Clinical importance of thoracal lymphadenopathy in COVID-19.

BACKGROUND: Thoracal lymphadenopathy may predict prognosis in patients with coronavirus disease 2019 (COVID-19), albeit the reported data is inconclusive. The aim of the present analysis was to analyze the affected lymph node stations and the cumulative lymph node size derived from computed tomography (CT) for prediction of 30-day mortality in patients with COVID-19. METHODS: The clinical database was retrospectively screened for patients with COVID-19 between 2020 and 2022. Overall, 177 patients (63 female, 35.6%) were included into the analysis. Thoracal lymphadenopathy was defined by short axis diameter above 10 mm. Cumulative lymph node size of the largest lymph nodes was calculated and the amount of affected lymph node stations was quantified. RESULTS: Overall, 53 patients (29.9%) died within the 30-day observation period. 108 patients (61.0%) were admitted to the ICU and 91 patients needed to be intubated (51.4%). Overall, there were 130 patients with lymphadenopathy (73.4%). The mean number of affected lymph node levels were higher in non-survivors compared to survivors (mean, 4.0 vs 2.2, p < 0.001). The cumulative size was also higher in non-survivors compared to survivors (mean 55.9 mm versus 44.1 mm, p = 0.006). Presence of lymphadenopathy was associated with 30-day mortality in a multivariable analysis, OR = 2.99 (95% CI 1.20 - 7.43), p = 0.02. CONCLUSIONS: Thoracal lymphadenopathy comprising cumulative size and affected levels derived from CT images is associated with 30-day mortality in patients with COVID-19. COVID-19 patients presenting with thoracic lymphadenopathy should be considered as a risk group.

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.

Extrapulmonary CT Findings Predict In-Hospital Mortality in COVID-19. A Systematic Review and Meta-Analysis.

RATIONALE AND OBJECTIVES: Several prognostic factors have been identified for COVID-19 disease. Our aim was to elucidate the influence of non-pulmonary findings of thoracic computed tomography (CT) on unfavorable outcomes and in-hospital mortality in COVID-19 patients based on a large patient sample. MATERIALS AND METHODS: MEDLINE library, Cochrane and SCOPUS databases were screened for the associations between CT-defined features and mortality in COVID-19 patients up to June 2021. In total, 22 studies were suitable for the analysis, and included into the present analysis. Overall, data regarding 4 extrapulmonary findings could be pooled: pleural effusion, pericardial effusion, mediastinal lymphadenopathy, and coronary calcification. RESULTS: The included studies comprised 7859 patients. The pooled odds ratios for the effect of the identified extrapulmonary findings on in-hospital mortality are as follows: pleural effusion, 4.60 (95% CI 2.97-7.12); pericardial effusion, 1.29 (95% CI 0.83-1.98); coronary calcification, 2.68 (95% CI 1.78-4.04); mediastinal lymphadenopathy, 2.02 (95% CI 1.18-3.45). CONCLUSION: Pleural effusion, mediastinal lymphadenopathy and coronary calcification have a relevant association with in-hospital mortality in COVID-19 patients and should be included as prognostic biomarker into clinical routine.