Background Coronavirus disease 2019 (COVID-19) is an emerging infectious disease that first appeared in Wuhan, China, and quickly spread throughout the world. We aimed to understand the relationship between diabetes mellitus and the prognosis of COVID-19. Methods Demographic, clinical, laboratory, radiologic, treatments, complications, and clinical outcomes data were extracted from electronic medical records and compared between diabetes (n = 84) and nondiabetes (n = 500) groups. Kaplan-Meier method and multivariate Cox analysis were applied to determine the risk factors for the prognosis of COVID-19. Results Compared with nondiabetic patients, diabetic patients had higher levels of neutrophils ( P = .014), C-reactive protein ( P = .008), procalcitonin ( P < .01), and D-dimer ( P = .033), and lower levels of lymphocytes ( P = .032) and albumin ( P = .035). Furthermore, diabetic patients had a significantly higher incidence of bilateral pneumonia (86.9%, P = .020). In terms of complications and clinical outcomes, the incidence of respiratory failure (36.9% vs 24.2%, P = .022), acute cardiac injury (47.4% vs 21.2%, P < .01), and death (20.2% vs 8.0%, P = .001) in the diabetes group was significantly higher than that in the nondiabetes group. Kaplan-Meier survival curve showed that COVID-19 patients with diabetes had a shorter overall survival time. Multivariate Cox analysis indicated that diabetes (hazard ratio 2.180, P = .031) was an independent risk factor for COVID-19 prognosis. In subgroup analysis, we divided diabetic patients into insulin-required and non-insulin-required groups according to whether they needed insulin, and found that diabetic patients requiring insulin may have a higher risk of disease progression and worse prognosis after the infection of severe acute respiratory syndrome coronavirus 2. Conclusions Diabetes is an independent risk factor for the prognosis of COVID-19. More attention should be paid to the prevention and treatment for diabetic patients, especially those who require insulin therapy.
Background. Secreted protein acidic and rich in cysteine-like 1 (SPARCL1) plays an important role in tumor pathogenesis. We aim to evaluate the clinical significance and potential biological roles of SPARCL1 in colorectal cancer (CRC). Methods. Datasets from the Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases were downloaded to evaluate the expression levels of SPARCL1 in CRC. Receiver operating characteristic (ROC) curve was constructed to evaluate the diagnostic value of SPARCL1. Then, comprehensive database search was conducted for published clinical studies to explore clinical significance of SPARCL1. In addition, coexpression genes of SPARCL1 were identified through the cBioPortal database and enrichment analysis of SPARCL1 and its coexpression genes were performed by the “clusterProfiler” R package. Finally, the correlations between SPARCL1 and tumor microenvironment scores, tumor-infiltrating immune cells in CRC were determined by “ESTIMATE” and “GSVA” R packages. Results. SPARCL1 was significantly downregulated in CRC tissues, and SPARCL1 showed high accuracy for diagnosis of primary CRC in both GEO and TCGA datasets. Pooled results from published clinical studies showed SPARCL1 expression was associated with differentiation ( OR = 1.89 , 95% CI: 1.38-2.59), tumor stage ( OR = 0.47 , 95% CI: 0.29-0.77), distant metastasis ( OR = 0.53 , 95% CI: 0.33-0.84), and overall survival ( HR = 0.56 , 95% CI: 0.43-0.74). SPARCL1 and its top 300 coexpression genes were involved in several KEGG pathways, such as focal adhesion, cell adhesion molecules, PI3K-Akt signaling pathway, cGMP-PKG signaling pathway, and ECM-receptor interaction. Besides, the SPARCL1 expression was significantly correlated with stromal score, immune score, ESTIMATE score, and diverse immune cells. Conclusion. SPARCL1 significantly correlated with clinicopathological features and tumor microenvironment in CRC.
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