Computed tomography-defined body composition as prognostic markers for unfavourable outcomes and in-hospital mortality in coronavirus disease 2019

Integrative metagenomics and metabolomics reveal age-associated gut microbiota and metabolite alterations in a hamster model of COVID-19

Aging is a key contributor of morbidity and mortality during acute viral pneumonia. The potential role of age-associated dysbiosis on disease outcomes is still elusive. In the current study, we used high-resolution shotgun metagenomics and targeted metabolomics to characterize SARS-CoV-2-associated changes in the gut microbiota from young (2-month-old) and aged (22-month-old) hamsters, a valuable model of COVID-19. We show that age-related dysfunctions in the gut microbiota are linked to disease severity and long-term sequelae in older hamsters. Our data also reveal age-specific changes in the composition and metabolic activity of the gut microbiota during both the acute phase (day 7 post-infection, D7) and the recovery phase (D22) of infection. Aged hamsters exhibited the most notable shifts in gut microbiota composition and plasma metabolic profiles. Through an integrative analysis of metagenomics, metabolomics, and clinical data, we identified significant associations between bacterial taxa, metabolites and disease markers in the aged group. On D7 (high viral load and lung epithelial damage) and D22 (body weight loss and fibrosis), numerous amino acids, amino acid-related molecules, and indole derivatives were found to correlate with disease markers. In particular, a persistent decrease in phenylalanine, tryptophan, glutamic acid, and indoleacetic acid in aged animals positively correlated with poor recovery of body weight and/or lung fibrosis by D22. In younger hamsters, several bacterial taxa (Eubacterium, Oscillospiraceae, Lawsonibacter) and plasma metabolites (carnosine and cis-aconitic acid) were associated with mild disease outcomes. These findings support the need for age-specific microbiome-targeting strategies to more effectively manage acute viral pneumonia and long-term disease outcomes.

Prognostic relevance of CT-defined body composition in patients with acute bleeding undergoing endovascular embolization

OBJECTIVES

Body composition assessment includes the parameter skeletal muscle mass, subcutaneous and visceral adipose tissue (SAT and VAT). The purpose of this study was to elucidate associations of body composition parameters with mortality in patients with acute bleeding undergoing transarterial embolization (TAE).

METHODS

A mixed cohort of patients from 2018 to 2022 with acute bleeding requiring treatment with a TAE was retrospectively evaluated. In every case, the triphasic CT to diagnose the source of bleeding was used to calculate the body composition parameters.

RESULTS

A total of 251 patients (93 female, 37.1%) with a mean age of 65.5 ± 14.3 years, 30-d mortality of 40.2%, and 24-h mortality of 7.6% were included in the analysis. In the Cox regression analysis, no statistically significant correlations were found between the body composition parameters and 24-h or 30-day mortality. In the subgroup analysis of patients aged older than 65 years, skeletal muscle index was associated with short-term 24-h mortality HR of 0.95 (95% CI 0.90; 0.99, P = .035).

CONCLUSIONS

The present study demonstrated the prognostic impact of clinical, laboratory, aniography-related, and CT-defined body composition in patients with acute haemorrhage undergoing endovascular therapy. Although the overall effect of CT-defined body composition appears to be small, skeletal muscle index was a prognostic factor in the age group over 65 years.

ADVANCES IN KNOWLEDGE

This is a large single-centre study to investigate the prognostic relevance of CT-defined body composition in patients undergoing TAE. The effect is overall small but might be further investigated in older patients in further trials.

Incidence of secondary pericardial effusions associated with different etiologies: a comprehensive review of literature

Pericardial effusion is a relatively common complication associated with inflammatory and non-inflammatory diseases. The primary etiology of this condition could be considered when choosing therapeutic options and factors such as effusion size and its hemodynamic consequence. In most cases, small to moderate pericardial effusions can be managed with observation and anti-inflammatory medications unless the effusion develops rapidly. However, in a small proportion of patients, large effusions lead to impaired cardiac filling with hemodynamic compromise and cardiovascular collapse due to cardiac tamponade. The rate at which fluid accumulates is the primary determinant of hemodynamic impact and thus guides the choice of treatment, irrespective of the effusion's size. Severe cases are typically treated with pericardiocentesis with echocardiographic guidance. More aggressive treatments may be necessary for cases due to purulent or malignant etiologies. These cases may require a pericardial window to allow for long-term drainage of the pericardial fluid. This comprehensive review focuses on the epidemiology of pericardial effusion and discusses pathophysiology, diagnostic approaches, and therapeutic options for different causes of secondary pericardial effusions.

Integrative metagenomics and metabolomics reveal age-associated gut microbiota and metabolite alterations in experimental COVID-19

Aging is a key contributor of morbidity and mortality during acute viral pneumonia. The potential role of age-associated dysbiosis on disease outcomes is still elusive. In the current study, we used high-resolution shotgun metagenomics and targeted metabolomics to characterize SARS-CoV-2-associated changes in the gut microbiota from young (2-month-old) and aged (22-month-old) hamsters, a valuable model of COVID-19. We show that age-related dysfunctions in the gut microbiota are linked to disease severity and long-term sequelae in older hamsters. Our data also reveal age-specific changes in the composition and metabolic activity of the gut microbiota during both the acute phase (day 7 post-infection, D7) and the recovery phase (D22) of infection. Aged hamsters exhibited the most notable shifts in gut microbiota composition and plasma metabolic profiles. Through an integrative analysis of metagenomics, metabolomics, and clinical data, we identified significant associations between bacterial taxa, metabolites and disease markers in the aged group. On D7 (high viral load and lung epithelial damage) and D22 (body weight loss and fibrosis), numerous amino acids, amino acid-related molecules, and indole derivatives were found to correlate with disease markers. In particular, a persistent decrease in phenylalanine, tryptophan, glutamic acid, and indoleacetic acid in aged animals positively correlated with poor recovery of body weight and/or lung fibrosis by D22. In younger hamsters, several bacterial taxa ( Eubacterium , Oscillospiraceae , Lawsonibacter ) and plasma metabolites (carnosine and cis-aconitic acid) were associated with mild disease outcomes. These findings support the need for age-specific microbiome-targeting strategies to more effectively manage acute viral pneumonia and long-term disease outcomes.

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.

Short-term mortality prediction in acute pulmonary embolism: Radiomics values of skeletal muscle and intramuscular adipose tissue

BACKGROUND

Acute pulmonary embolism (APE) is a potentially life-threatening disorder, emphasizing the importance of accurate risk stratification and survival prognosis. The exploration of imaging biomarkers that can reflect patient survival holds the potential to further enhance the stratification of APE patients, enabling personalized treatment and early intervention. Therefore, in this study, we develop computed tomography pulmonary angiography (CTPA) radiomic signatures for the prognosis of 7- and 30-day all-cause mortality in patients with APE.

METHODS

Diagnostic CTPA images from 829 patients with APE were collected. Two hundred thirty-four features from each skeletal muscle (SM), intramuscular adipose tissue (IMAT) and both tissues combined (SM + IMAT) were calculated at the level of thoracic vertebra 12. Radiomic signatures were derived using 10 times repeated three-fold cross-validation on the training data for SM, IMAT and SM + IMAT for predicting 7- and 30-day mortality independently. The performance of the radiomic signatures was then evaluated on held-out test data and compared with the simplified pulmonary embolism severity index (sPESI) score, a well-established biomarker for risk stratification in APE. Predictive accuracy was assessed by the area under the receiver operating characteristic curve (AUC) with a 95% confidence interval (CI), sensitivity and specificity.

RESULTS

The radiomic signatures based on IMAT and a combination of SM and IMAT (SM + IMAT) achieved moderate performance for the prediction of 30-day mortality on test data (IMAT: AUC = 0.68, 95% CI [0.57-0.78], sensitivity = 0.57, specificity = 0.73; SM + IMAT: AUC = 0.70, 95% CI [0.60-0.79], sensitivity = 0.74, specificity = 0.54). Radiomic signatures developed for predicting 7-day all-cause mortality showed overall low performance. The clinical signature, that is, sPESI, achieved slightly better performance in terms of AUC on test data compared with the radiomic signatures for the prediction of both 7- and 30-day mortality on the test data (7 days: AUC = 0.73, 95% CI [0.67-0.79], sensitivity = 0.92, specificity = 0.16; 30 days: AUC = 0.74, 95% CI [0.66-0.82], sensitivity = 0.97, specificity = 0.16).

CONCLUSIONS

We developed and tested radiomic signatures for predicting 7- and 30-day all-cause mortality in APE using a multicentric retrospective dataset. The present multicentre work shows that radiomics parameters extracted from SM and IMAT can predict 30-day all-cause mortality in patients with APE.

Pericardial Effusion Predicts Clinical Outcomes in Patients with COVID-19: A Nationwide Multicenter Study

RATIONALE AND OBJECTIVES

The prognostic role of pericardial effusion (PE) in Covid 19 is unclear. The aim of the present study was to estimate the prognostic role of PE in patients with Covid 19 in a large multicentre setting.

MATERIALS AND METHODS

This retrospective study is a part of the German multicenter project RACOON (Radiological Cooperative Network of the Covid 19 pandemic). The acquired sample comprises 1197 patients, 363 (30.3%) women and 834 (69.7%) men. In every case, chest computed tomography was analyzed for PE. Data about 30-day mortality, need for mechanical ventilation and need for intensive care unit (ICU) admission were collected. Data were evaluated by means of descriptive statistics. Group differences were calculated with Mann-Whitney test and Fisher exact test. Uni-and multivariable regression analyses were performed.

RESULTS

Overall, 46.4% of the patients were admitted to ICU, mechanical lung ventilation was performed in 26.6% and 30-day mortality was 24%. PE was identified in 159 patients (13.3%). The presence of PE was associated with 30-day mortality: HR= 1.54, CI 95% (1.05; 2.23), p = 0.02 (univariable analysis), and HR= 1.60, CI 95% (1.03; 2.48), p = 0.03 (multivariable analysis). Furthermore, density of PE was associated with the need for intubation (OR=1.02, CI 95% (1.003; 1.05), p = 0.03) and the need for ICU admission (OR=1.03, CI 95% (1.005; 1.05), p = 0.01) in univariable regression analysis. The presence of PE was associated with 30-day mortality in male patients, HR= 1.56, CI 95%(1.01-2.43), p = 0.04 (multivariable analysis). In female patients, none of PE values predicted clinical outcomes.

CONCLUSION

The prevalence of PE in Covid 19 is 13.3%. PE is an independent predictor of 30-day mortality in male patients with Covid 19. In female patients, PE plays no predictive role.

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.

Chest CT opportunistic biomarkers for phenotyping high-risk COVID-19 patients: a retrospective multicentre study

OBJECTIVE

To assess the value of opportunistic biomarkers derived from chest CT performed at hospital admission of COVID-19 patients for the phenotypization of high-risk patients.

METHODS

In this multicentre retrospective study, 1845 consecutive COVID-19 patients with chest CT performed within 72 h from hospital admission were analysed. Clinical and outcome data were collected by each center 30 and 80 days after hospital admission. Patients with unknown outcomes were excluded. Chest CT was analysed in a single core lab and behind pneumonia CT scores were extracted opportunistic data about atherosclerotic profile (calcium score according to Agatston method), liver steatosis (≤ 40 HU), myosteatosis (paraspinal muscle F < 31.3 HU, M < 37.5 HU), and osteoporosis (D12 bone attenuation < 134 HU). Differences according to treatment and outcome were assessed with ANOVA. Prediction models were obtained using multivariate binary logistic regression and their AUCs were compared with the DeLong test.

RESULTS

The final cohort included 1669 patients (age 67.5 [58.5-77.4] yo) mainly men 1105/1669, 66.2%) and with reduced oxygen saturation (92% [88-95%]). Pneumonia severity, high Agatston score, myosteatosis, liver steatosis, and osteoporosis derived from CT were more prevalent in patients with more aggressive treatment, access to ICU, and in-hospital death (always p < 0.05). A multivariable model including clinical and CT variables improved the capability to predict non-critical pneumonia compared to a model including only clinical variables (AUC 0.801 vs 0.789; p = 0.0198) to predict patient death (AUC 0.815 vs 0.800; p = 0.001).

CONCLUSION

Opportunistic biomarkers derived from chest CT can improve the characterization of COVID-19 high-risk patients.

CLINICAL RELEVANCE STATEMENT

In COVID-19 patients, opportunistic biomarkers of cardiometabolic risk extracted from chest CT improve patient risk stratification.

KEY POINTS

• In COVID-19 patients, several information about patient comorbidities can be quantitatively extracted from chest CT, resulting associated with the severity of oxygen treatment, access to ICU, and death. • A prediction model based on multiparametric opportunistic biomarkers derived from chest CT resulted superior to a model including only clinical variables in a large cohort of 1669 patients suffering from SARS- CoV2 infection. • Opportunistic biomarkers of cardiometabolic comorbidities derived from chest CT may improve COVID-19 patients' risk stratification also in absence of detailed clinical data and laboratory tests identifying subclinical and previously unknown conditions.

Prognostic Value of Diaphragm Diameter, Muscle Volume, and Bone Mineral Density in Critically Ill COVID-19 Patients

Objective: We aimed to analyze the prognostic value of muscle volume (MV), bone mineral density (BMD), and diaphragm diameter (DD) in COVID-19. Method: The study included 498 patients admitted to the intensive care unit (ICU) with a positive polymerase chain reaction test for COVID-19 from March 11, 2020, through August 31, 2022. The patients' laboratory and demographic data of the patients at the time of ICU admission were recorded. MV, DD, and BMD measurements were performed using computed tomography examinations. Muscle index (MI) was calculated as MV/height2. Quartiles were determined for all 4 measurements. Patients in the lowest quartile were recorded as having low MV, MI, DD, and BMD values. The parameters were evaluated for the whole group and compared according to gender and mortality. The multiple regression analysis was performed for the prediction of mortality. Results: In the mortality group, the male and female patients had significantly statistically lower values in MV (P < .001 and P = .002, respectively), MI (P < .001 and P = .005, respectively), DD (P < .001 and P < .001, respectively), and BMD (P = .002 and P < .001, respectively). In the multiple regression analysis, low MI (OR: 2.03, 95% CI: 1.14-3.61, P = .016) and DD (OR: 10.47, 95% CI: 5.59-19.59, P < .001) values remained significant for the prediction of mortality. Conclusion: BMD is a risk factor for mortality in patients with severe COVID-19, but cannot be used as an independent predictor. However, MI and DD can be used as independent predictors of mortality even in severe cases.

Which vertebral level should be used to calculate sarcopenia in covid-19 patients? A systematic review and meta-analysis

BACKGROUND & AIMS

Evidence shows that CT-derived sarcopenia can predict adverse outcomes in COVID-19 patients. However, discrepancies exist as to which vertebral level can be used to calculate sarcopenia which can effectively serve as a prognostic tool. Thus, we aim to investigate the difference in sarcopenia calculated at the Thoracic and Lumbar vertebral levels.

METHODS

An online literature search was conducted on Electronic databases such as PubMed, Cochrane CENTRAL, and Google scholar. Meta-analysis was performed by using Revman 5.3 software.

RESULTS

A total of 14 articles were selected for meta-analysis. The prevalence of sarcopenia calculated at the Thoracic level was 31% (95%CI 24%-37%; p < 0.00001; I² = 86%), while sarcopenia calculated at the Lumbar vertebral level was 63% (95%CI 51%-75%; p < 0.00001; I² = 88%). Meanwhile, sarcopenia calculated at the Upper thoracic level was a significant predictor of mortality OR 3.47 (95%CI 1.74-6.91; p = 0.0004; I² = 56%)as compared to sarcopenia calculated at the lower thoracic OR 1.74 (95%Cl 0.91-3.33; p = 0.10; I² = 60%)or lumbar level OR 2.49 (95%CI 0.45-13.72; p = 0.30; I² = 57%). In addition to this sarcopenia calculated at the Upper thoracic level was also a significant predictor of severe illness OR 3.92 (95%CI 2.33-6.58; p < 0.00001; I² = 0%) as compared to lower thoracic OR 1.40 (95%CI 0.78-2.53; p = 0.26; I² = 67%) or lumbar level OR 1.64 (95%CI 0.26-10.50; p = 0.60; I² = 81%) CONCLUSIONS: Sarcopenia calculated at the thoracic vertebrae and lumber level has different prognostic values. Sarcopenia is prevalent at the lumbar level. Sarcopenia at the thoracic level has a higher mortality and severity rate.

Radiologic Features of T10 Paravertebral Muscle Sarcopenia: Prognostic Factors in COVID-19

Background

Sarcopenia, defined as a small cross-sectional area (CSA) in computed tomography (CT) measurements of skeletal muscles, serves as a disease severity marker in various clinical scenarios, including pulmonary conditions and critical illness. Another parameter of sarcopenia, the level of myosteatosis, reflected by the tissue's radiodensity, in the thoracic skeletal muscles group, has been linked to disease progression in coronavirus disease 2019 (COVID-19) patients. We hypothesize that CT-derived measurements of the skeletal muscle density (SMD) and the CSA of thoracic skeletal muscles can predict outcomes in COVID-19 pneumonia.

Methods

We retrospectively reviewed the CT scans of 84 patients with COVID-19 pneumonia admitted to two of Greece's largest academic teaching hospitals between April 2020 and February 2021. CSA and SMD at the level of the T10 vertebra were measured using computational imaging methods. The patient population was stratified according to survival status and CT severity score (CT-SS). Correlations were drawn between the radiologic features of sarcopenia, CT severity subgroups, serum inflammatory markers, and adverse events, e.g., death and intubation.

Results

Thoracic muscles' CSA measurements correlate with CT-SS and prominent inflammatory markers, such as white blood cell (WBC), C-reactive protein (CRP), fibrinogen, and D-dimers. Moreover, according to linear regression analysis, CSA seems to predict CT-SS variation significantly (β = -0.266, P = 0.018). CSA proved to differ significantly across survivors (P = 0.027) but not between CT severity categories and intubation subgroups. The AUC (area under the curve) of the receiver operating characteristic (ROC) curve for the predictive value of thoracic muscles' CSA in mortality is 0.774 (95% confidence interval (CI): 0.66 - 0.83, P < 0.000). The optimal cut-off value (Youden index = 0.57) for mortality prognosis, with a sensitivity of 66.7% and a specificity of 88.9%, is 15.55. Thoracic muscles' SMD analyses did not reveal any significant correlations.

Conclusions

Easy to obtain and accurately calculated, radiologic features can provide a reliable alternative to laboratory methods for predicting survival in COVID-19. Thoracic muscles' CSA measurement in the level of the T10 vertebra, an acclaimed prognostic imaging assessment that relates directly to CT-SS and inflammatory markers in COVID-19 pneumonia, is a fairly specific tool for survival prognosis.

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.

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.

Low thoracic skeletal muscle index is associated with negative outcomes in 244 patients with respiratory COVID-19

BACKGROUND

Sarcopenia is associated with negative outcomes in intensive care unit (ICU) patients and during chronic diseases. We aimed to evaluate if low skeletal muscle index (SMI) measured by computed tomography (CT) at the thoracic level is associated with poor outcomes in hospitalized patients with respiratory COVID-19.

METHODS

Patients admitted to the hospital between March 1st and June 9, 2020 with a confirmed diagnosis of respiratory COVID-19 in the Emergency Department were included in this retrospective cohort study. SMI was assessed from a transverse CT image at the T12 level. We analysed the association between thoracic SMI and mortality, ICU admissions, infections, length of stay and gravity scores.

RESULTS

We included 244 patients, whose median age was 62 (20-95) years, mean body mass index was 28,6 kg/m2, and 34% were obese patients. 102 patients (41,8%) had low thoracic SMI. On multivariable analysis, low thoracic SMI was associated with more infections (OR = 1,88 [1,06-2,98]) and increased length of stay (OR = 1,87 [1,14-3,49]) but not with mortality (OR = 1.37 [0.54-3.52]), whereas it was inversely associated with ICU admission (OR = 5,56 [1,96-16,67].

CONCLUSION

Low SMI measured by CT at the thoracic level T12 is associated with negative outcomes in patients with respiratory COVID-19.

Sarcopenia indicate poor survival in patients undergoing transarterial chemoembolization (TACE) for hepatic malignancies

BACKGROUND

Patient selection for transarterial chemoembolization (TACE) has remained challenging. Currently used markers mainly reflect liver function and turned out as less reliable in larger clinical trials. The patients´ body composition has been linked with patient outcome in different cancers. Now, we analyzed the function of different parameters of the patient's body composition as prognostic and/ or predictive parameters in patients that received TACE.

METHODS

CT scans were used to assess five parameters of the individual body composition (skeletal muscle index (SMI), median muscular attenuation (MMA), bone mineral density (BMD) as well as the visceral and subcutaneous fat area) in 89 patients undergoing TACE. Results were correlated with tumor response to TACE and outcome of patients.

RESULTS

SMI and visceral fat area were significantly higher in male patients and among patients undergoing TACE for HCC compared to patients with liver metastases. While all parameters of the body composition did not predict response to TACE, patients with an SMI below the ideal cutoff value of 37.76 cm²/m² had a significantly reduced long-term outcome with a median overall survival of 404 days compared to 1321 days for patients with a high SMI. Moreover, the pre-interventional SMI turned out as an independent prognostic factor in a multivariate Cox regression model including clinicopathological parameters and laboratory markers of organ dysfunction and systemic inflammation (HR: 0.899, 95% CI 0.827-0.979, p = 0.014).

CONCLUSION

The pre-interventional SMI represents an independent prognostic factor for overall survival following TACE. Assessment of the individual body composition using routine CT scan might help to identify the ideal patients for TACE.

Factors associated with mortality in hospitalised, non-severe, older COVID-19 patients - the role of sarcopenia and frailty assessment

BACKGROUND

COVID-19 has affected older persons the most. The propensity to have severe COVID-19 or die of the infection was especially prevalent among older subjects with multimorbidity, frailty and sarcopenia. The aim of our study was to check which of the simple clinical biomarkers, including the assessment of muscle and frailty, would associate with the survival and the length of hospital stay in older patients with COVID-19. An additional aim was to report the influence of chronic diseases, chronic medication use, and COVID-19 signs and symptoms on the aforementioned outcome measures.

METHODS

The CRACoV study was a prospective single-center (University Hospital in Krakow, Krakow, Poland) observational study of clinical outcomes in symptomatic COVID-19 patients that required hospital treatment. We analysed data of persons aged ≥ 65 years. We assessed muscular parameters in accordance with EWGSOP2, frailty with the Rockwood Clinical Frailty Scale. We used the data of the initial and 3-month assessment. Demographic characteristics, past medical history, and baseline laboratory values were gathered as a part of routine care. We calculated sex and age, and additionally number-of-diseases adjusted odds ratios of mortality associated with studied factors and betas of the relation with these factors and the length of hospital stay.

RESULTS

The mean (standard deviation, SD) age of 163 participants (44.8% women, 14.8% died) was 71.8 (5.6) years, age range 65-89 years. One score greater SARC-F was associated with 34% (p = 0.003) greater risk of death, and 16.8 h longer hospital stay (p = 0.01). One score greater Rockwood was associated with 86% (p = 0.002) greater risk of death, but was unrelated to the length of hospital stay. Hand grip strength and dynapenia were unrelated to mortality, but dynapenia was related to longer hospital stay. Probable sarcopenia was associated with 441% (p = 0.01) greater risk of death.

CONCLUSIONS

In conclusion, the patient assessment with SARC-F and the Rockwood Clinical Frailty Scale may significantly improve the prediction of outcomes in older patients with COVID-19 and by extension might be of use in other acute severe infections. This, however, requires further research to confirm.

Prevalence of Sarcopenia in Patients With COVID-19: A Systematic Review and Meta-Analysis

BACKGROUND

It has been speculated that patients with sarcopenia are aggravated by the current novel coronavirus disease 2019 (COVID-19) epidemic. However, there is substantial uncertainty regarding the prevalence of sarcopenia in patients with COVID-19.

OBJECTIVES

The purpose of the study was to systematically evaluate the prevalence of sarcopenia in patients with COVID-19, including stratification by gender, study location, study population, study design, and diagnostic criteria.

DESIGN

This is the systematic literature review and meta-analysis.

METHODS

An electronic search was performed in MEDLINE/PubMed, Embase, Cochrane Library, and Web of Science and Scopus to identify observational studies reporting a prevalence estimate for sarcopenia in patients with COVID-19. Studies were reviewed in accordance with the Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) guidelines and a meta-analysis was performed. Risk of bias (RoB) was assessed using the Newcastle-Ottawa Scale (NOS) for cohort studies and Joanna Briggs Institute (JBI) manual for cross-sectional studies, and Stata 14.0 was used to perform meta-analyses.

RESULTS

A total of 4,639 studies were initially identified. After removing the duplicates and applying the selection criteria, we reviewed 151 full-text studies. A total of 21 studies, including 5,407 patients, were eligible for inclusion in this review finally. The prevalence of sarcopenia in patients with COVID-19 in individual studies varied from 0.8 to 90.2%. The pooled prevalence of sarcopenia in COVID-19 was 48.0% (95% confidence interval, CI: 30.8 to 65.1%, I 2 = 99.68%, p = 0.000). We did not find any significant differences in the prevalence estimates between gender specificity (OR = 1.34; 95% CI = 0.80-2.26; p = 0.001). By sex, the prevalence was 42.5% (95% CI: 31.7 to 53.4%) in men and 35.7% (95% CI: 24.2 to 47.2%) in women. The prevalence estimates significantly varied based on population settings and different diagnostic criteria of sarcopenia. ICU patients (69.7, 95% CI: 51.7 to 85.2%) were more likely to suffer from sarcopenia compared to other population settings.

CONCLUSION

To our knowledge, this is the first meta-analysis reporting on the prevalence of sarcopenia in patients with COVID-19. Sarcopenia is frequently observed in patients with COVID-19, with varying prevalence across population settings. This study would be useful for clinicians to prompt the increasing awareness of identifying sarcopenia and developing interventions at patients with COVID-19 with high risk of sarcopenia. Further prospective longitudinal studies to define the association of sarcopenia and its prognostic outcomes in COVID-19 survivors are urgently needed to propose the most appropriate treatment strategies during their admission and discharge.

SYSTEMATIC REVIEW REGISTRATION

[www.crd.york.ac.uk/prospero/], identifier [CRD42022300431].

Cytokines and Chemokines in Cancer Cachexia and Its Long-Term Impact on COVID-19

Cancer cachexia remains a serious public health concern worldwide, particularly as cancer rates rise. Treatment is endangered, and survival is reduced, because this illness is commonly misdiagnosed and undertreated. Although weight loss is the most evident sign of cachexia, there are other early metabolic and inflammatory changes that occur before the most obvious symptoms appear. Cachexia-related inflammation is induced by a combination of factors, one of which is the release of inflammation-promoting chemicals by the tumor. Today, more scientists are beginning to believe that the development of SARS-CoV-2 (COVID-19) related cachexia is similar to cancer-related cachexia. It is worth noting that patients infected with COVID-19 have a significant inflammatory response and can develop cachexia. These correlations provide feasible reasons for the variance in the occurrence and severity of cachexia in human malignancies, therefore, specific therapeutic options for these individuals must be addressed based on disease types. In this review, we highlighted the role of key chemokines, cytokines, and clinical management in relation to cancer cachexia and its long-term impact on COVID-19 patients.

Computed tomography-defined body composition as prognostic markers for unfavourable outcomes and in-hospital mortality in coronavirus disease 2019

BACKGROUND

Low skeletal muscle mass (LSMM) and visceral fat areas can be assessed by cross-sectional images. These parameters are associated with several clinically relevant factors in various disorders with predictive and prognostic implications. Our aim was to establish the effect of computed tomography (CT)-defined LSMM and fat areas on unfavourable outcomes and in-hospital mortality in coronavirus disease 2019 (COVID-19) patients based on a large patient sample.

METHODS

MEDLINE library, Cochrane, and Scopus databases were screened for the associations between CT-defined LSMM as well as fat areas and in-hospital mortality in COVID-19 patients up to September 2021. In total, six studies were suitable for the analysis and included into the present analysis.

RESULTS

The included studies comprised 1059 patients, 591 men (55.8%) and 468 women (44.2%), with a mean age of 60.1 years ranging from 48 to 66 years. The pooled prevalence of LSMM was 33.6%. The pooled odds ratio for the effect of LSMM on in-hospital mortality in univariate analysis was 5.84 [95% confidence interval (CI) 1.07-31.83]. It was 2.73 (95% CI 0.54-13.70) in multivariate analysis. The pooled odds ratio of high visceral fat area on unfavourable outcome in univariate analysis was 2.65 (95% CI 1.57-4.47).

CONCLUSIONS

Computed tomography-defined LSMM and high visceral fat area have a relevant association with in-hospital mortality in COVID-19 patients and should be included as relevant prognostic biomarkers into clinical routine.