The timeline presented here is a compilation of the results of 2 years of scientific inquiry, describing how the science has progressed, the principal findings, and the challenges ahead regarding SARS-CoV-2, COVID-19, and emerging variants, especially in patients with obesity.

Modifications of Chest CT Body Composition Parameters at Three and Six Months after Severe COVID-19 Pneumonia: A Retrospective Cohort Study

We aimed to describe body composition changes up to 6-7 months after severe COVID-19 and to evaluate their association with COVID-19 inflammatory burden, described by the integral of the C-reactive protein (CRP) curve. The pectoral muscle area (PMA) and density (PMD), liver-to-spleen (L/S) ratio, and total, visceral, and intermuscular adipose tissue areas (TAT, VAT, and IMAT) were measured at baseline (T0), 2-3 months (T1), and 6-7 months (T2) follow-up CT scans of severe COVID-19 pneumonia survivors. Among the 208 included patients (mean age 65.6 ± 11 years, 31.3% females), decreases in PMA [mean (95%CI) -1.11 (-1.72; -0.51) cm2] and in body fat areas were observed [-3.13 (-10.79; +4.52) cm2 for TAT], larger from T0 to T1 than from T1 to T2. PMD increased only from T1 to T2 [+3.07 (+2.08; +4.06) HU]. Mean decreases were more evident for VAT [-3.55 (-4.94; -2.17) cm2] and steatosis [L/S ratio increase +0.17 (+0.13; +0.20)] than for TAT. In multivariable models adjusted by age, sex, and baseline TAT, increasing the CRP interval was associated with greater PMA reductions, smaller PMD increases, and greater VAT and steatosis decreases, but it was not associated with TAT decreases. In conclusion, muscle loss and fat loss (more apparent in visceral compartments) continue until 6-7 months after COVID-19. The inflammatory burden is associated with skeletal muscle loss and visceral/liver fat loss.

The Role of Obesity, Body Composition, and Nutrition in COVID-19 Pandemia: A Narrative Review

The coronavirus disease 2019 (COVID-19) pandemic has spread worldwide, infecting nearly 500 million people, with more than 6 million deaths recorded globally. Obesity leads people to be more vulnerable, developing worse outcomes that can require hospitalization in intensive care units (ICU). This review focused on the available findings that investigated the link between COVID-19, body composition, and nutritional status. Most studies showed that not only body fat quantity but also its distribution seems to play a crucial role in COVID-19 severity. Compared to the body mass index (BMI), visceral adipose tissue and intrathoracic fat are better predictors of COVID-19 severity and indicate the need for hospitalization in ICU and invasive mechanical ventilation. High volumes of epicardial adipose tissue and its thickness can cause an infection located in the myocardial tissue, thereby enhancing severe COVID-related myocardial damage with impairments in coronary flow reserve and thromboembolism. Other important components such as sarcopenia and intermuscular fat augment the vulnerability in contracting COVID-19 and increase mortality, inflammation, and muscle damage. Malnutrition is prevalent in this population, but a lack of knowledge remains regarding the beneficial effects aimed at optimizing nutritional status to limit catabolism and preserve muscle mass. Finally, with the increase in patients recovering from COVID-19, evaluation and treatment in those with Long COVID syndrome may become highly relevant.

Associations of Dynapenic Obesity and Sarcopenic Obesity with the Risk of Complications in COVID-19

Ageing is associated with changes in body composition, such as low muscle mass (sarcopenia), decreased grip strength or physical function (dynapenia), and accumulation of fat mass. When the accumulation of fat mass synergistically accompanies low muscle mass or reduced grip strength, it results in sarcopenic obesity and dynapenic obesity, respectively. These types of obesity contribute to the increased risk of cardiovascular disease and mortality in the elderly, which could increase the damage caused by COVID-19. In this review, we associated factors that could generate a higher risk of COVID-19 complications in dynapenic obesity and sarcopenic obesity. For example, skeletal muscle regulates the expression of inflammatory cytokines and supports metabolic stress in pulmonary disease; hence, the presence of dynapenic obesity or sarcopenic obesity could be related to a poor prognosis in COVID-19 patients.

Nutritional Risk Assessment Scores Effectively Predict Mortality in Critically Ill Patients with Severe COVID-19

Background: Malnutrition predicts a worse outcome for critically ill patients. However, quick, easy-to-use nutritional risk assessment tools have not been adequately validated. Aims and Methods: The study aimed to evaluate the role of four biological nutritional risk assessment instruments (the Prognostic Nutritional Index—PNI, the Controlling Nutritional Status Score—CONUT, the Nutrition Risk in Critically Ill—NUTRIC, and the modified NUTRIC—mNUTRIC), along with CT-derived fat tissue and muscle mass measurements in predicting in-hospital mortality in a consecutive series of 90 patients hospitalized in the intensive care unit for COVID-19-associated ARDS. Results: In-hospital mortality was 46.7% (n = 42/90). Non-survivors had a significantly higher nutritional risk, as expressed by all four scores. All scores were independent predictors of mortality on the multivariate regression models. PNI had the best discriminative capabilities for mortality, with an area under the curve (AUC) of 0.77 for a cut-off value of 28.05. All scores had an AUC above 0.72. The volume of fat tissue and muscle mass were not associated with increased mortality risk. Conclusions: PNI, CONUT, NUTRIC, and mNUTRIC are valuable nutritional risk assessment tools that can accurately predict mortality in critically ill patients with COVID-19-associated ARDS.

Prediction of abdominal CT body composition parameters by thoracic measurements as a new approach to detect sarcopenia in a COVID-19 cohort

As most COVID-19 patients only receive thoracic CT scans, but body composition, which is relevant to detect sarcopenia, is determined in abdominal scans, this study aimed to investigate the relationship between thoracic and abdominal CT body composition parameters in a cohort of COVID-19 patients. This retrospective study included n = 46 SARS-CoV-2-positive patients who received CT scans of the thorax and abdomen due to severe disease progression. The subcutaneous fat area (SF), the skeletal muscle area (SMA), and the muscle radiodensity attenuation (MRA) were measured at the level of the twelfth thoracic (T12) and the third lumbar (L3) vertebra. Necessity of invasive mechanical ventilation (IMV), length of stay, or time to death (TTD) were noted. For statistics correlation, multivariable linear, logistic, and Cox regression analyses were employed. Correlation was excellent for the SF (r = 0.96) between T12 and L3, and good for the respective SMA (r = 0.80) and MRA (r = 0.82) values. With adjustment (adj.) for sex, age, and body-mass-index the variability of SF (adj. r² = 0.93; adj. mean difference = 1.24 [95% confidence interval (95% CI) 1.02–1.45]), of the SMA (adj. r² = 0.76; 2.59 [95% CI 1.92–3.26]), and of the MRA (adj. r² = 0.67; 0.67 [95% CI 0.45–0.88]) at L3 was well explained by the respective values at T12. There was no relevant influence of the SF, MRA, or SMA on the clinical outcome. If only thoracic CT scans are available, CT body composition values at T12 can be used to predict abdominal fat and muscle parameters, by which sarcopenia and obesity can be assessed.

Pectoralis Muscle Mass on Chest CT at Admission Predicts Prognosis in Patients with Pneumonia

Methods

A retrospective cohort study was performed in patients aged 18 years or older with pneumonia who underwent chest CT within 24 hours of admission between April 2014 and March 2019. We measured the thickness, area, and volume of the pectoralis major and minor muscles at the level of the aortic arch. Factors associated with mortality were examined using logistic regression analysis.

Results

A total of 483 patients (mean age 77 ± 14 years, 300 men (62%)) were included, and fifty-one patients (11%) died during admission. In univariate analysis, decreased thickness, area, and volume of the pectoralis major and minor muscles were associated with higher in-hospital mortality. Multivariate analysis with adjustment for age, gender, serum albumin, and A-DROP revealed that thinner pectoralis major and minor muscles were independent factors of poor prognosis (odds ratio: 0.878, 95% confidence interval (CI): 0.783-0.985, P=0.026 and odds ratio: 0.842, 95% CI: 0.733-0.968, P=0.016, respectively). Approximately 25% of the patients died when the pectoralis minor muscle thickness was 5 mm or less, and no patients died when it was 15 mm or more.

Conclusion

The pectoralis muscle mass may be an independent prognostic factor in hospitalized patients with pneumonia.

Association of body composition parameters measured on CT with risk of hospitalization in patients with Covid-19

PURPOSE

To assess prognostic value of body composition parameters measured at CT to predict risk of hospitalization in patients with COVID-19 infection.

METHODS

177 patients with SARS-CoV-2 infection and with abdominopelvic CT were included in this retrospective IRB approved two-institution study. Patients were stratified based on disease severity as outpatients (no hospital admission) and patients who were hospitalized (inpatients). Two readers blinded to the clinical outcome segmented axial CT images at the L3 vertebral body level for visceral adipose tissue (VAT), subcutaneous adipose tissue (SAT), muscle adipose tissue (MAT), muscle mass (MM). VAT to total adipose tissue ratio (VAT/TAT), MAT/MM ratio, and muscle index (MI) at L3 were computed. These measures, along with detailed clinical risk factors, were compared in patients stratified by severity. Various logistic regression clinical and clinical + imaging models were compared to discriminate inpatients from outpatients.

RESULTS

There were 76 outpatients (43%) and 101 inpatients. Male gender (p = 0.013), age (p = 0.0003), hypertension (p = 0.0003), diabetes (p = 0.0001), history of cardiac disease (p = 0.007), VAT/TAT (p < 0.0001), and MAT/MM (p < 0.0001), but not BMI, were associated with hospitalization. A clinical model (age, gender, BMI) had AUC of 0.70. Addition of VAT/TAT to the clinical model improved the AUC to 0.73. Optimal model that included gender, BMI, race (Black), MI, VAT/TAT, as well as interaction between gender and VAT/TAT and gender and MAT/MM demonstrated the highest AUC of 0.83.

CONCLUSION

MAT/MM and VAT/TAT provides important prognostic information in predicting patients with COVID-19 who are likely to require hospitalization.