Intramuscular adipose tissue at level Th12 is associated with survival in COVID-19

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.

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.

The impact of muscle mass and myosteatosis on mortality in critically ill patients with Sars-Cov2-related pneumonia

BACKGROUND & AIMS

Sars-Cov-2 pneumonia can lead to severe complications, requiring invasive mechanical ventilation and admission to the intensive care unit (ICU). Low muscle quantity and quality (the latter evaluated by the amount of ectopic fat infiltration in the muscle [myosteatosis]) at ICU admission are associated with worse outcomes in critically ill patients. The purpose of the present study is to assess muscle mass and myosteatosis of paravertebral skeletal muscle, in critically ill patients with Sars-Cov2 pneumonia and its association with mortality.

METHODS

We conducted a retrospective observational study in 110 critically ill patients with severe Sars-Cov-2 pneumonia that had a high - resolution chest Computerized Tomography (HR-CT) at ICU admission. We acquired CT images at the level of the thoracic 12 (T12) vertebral body and measured skeletal muscle area (SMA), intermuscular adipose tissue (IMAT), and low attenuation muscle area (LAMA). Patients were followed until ICU mortality or discharge.

RESULTS

Patients were 59.8 ± 8.1 years old, 77% were male. Seventy-nine percent of patients were considered at nutritional risk, and 22% were obese. Average Acute Physiology and Chronic Health Evaluation II (APACHE II) score was 17 ± 5.4, and the overall ICU mortality was 48,2% (53/110). At ICU admission, both parameters of myosteatosis were associated with higher mortality (IMAT [per 10% increase] HR: 2.01 (95% Confidence Interval [CI] 1.27 to 3.17), P = 0.003; LAMA HR [per 10% increase]: 1.53 (95% CI 1.10 to 2.13), P = 0.012).

CONCLUSION

Myosteatosis as assessed by CT scans plays a relevant role as a prognostic marker in critically ill patients with Sars-Cov2 severe pneumonia.

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.

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

OBJECTIVE

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

METHODS

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

RESULTS

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

CONCLUSION

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

ADVANCES IN KNOWLEDGE

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

Sarcopenia and COVID-19 Outcomes

Coronavirus disease 2019 (COVID-19) spread rapidly and became a severe global public health threat. Older adults have a high risk of COVID-19 and its associated mortality. Sarcopenia has emerged as a predictor of poor outcomes in COVID-19 patients, including lengthy hospital stays, mortality, intensive care unit admission, need for invasive mechanical ventilation, and poor rehabilitation outcomes. Chronic inflammation, immune dysfunction, respiratory muscle dysfunction, and swallowing dysfunction may underlie the association between sarcopenia and the poor outcomes of COVID-19 patients. Interleukin 6 receptor blockers (tocilizumab or sarilumab) are recommended for treating patients with severe COVID-19, and their therapeutic effects on sarcopenia are of great interest. This review aimed to analyze the current reports on the association between sarcopenia and COVID-19 and provide an update on the contribution of sarcopenia to the severity and adverse outcomes of COVID-19 and its underlying mechanisms. We also aimed to explore the different screening tools for sarcopenia concurrent with COVID-19, and advocate for early diagnosis and treatment of sarcopenia. Given that the fight against the COVID-19 pandemic may be long-term, further research into understanding the effects of sarcopenia in patients infected with the Omicron variant is necessary.

Prognostic Role of the Pectoralis Musculature in Patients with COVID-19. A Multicenter Study

RATIONALE AND OBJECTIVES

To evaluate the impact of low skeletal muscle mass in patients with COVID-19 on relevant outcomes like 30-day mortality, need for intubation and need for intensive care unit admission.

MATERIALS AND METHODS

For this study, data from six centers were acquired. The acquired sample comprises 1138 patients. There were 547 women (48.1%) and 591 men (51.9%) with a mean age of 54.5 ± 18.8 years; median age, 55 years; range, 18-84 years). In every case, thoracic CT without intravenous application of contrast medium was performed. The following parameters of the pectoralis muscles were estimated: muscle area as a sum of the bilateral areas of the pectoralis major and minor muscles, muscle density, muscle index (PMI) (pectoralis muscle area divided by the patient's body height square) as a ratio pectoralis major and minor muscles divided by the patient's body height², and muscle gauge as PMI x muscle density.

RESULTS

Overall, 220 patients (19.33%) were admitted to the intensive care unit. In 171 patients (15.03%), mechanical lung ventilation was performed. Finally, 154 patients (13.53%) died within the observation time of 30-day. All investigated parameters of pectoralis muscle were lower in the patients with unfavorable courses of Covid-19. All pectoralis muscle parameters were associated with 30-day mortality in multivariate analyses adjusted for age and sex: pectoralis muscle area, HR = 0.93 CI 95% (0.91-0.95) p < 0.001; pectoralis muscle density, HR = 0.94 CI 95% (0.93-0.96) p < 0.001; pectoralis muscle index, HR = 0.79 CI 95% (0.75-0.85) p < 0.001, pectoralis muscle gauge, HR = 0.995 CI 95% (0.99-0.996) p < 0.001.

CONCLUSION

in COVID-19, survivors have larger areas and higher index, gauge and density of the pectoralis muscles in comparison to nonsurvivors. However, the analyzed muscle parameters cannot be used for prediction of disease courses.

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.

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.

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].

Association between CT-Based Preoperative Sarcopenia and Outcomes in Patients That Underwent Liver Resections

Simple Summary

Cancer cachexia often includes sarcopenia, which is characterized by a progressive, generalized loss of skeletal muscle mass and strength, combined with fatty infiltration into the muscle. Sarcopenia has been considered a patient-specific imaging biomarker for predicting outcomes after cancer surgery. The present study aimed to evaluate whether preoperative sarcopenia was associated with postoperative outcomes and survival in patients that underwent liver resections. Sarcopenia, assessed by preoperative CT imaging, was present in two-thirds of patients. Independent risk factors for sarcopenia were age, male sex, ASA score ≥ 3, and malignancies. Based on CT assessment alone, sarcopenia had no impact on clinical outcomes or overall survival after hepatectomy.

Abstract

This retrospective observational study aimed to evaluate whether preoperative sarcopenia, assessed by CT imaging, was associated with postoperative clinical outcomes and overall survival in patients that underwent liver resections. Patients operated on between January 2014 and February 2020 were included. The skeletal muscle index (SMI) was measured at the level of the third lumbar vertebra on preoperative CT scans. Preoperative sarcopenia was defined based on pre-established SMI cut-off values. The outcomes were postoperative morbidity, length of hospital stay (LOS), and overall survival. Among 355 patients, 212 (59.7%) had preoperative sarcopenia. Patients with sarcopenia were significantly older (63.5 years) and had significantly lower BMIs (23.9 kg/m²) than patients without sarcopenia (59.3 years, p < 0.01, and 27.7 kg/m², p < 0.01, respectively). There was no difference in LOS (8 vs. 8 days, p = 0.75), and the major complication rates were comparable between the two groups (11.2% vs. 11.3%, p = 1.00). The median overall survival times were comparable between patients with sarcopenia and those without sarcopenia (15 vs. 16 months, p = 0.87). Based on CT assessment alone, preoperative sarcopenia appeared to have no impact on postoperative clinical outcomes or overall survival in patients that underwent liver resections. Future efforts should also consider muscle strength and physical performance, in addition to imaging, for preoperative risk stratification.