key: cord-0904519-7u83721t
authors: Surov, Alexey; Kardas, Hakan; Besutti, Giulia; Pellegrini, Massimo; Ottone, Marta; Onur, Mehmet Ruhi; Atak, Firat; Erdemir, Ahmet Gurkan; Hocaoglu, Elif; Yıldız, Ömer; Inci, Ercan; Cingöz, Eda; Cingöz, Mehmet; Dursun, Memduh; Korkmaz, İnan; Orhan, Çağrı; Strobel, Alexandra; Wienke, Andreas; Pech, Maciej
title: Prognostic role of the pectoralis musculature in patients with COVID-19. A multicenter study
date: 2022-05-16
journal: Acad Radiol
DOI: 10.1016/j.acra.2022.05.003
sha: 6c2350ff8e1b02ef30dfcabb14a52e9306c9f955
doc_id: 904519
cord_uid: 7u83721t

PURPOSE: 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. METHODS: For this study, data from 6 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 (PMA), muscle density, muscle index (PMI) (pectoralis muscle area divided by the patient's body height square) as a ratio PMA divided by the patient's body height(2), 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 CI95% (0.91-0.95) p<0.001; pectoralis muscle density, HR= 0.94 CI95% (0.93-0.96) p<0.001; pectoralis muscle index, HR= 0.79 CI95%(0.75-0.85) p<0.001, pectoralis muscle gauge, HR= 0.995 CI95%(0.99-0.996) p<0.001. CONCLUSIONS: in COVID-19, survivors have larger areas and higher index, gauge and density of the pectoralis muscles in comparison to non-survivors. However, the analyzed muscle parameters cannot be used for prediction of disease courses.

Purpose: 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.

Methods: For this study, data from 6 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 (PMA), muscle density, muscle index (PMI) (pectoralis muscle area divided by the patient's body height square) as a ratio PMA divided by the patient's body height 2 , and muscle gauge as PMI x muscle density. 

The coronavirus disease 2019 (COVID-19) pandemic represents a great problem for the global health. The clinical course of COVID-19 is very variable. In fact, although it has been identified that most patients had a relatively mild course, some patients still had a rapid progression with fatal outcome (1, 2) . However, some patients had a rapid progression of disease with fatal outcome (1, 2) . Therefore, prediction of unfavorable outcomes of COVID-19 is essential. Already established prognostic factors are age and sex (3, 4) . Comorbidities, such as dementia, heart failure and peripheral vascular diseases are also predictors of an unfavourable course of the disease (3, 4) .

Computed tomography (CT) is the imaging modality of choice in COVID-19, especially for detection of pulmonary consolidations (5) (6) (7) . Typical imaging findings in COVID-19 are bilateral, peripheral dominant ground-glass opacities with lower lobe and posterior predilection (5-7).

Also extrapulmonary findings play an important role in COVID-19 (8) . It has been shown that pleural effusion, pericardial effusion and mediastinal lymphadenopathy can be used as predictors of severe course of COVID-19 (6, 8) . In fact, pleural effusion and coronary calcifications are strong predictors of mortality in COVID-19, odds ratio (OR) = 4.6 (95% CI 2.97-7.12), p<0.00001, and OR = 2.68 (95% CI 1.78-4.04), p<0.00001, respectively (8) .

unfavourable courses of COVID-19 (9) .

The purpose of the present multi-center study was to evaluate the impact of LSMM in COVID-19 patients on relevant outcomes like 30-day mortality, need for intubation and need for intensive care.

This retrospective study was approved by our institutional review board (Medical In the centers, the data were acquired retrospectively. Inclusion criteria were as follows:

-diagnosis of COVID-19 confirmed by PCR;

-available thoracic CT images without intravenous administration of contrast medium; -available data regarding the following clinical outcomes: 30 day mortality, need for mechanical ventilation, and admission on an intensive care unit.

Exclusion criteria were as follows:

-cases with missing data regarding the above-mentioned outcomes;

-CT images after intravenous application of contrast medium;

-missing confirmation of COVID-19 infection by PCR.

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 on different clinical CT scanners or on each center's CT units.

In every case, the first CT scan of patients after hospital admission was used. In all 6 centers, measurements were performed by experienced radiologists blinded to the clinical course of patients. The measurements were performed on axial images at the T4 level in the soft tissue window on dedicated workstations. A polygonal region of interest (ROI) was drawn along the contours of the pectoralis major and minor muscles on both sides (Figures 1 and 2 ). Pectoralis muscle area (PMA) was defined as a sum of the bilateral areas of the pectoralis major and minor muscles.

Furthermore, pectoralis muscle density was measured within the ROIs. Pectoralis muscle index (PMI) was calculated as a ratio PMA divided by the patient's body height square. Additionally, skeletal muscle gauge (SMG) was calculated by multiplying PMI with mean muscle density as reported previously (10) .

Statistical analysis was performed using the SPSS package (IBM SPSS Statistics for Windows, version 225.0, Armonk, NY, USA: IBM corporation). Continuous variables were described by mean value, median and standard deviation. Categorical variables were given as relative frequencies. The comparison of pectoralis muscle parameters was performed by Mann-Whitney-U tests and the p-values were adjusted for multiple testing (Bonferroni correction). To assess the impact of the pectoralis musculature on clinical outcomes, uni-and multivariable logistic regression models were used to assess the impact of pectoralis muscle on clinical outcomes. Odds ratios are presented together with 95 % confidence intervals (95 % CI). In all instances, P values < 0.05 were taken to indicate statistical significance.

The estimated values (Mean±SD) of the pectoralis muscles were as follows:

pectoralis muscle area, 28 Regression analysis identified that all pectoralis muscle parameters were associated with unfavorable courses (Table 2) . Also, all pectoralis muscle parameters were associated with unfavorable courses after adjusting for age and sex (Table 3) .

The present study showed at the first time the prognostic role of the pectoralis musculature in COVID-19 based on a large sample in a multicenter setting.

According to the literature, parameters of body composition measured on cross sectional imaging techniques like CT play an important clinical role and are strong predictors for several relevant outcomes in different disorders (11) (12) (13) (14) (15) . Importantly, muscle measurement is a by-product of cross-sectional imaging and does not need additional investigations. So far, in patients with abdominal trauma, low skeletal muscle mass on CT is significantly associated with longer hospitalization, longer intensive care length of stay, higher cost, higher frequency of mechanical ventilation, longer duration of vasopressor use, and higher incidence of massive transfusion and transfusion-related complications (11 Associations between LSMM and unfavorable courses of COVID-19 are multifactorial. The presence of LSMM may reflect a state of malnutrition and/or catabolism. It is also known that anemia and hypoalbuminemia are associated with low muscle density (26) . Furthermore, there are significant interactions between the skeletal musculature and immune system. So far, skeletal muscles release numerous myokines with autocrine, paracrine, and immune effects (27) . For instance, interleukin (IL)-15 is a myokine that stimulates proliferation and activation of natural killer cells and CD8+ T lymphocytes (28) . These cells play an essential role in antiviral immune defense (28) . Furthermore, IL 15 induces activation and phagocytosis of neutrophils (29) . IL 15 also delays human neutrophil apoptosis (30) .

Presumably, in patients with reduced muscle quantity and/or quality a less number of myokines is produced.

Notably, different measurements and values for estimation of LSMM in patients with COVID-19 are used. According to the literature, SMI estimation on CT at the level of the third lumbar vertebra (L3) represents a standardized method to quantify the skeletal musculature (31) . In patients with COVID-19, often only thoracic CT investigations for the analysis of pulmonary damage are performed. Therefore, the 13 estimation of the standardized SMI values at the L3 level is impossible. Hence, in the previous studies, other vertebral levels for the quantification of the skeletal musculature are proposed, such as thoracic vertebra 5 (32), thoracic vertebra 12 (22, 24, 33) , or lumbar vertebra 1 (34) .The pectoralis muscles as surrogate marker is also used (35, 36) .

The present study has several limitations. Firstly, it is based on retrospective cohorts.

Secondly, only patients, who underwent CT investigations without intravenous administration of contrast medium, were included. Thirdly, we did not analyze virus subtypes in our patients. It is well known that several viruses provoke different disease severity. However, to date, it is the largest multicenter cohort and our results represent evidence based data regarding associations between skeletal musculature and clinical outcomes in COVID-19.

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

None. 

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