Intermuscular Adipose Tissue as a Risk Factor for Mortality and Muscle Injury in Critically Ill Patients Affected by 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.

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.

The effects of myosteatosis on skeletal muscle function in older adults

Myosteatosis, or the infiltration of fatty deposits into skeletal muscle, occurs with advancing age and contributes to the health and functional decline of older adults. Myosteatosis and its inflammatory milieu play a larger role in adipose tissue dysfunction, muscle tissue dysfunction, and increased passive muscle stiffness. Combined with the age-related decline of sex hormones and development of anabolic resistance, myosteatosis also contributes to insulin resistance, impaired muscle mechanics, loss of force production from the muscle, and increased risk of chronic disease. Due to its highly inflammatory secretome and the downstream negative effects on muscle metabolism and mechanics, myosteatosis has become an area of interest for aging researchers and clinicians. Thus far, myosteatosis treatments have had limited success, as many lack the potency to completely rescue the metabolic and physical consequences of myosteatosis. Future research is encouraged for the development of reliable assessment methods for myosteatosis, as well as the continued exploration of pharmacological, nutritional, and exercise-related interventions that may lead to the success in attenuating myosteatosis and its clinical consequences within the aging population.

Myosteatosis predicts short-term mortality in patients with COVID-19: A multicenter analysis

OBJECTIVES

Body composition on computed tomography can predict prognosis in patients with COVID-19. The reported data are based on small retrospective studies. The aim of the present study was to analyze the prognostic relevance of skeletal muscle parameter derived from chest computed tomography for prediction of 30-d mortality in patients with COVID-19 in a multicenter setting.

METHODS

The clinical databases of three centers were screened for patients with COVID-19 between 2020 and 2022. Overall, 447 patients (142 female; 31.7%) were included into the study. The mean age at the time of computed tomography acquisition was 63.8 ± 14.7 y and median age was 65 y. Skeletal muscle area and skeletal muscle density were defined on level T12 of the chest.

RESULTS

Overall, 118 patients (26.3%) died within the 30-d observation period. Of the patient sample, 255 patients (57.0%) were admitted to an intensive care unit and 122 patients needed mechanical ventilation (27.3%). The mean skeletal muscle area of all patients was 96.1 ± 27.2 cm² (range = 23.2-200.7 cm²). For skeletal muscle density, the mean was 24.3 ± 11.1 Hounsfield units (range = -5.6 to 55.8 Hounsfield units). In survivors, the mean skeletal muscle density was higher compared with the lethal cases (mean 25.8 ± 11.2 versus 20.1 ± 9.6; P < 0.0001). Presence of myosteatosis was independently associated with 30-d mortality: odds ratio = 2.72 (95% CI, 1.71-4.32); P = 0.0001.

CONCLUSIONS

Myosteatosis is strongly associated with 30-d mortality in patients COVID-19. Patients with COVID-19 with myosteatosis should be considered a risk group.

Integrated assessment of computed tomography density in pectoralis and erector spinae muscles as a prognostic biomarker for coronavirus disease 2019

BACKGROUND ＆ AIMS: Muscle quantification using chest computed tomography (CT) is a useful prognostic biomarker for coronavirus disease 2019 (COVID-19). However, no studies have evaluated the clinical course through comprehensive assessment of the pectoralis and erector spinae muscles. Therefore, we compared the impact of the areas and densities of these muscles on COVID-19 infection outcome.

METHODS

This multicenter retrospective cohort study was conducted by the COVID-19 Task Force. A total of 1410 patients with COVID-19 were included, and data on the area and density of the pectoralis and erector spinae muscles on chest CT were collected. The impact of each muscle parameter on the clinical outcome of COVID-19 was stratified according to sex. The primary outcome was the percentage of patients with severe disease, including those requiring oxygen supplementation and those who died. Additionally, 167 patients were followed up for changes in muscle parameters at three months and for the clinical characteristics in case of reduced CT density.

RESULTS

For both muscles, low density rather than muscle area was associated with COVID-19 severity. Regardless of sex, lower erector spinae muscle density was associated with more severe disease than pectoralis muscle density. The muscles were divided into two groups using the receiver operating characteristic curve of CT density, and the population was classified into four (Group A: high CT density for both muscles, Group B: low CT density for pectoralis and high for erector spinae muscle. Group C: high CT density for pectoralis and low for erector spinae muscle, Group D: low CT density for both muscles). In univariate analysis, Group D patients exhibited worse outcomes than Group A (OR: 2.96, 95% CI: 2.03-4.34 in men; OR: 3.02, 95% CI: 2.66-10.4 in women). Multivariate analysis revealed that men in Group D had a significantly more severe prognosis than those in Group A (OR: 1.82, 95% CI: 1.16-2.87). Moreover, Group D patients tended to have the highest incidence of other complications due to secondary infections and acute kidney injury during the clinical course. Longitudinal analysis of both muscle densities over three months revealed that patients with decreased muscle density over time were more likely to have severe cases than those who did not.

CONCLUSIONS

Muscle density, rather than muscle area, predicts the clinical outcomes of COVID-19. Integrated assessment of pectoralis and erector spinae muscle densities demonstrated higher accuracy in predicting the clinical course of COVID-19 than individual assessments.

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.

Sarcopenic obesity and its relation with muscle quality and mortality in patients on chronic hemodialysis

BACKGROUND & AIMS

Sarcopenia is prevalent in patients with end-stage kidney disease (ESKD) on hemodialysis (HD), and is associated with poor outcomes, while obesity may be protective. Sarcopenic obesity is associated with increased frailty, morbidity and mortality in the general population. Myosteatosis, i.e., muscle fat infiltration, has major effects on muscle strength and physical performance, but is poorly investigated in the nephrology setting. In the present study we aimed to assess the association between sarcopenic obesity, as diagnosed by abdominal CT, and mortality. Moreover, the relationship between myosteatosis, sarcopenic obesity and mortality was also investigated.

METHODS

This is a retrospective study in which ESKD patients on HD submitted to unenhanced abdominal CT for clinical reasons at least 6 months after dialysis initiation were evaluated for sarcopenic obesity and myosteatosis, defined as intermuscular fat area and low attenuation muscle area. Sarcopenic obesity was diagnosed in cases of low abdominal skeletal muscle area and high total fat area. Receiver-operating characteristics (ROC) analysis with Youden index was used to determine the cut-off for high total fat area. Intermuscular fat area and low attenuation muscle area were evaluated by applying the Hounsfield unit of interest (-190; -30, and -29; +29 respectively). Cox regression analysis was used to evaluate the association between predictors and mortality risk.

RESULTS

We enrolled 212 patients, aged 68.8 (±14.7) years, 65.5% (139/212) male. Median follow-up was 19.7 (interquartile range [IQR] 2.7-35) months. Sarcopenic obesity was diagnosed in 19.8% of patients and was associated with increased mortality (HR: 3.29 (1.72; 6.27), P < 0.001), and with the presence of myosteatosis. Both intermuscular fat area and low attenuation muscle area were associated with increased mortality in adjusted analyses.

CONCLUSIONS

Patients with sarcopenic obesity have increased myosteatosis. Sarcopenic obesity and myosteatosis are associated with increased mortality in patients on HD.

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.

Construction of a nomogram for predicting COVID-19 in-hospital mortality: A machine learning analysis

Background and objectives

We aim to verify the use of ML algorithms to predict patient outcome using a relatively small dataset and to create a nomogram to assess in-hospital mortality of patients with COVID-19.

Methods

A database of 200 COVID-19 patients admitted to the Clinical Hospital of State University of Campinas (UNICAMP) was used in this analysis. Patient features were divided into three categories: clinical, chest abnormalities, and body composition characteristics acquired by computerized tomography. These features were evaluated independently and combined to predict patient outcomes. To minimize performance fluctuations due to low sample number, reduce possible bias related to outliers, and evaluate the uncertainties generated by the small dataset, we developed a shuffling technique, a modified version of the Monte Carlo Cross Validation, creating several subgroups for training the algorithm and complementary testing subgroups. The following ML algorithms were tested: random forest, boosted decision trees, logistic regression, support vector machines, and neural networks. Performance was evaluated by analyzing Receiver operating characteristic (ROC) curves. The importance of each feature in the determination of the outcome predictability was also studied and a nomogram was created based on the most important features selected by the exclusion test.

Results

Among the different sets of features, clinical variables age, lymphocyte number and weight were the most valuable features for prognosis prediction. However, we observed that skeletal muscle radiodensity and presence of pleural effusion were also important for outcome determination. Integrating these independent predictors was successfully developed to accurately predict mortality in COVID-19 in hospital patients. A nomogram based on these five features was created to predict COVID-19 mortality in hospitalized patients. The area under the ROC curve was 0.86 ± 0.04.

Conclusion

ML algorithms can be reliable for the prediction of COVID-19-related in-hospital mortality, even when using a relatively small dataset. The success of ML techniques in smaller datasets broadens the applicability of these methods in several problems in the medical area. In addition, feature importance analysis allowed us to determine the most important variables for the prediction tasks resulting in a nomogram with good accuracy and clinical utility in predicting COVID-19 in-hospital mortality.

Biomarkers extracted by fully automated body composition analysis from chest CT correlate with SARS-CoV-2 outcome severity

The complex process of manual biomarker extraction from body composition analysis (BCA) has far restricted the analysis of SARS-CoV-2 outcomes to small patient cohorts and a limited number of tissue types. We investigate the association of two BCA-based biomarkers with the development of severe SARS-CoV-2 infections for 918 patients (354 female, 564 male) regarding disease severity and mortality (186 deceased). Multiple tissues, such as muscle, bone, or adipose tissue are used and acquired with a deep-learning-based, fully-automated BCA from computed tomography images of the chest. The BCA features and markers were univariately analyzed with a Shapiro–Wilk and two-sided Mann–Whitney-U test. In a multivariate approach, obtained markers were adjusted by a defined set of laboratory parameters promoted by other studies. Subsequently, the relationship between the markers and two endpoints, namely severity and mortality, was investigated with regard to statistical significance. The univariate approach showed that the muscle volume was significant for female (p_severity ≤ 0.001, p_mortality ≤ 0.0001) and male patients (p_severity = 0.018, p_mortality ≤ 0.0001) regarding the severity and mortality endpoints. For male patients, the intra- and intermuscular adipose tissue (IMAT) (p ≤ 0.0001), epicardial adipose tissue (EAT) (p ≤ 0.001) and pericardial adipose tissue (PAT) (p ≤ 0.0001) were significant regarding the severity outcome. With the mortality outcome, muscle (p ≤ 0.0001), IMAT (p ≤ 0.001), EAT (p = 0.011) and PAT (p = 0.003) remained significant. For female patients, bone (p ≤ 0.001), IMAT (p = 0.032) and PAT (p = 0.047) were significant in univariate analyses regarding the severity and bone (p = 0.005) regarding the mortality. Furthermore, the defined sarcopenia marker (p ≤ 0.0001, for female and male) was significant for both endpoints. The cardiac marker was significant for severity (p_female = 0.014, p_male ≤ 0.0001) and for mortality (p_female ≤ 0.0001, p_male ≤ 0.0001) endpoint for both genders. The multivariate logistic regression showed that the sarcopenia marker was significant (p_severity = 0.006, p_mortality = 0.002) for both endpoints (OR_severity = 0.42, 95% CI_severity: 0.23–0.78, OR_mortality = 0.34, 95% CI_mortality: 0.17–0.67). The cardiac marker showed significance (p = 0.018) only for the severity endpoint (OR = 1.42, 95% CI 1.06–1.90). The association between BCA-based sarcopenia and cardiac biomarkers and disease severity and mortality suggests that these biomarkers can contribute to the risk stratification of SARS-CoV-2 patients. Patients with a higher cardiac marker and a lower sarcopenia marker are at risk for a severe course or death. Whether those biomarkers hold similar importance for other pneumonia-related diseases requires further investigation.

Low skeletal muscle radiodensity and neutrophil-to-lymphocyte ratio as predictors of poor outcome in patients with COVID-19

Inflammatory states and body composition changes are associated with a poor prognosis in many diseases, but their role in coronavirus disease 2019 (COVID-19) is not fully understood. To assess the impact of low skeletal muscle radiodensity (SMD), high neutrophil-to-lymphocyte ratio (NLR) and a composite score based on both variables, on complications, use of ventilatory support, and survival in patients with COVID-19. Medical records of patients hospitalized between May 1, 2020, and July 31, 2020, with a laboratory diagnosis of COVID-19 who underwent computed tomography (CT) were retrospectively reviewed. CT-derived body composition measurements assessed at the first lumbar vertebra level, and laboratory tests performed at diagnosis, were used to calculate SMD and NLR. Prognostic values were estimated via univariate and multivariate logistic regression analyses and the Kaplan–Meier curve. The study was approved by the local Institutional Review Board (CAAE 36276620.2.0000.5404). A total of 200 patients were included. Among the patients assessed, median age was 59 years, 58% were men and 45% required ICU care. A total of 45 (22.5%) patients died. Multivariate logistic analysis demonstrated that a low SMD (OR 2.94; 95% CI 1.13–7.66, P = 0.027), high NLR (OR 3.96; 95% CI 1.24–12.69, P = 0.021) and both low SMD and high NLR (OR 25.58; 95% CI 2.37–276.71, P = 0.008) combined, were associated with an increased risk of death. Patients who had both low SMD and high NLR required more mechanical ventilation (P < 0.001) and were hospitalized for a longer period (P < 0.001). Low SMD, high NLR and the composite score can predict poor prognosis in patients with COVID-19, and can be used as a tool for early identification of patients at risk. Systemic inflammation and low muscle radiodensity are useful predictors of poor prognosis, and the assessment of these factors in clinical practice should be considered.

Prognostic Impact of Myosteatosis on Mortality in Hospitalized Patients with COVID-19

Body composition, including sarcopenia, adipose tissue, and myosteatosis, is associated with unfavorable clinical outcomes in patients with coronavirus disease (COVID-19). However, few studies have identified the impact of body composition, including pre-existing risk factors, on COVID-19 mortality. Therefore, this study aimed to evaluate the effect of body composition, including pre-existing risk factors, on mortality in hospitalized patients with COVID-19. This two-center retrospective study included 127 hospitalized patients with COVID-19 who underwent unenhanced chest computed tomography (CT) between February and April 2020. Using the cross-sectional CT images at the L2 vertebra level, we analyzed the body composition, including skeletal muscle mass, visceral to subcutaneous adipose tissue ratio (VSR), and muscle density using the Hounsfield unit (HU). Of 127 patients with COVID-19, 16 (12.6%) died. Compared with survivors, non-survivors had low muscle density (41.9 vs. 32.2 HU, p < 0.001) and high proportion of myosteatosis (4.5 vs. 62.5%, p < 0.001). Cox regression analyses revealed diabetes (hazard ratio [HR], 3.587), myosteatosis (HR, 3.667), and a high fibrosis-4 index (HR, 1.213) as significant risk factors for mortality in patients with COVID-19. Myosteatosis was associated with mortality in hospitalized patients with COVID-19, independent of pre-existing prognostic factors.

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.

Function Over Mass: A Meta-Analysis on the Importance of Skeletal Muscle Quality in COVID-19 Patients

COVID-19 caused by SARS-CoV-2 infection is a highly contagious disease affecting both the higher and lower portions of the respiratory tract. This disease reached over 265 million people and has been responsible for over 5.25 million deaths worldwide. Skeletal muscle quality and total mass seem to be predictive of COVID-19 outcome. This systematic review aimed at providing a critical analysis of the studies published so far reporting on skeletal muscle mass in patients with COVID-19, with the intent of examining the eventual association between muscle status and disease severity. A meta-analysis was performed to evaluate whether skeletal muscle quantity, quality and function were related to disease severity. Systematic reviews and meta-analyses were conducted according to the guidelines of the Cochrane Handbook for Systematic Reviews of Interventions and reported according to the guidelines of the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analysis) guide. From a total of 1,056 references found, 480 were selected after removing duplicates. Finally, only 7 met the specified inclusion criteria. The results of this meta-analysis showed that skeletal muscle quality, rather than quantity, was associated with COVID-19 severity, as confirmed by lower skeletal muscle density and lower handgrip strength in patients with severe disease. Muscle function assessment can thus be a valuable tool with prognostic value in COVID-19.

Myosteatosis Significantly Predicts Persistent Dyspnea and Mobility Problems in COVID-19 Survivors

Background

Persistent symptoms including dyspnea and functional impairment are common in COVID-19 survivors. Poor muscle quality (myosteatosis) associates with poor short-term outcomes in COVID-19 patients. The aim of this observational study was to assess the relationship between myosteatosis diagnosed during acute COVID-19 and patient-reported outcomes at 6 months after discharge.

Methods

Myosteatosis was diagnosed based on CT-derived skeletal muscle radiation attenuation (SM-RA) measured during hospitalization in 97 COVID-19 survivors who had available anthropometric and clinical data upon admission and at the 6-month follow-up after discharge. Dyspnea in daily activities was assessed using the modified Medical Research Council (mMRC) scale for dyspnea. Health-related quality of life was measured using the European quality of life questionnaire three-level version (EQ-5D-3L).

Results

Characteristics of patients with (lowest sex- and age-specific tertile of SM-RA) or without myosteatosis during acute COVID-19 were similar. At 6 months, patients with myosteatosis had greater rates of obesity (48.4 vs. 27.7%, p = 0.046), abdominal obesity (80.0 vs. 47.6%, p = 0.003), dyspnea (32.3 vs. 12.5%, p = 0.021) and mobility problems (32.3 vs. 12.5%, p = 0.004). Myosteatosis diagnosed during acute COVID-19 was the only significant predictor of persistent dyspnea (OR 3.19 [95% C.I. 1.04; 9.87], p = 0.043) and mobility problems (OR 3.70 [95% C.I. 1.25; 10.95], p = 0.018) at 6 months at logistic regression adjusted for sex, age, and BMI.

Conclusion

Myosteatosis diagnosed during acute COVID-19 significantly predicts persistent dyspnea and mobility problems at 6 months after hospital discharge independent of age, sex, and body mass.

Clinical Trial Registration

[www.ClinicalTrials.gov], identifier [NCT04318366].

Neurological consequences of COVID-19 and brain related pathogenic mechanisms: A new challenge for neuroscience

Due to the infection by the SARS-CoV-2 virus (COVID-19) there were also reported neurological symptoms, being the most frequent and best cited those that affect the cerebrovascular, sensorial, cognitive and motor functions, together with the neurological diffuse symptoms as for examples headache or dizziness. Besides, some of them behave high risk of mortality. Consequently, it is crucial to elucidate the mechanisms of action in brain of SARS-CoV-2 virus in order to create new therapeutic targets to fight against this new disease. Since now the mechanisms of arrival to the brain seems to be related with the following processes: blood brain barrier (BBB) disruption together with nervous or axonal transport of the virus by the trigeminal nerve, the vagus nerve, or the brain-gut-axis. Being two the mechanisms of brain affectation most cited: a direct affectation of the virus in the brain through neuroinvasion and an indirect mechanism of action due to the effects of the systemic infection. Both processes include the triggering of inflammation, hypoxia and the increased likelihood of secondary infections. This topic supposes a major novel challenge for neuroscience. Therefore, the aim of this review is to provide summarized information about the neurological symptomatology and the brain pathogenic mechanisms involved and reported in COVID-19.

Effect of Body Composition Change during Neoadjuvant Chemotherapy for Esophageal Squamous Cell Carcinoma

Effects of changes in body composition during neoadjuvant chemotherapy (NAC) on perioperative complications and prognosis are unknown in patients with esophageal squamous cell carcinoma (ESCC). A total of 175 patients who underwent surgery for ESCC in our hospital between 2016 and 2019 were examined. The psoas muscle index (PMI) was calculated from the total psoas muscle area, and the visceral fat mass (VFM) at the umbilical level was measured. We defined body composition change (BCC) group as those with increased VFM of ≥ 3% and decreased PMI of ≥ 3% during NAC. Sarcopenia (S) was defined as PMI < 5.89 (male) and <4.06 (female). Nutritional assessment using the Subjective Global Assessment tool was performed upon admission. The percentages of BCC group, pre-NAC S, and post-NAC S was 32.5%, 79.4%, and 80.0%, respectively. BCC group had significantly more postoperative complications (p < 0.01) and longer hospital stays (p = 0.03) than groups pre-NAC S and post-NAC S. Overall survival (OS) analysis using the Cox hazard model showed that stage III (p < 0.01) and post-NAC S (p = 0.03) were poor prognostic factors. Changes in body composition during NAC affected perioperative complications and prognosis of patients with ESCC.

Research on SARS-COV-2 pandemic: a narrative review focused on the Italian contribution

Background

Since late 2019, a severe acute respiratory syndrome, caused by the severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), has spread with overwhelming speed causing over 214 million confirmed infections and more than 4.5 million deaths worldwide. In this framework, Italy had the second highest number of SARS-CoV-2 infections worldwide, and the largest number of deaths. A global effort of both the scientific community and governments has been undertaken to stem the pandemic. The aim of this paper is to perform a narrative review of the Italian contribution to the scientific literature regarding intensive care management of patients suffering from COVID-19, being one of the first western countries to face an outbreak of SARS-CoV-2 infection.

Main body

We performed a narrative review of the literature, dedicating particular attention and a dedicated paragraph to ventilatory support management, chest imaging findings, biomarkers, possible pharmacological interventions, bacterial superinfections, prognosis and non-clinical key aspects such as communication and interaction with relatives.

Conclusions

Many colleagues, nurses and patients died leaving their families alone. To all of them, we send our thoughts and dedicate these pages.