Background: Coronavirus disease 2019 (COVID-19) has led to severe pneumonia and mortality worldwide, however, clinical outcomes in end-stage renal disease patients remain unclear. This study evaluates the prognostic value of chest computed tomography (CT) findings in predicting COVID-19-related outcomes in prevalent hemodialysis patients.
Methods: We retrospectively analyzed 326 prevalent hemodialysis patients diagnosed with COVID-19 who underwent chest CT scans. Characteristics assessed included pleural effusion, lung involvement volume, nodular consolidation, patchy infiltration, and ground-glass opacity. Artificial intelligence (AI)-assisted CT analysis quantified lung involvement. The primary endpoint was in-hospital mortality. Clinical data were collected, and logistic regression analysis assessed the association between CT findings and mortality.
Results: The mean age of the patients was 66.7 ± 12.6 years, 61.0% were male, and 58.6% were diabetic. Chest CT showed that 18.1% had lung involvement >10%, 32.5% had pleural effusion, 68.7% had nodular consolidation, 57.1% had patchy infiltration, and 58.0% had ground-glass opacity. Seventy patients (21.5%) died. Multivariate logistic regression analysis identified lung involvement >2.7% (odds ratio [OR], 16.70; 95% confidence interval [CI], 4.35-65.63), pleural effusion (OR, 3.28; 95% CI, 1.15-9.35), nodular consolidation (OR, 4.08; 95% CI, 1.12-14.82), and patchy infiltration (OR, 3.75; 95% CI, 1.17-12.03) as significant mortality risk factors.
Conclusion: Chest CT findings, including lung involvement >2.7% and the presence of pleural effusion, nodular consolidation, and patchy infiltrates, significantly indicated mortality in COVID-19 pneumonia among prevalent hemodialysis patients. AI-assisted CT analysis proved useful in assessing lung involvement extent, showing that even minimal lung involvement can be associated with increased mortality.
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http://dx.doi.org/10.23876/j.krcp.24.079 | DOI Listing |
Int J Surg
January 2025
Aging Research Center, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden.
Introduction: Lung function has been associated with cognitive decline and dementia, but the extent to which lung function impacts brain structural changes remains unclear. We aimed to investigate the association of lung function with structural macro- and micro-brain changes across mid- and late-life.
Methods: The study included a total of 37 164 neurologic disorder-free participants aged 40-70 years from the UK Biobank, who underwent brain MRI scans 9 years after baseline.
Cell Mol Life Sci
January 2025
Department of Clinical Laboratory, Harbin Medical University Cancer Hospital, 150 Haping Road, Harbin, 150081, China.
Non-small cell lung cancer (NSCLC) has emerged as one of the most prevalent malignancies worldwide. N6-methyladenosine (mA) methylation, a pervasive epigenetic modification in long noncoding RNAs (lncRNAs), plays a crucial role in NSCLC progression. Here, we report that mA modification and the expression of the lncRNA stem cell inhibitory RNA transcript (SCIRT) was significantly upregulated in NSCLC tissues and cells.
View Article and Find Full Text PDFJ Virol
January 2025
Department of Laboratory Medicine, Clinical Center, National Institutes of Health, Bethesda, Maryland, USA.
Unlabelled: APOBEC3 proteins (A3s) play an important role in host innate immunity against viruses and DNA mutations in cancer. A3s-induced mutations in both viral and human DNA genomes vary significantly from non-lethal mutations in viruses to localized hypermutations, such as kataegis in cancer. How A3s are regulated remains largely unknown.
View Article and Find Full Text PDFJ Vis Exp
January 2025
Fever Outpatient Clinic, Dongzhimen Hospital, Affiliated to Beijing University of Chinese Medicine;
Non-invasive assessment of pulmonary nodule malignancy remains a critical challenge in lung cancer diagnosis. Traditional methods often lack precision in differentiating benign from malignant nodules, particularly in the early stages. This study introduces an approach using multifractal spectrum analysis to quantitatively evaluate pulmonary nodule characteristics.
View Article and Find Full Text PDFUnlabelled: Immune escape is a critical hallmark of cancer progression and underlies resistance to multiple immunotherapies. However, it remains unclear when the genetic events associated with immune escape occur during cancer development. Here, we integrate functional genomics studies of immunomodulatory genes with a tumor evolution reconstruction approach to infer the evolution of immune escape across 38 cancer types from the Pan-Cancer Analysis of Whole Genomes dataset.
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