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.

COVID-19-Related Lung Involvement at Different Time Intervals: Evaluation of Computed Tomography Images With Semiquantitative Scoring System and COVID-19 Reporting and Data System Scoring.

INTRODUCTION: This study aimed to evaluate the frequency of typical and atypical thoracic CT findings in patient groups diagnosed during different periods of the pandemic, examine disease severity using radiological scoring methods, and determine the relationship between atypical CT findings and disease severity. MATERIALS AND METHODS: One hundred fifty-one patients with positive reverse transcription polymerase chain reaction (RT-PCR) test and thoracic CT scan were included in the study. The patients were divided into two groups as group 1 (March to August 2020) diagnosed in the first six months of the pandemic and group 2 (September 2020 to February 2021) diagnosed in the second six months. CT images of the patients were analyzed for the frequency of typical and atypical findings. Evaluation was made in terms of disease suspicion and severity by scoring methods, and the relationship between atypical findings and disease severity was examined. RESULTS: There was no statistically significant difference between the frequency and distribution patterns of typical CT findings observed in both groups. The most common atypical finding in both groups was nodular lesions. Central distribution, one of the atypical findings, was not seen in group 1, whereas it was present in nine patients in group 2 (p=0.001). The mean CT severity score was higher in group 2, and there was a statistically significant difference between the mean CT scores of both groups (p<0.001). In addition, six (7.2%) patients in group 1 and 34 (50%) patients in group 2 had CT scores above the cut-off value (p<0.001). There was no statistically significant relationship between atypical findings and severity score. CONCLUSION: Other diseases and atypical findings that may accompany COVID-19 pneumonia may increase the rate of misdiagnosis. In the diagnosis of the disease, clinical signs and symptoms and radiological findings should be evaluated together, and it should be kept in mind that lung findings in thorax CT change over time.