The global pandemic of COVID-19 poses a huge threat to the health and lives of people all over the world, and brings unprecedented pressure to the medical system. We need to establish a practical method to improve the efficiency of treatment and optimize the allocation of medical resources. Due to the influx of a large number of patients into the hospital and the running of medical resources, blood routine test became the only possible check while COVID-19 patients first go to a fever clinic in a community hospital. This study aims to establish an efficient method to identify key indicators from initial blood routine test results for COVID-19 severity prediction. We determined that age is a key indicator for severity predicting of COVID-19, with an accuracy of 0.77 and an AUC of 0.92. In order to improve the accuracy of prediction, we proposed a Multi Criteria Decision Making (MCDM) algorithm, which combines the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) and Naïve Bayes (NB) classifier, to further select effective indicators from patients’ initial blood test results. The MCDM algorithm selected 3 dominant feature subsets: {Age, WBC, LYMC, NEUT} with a selection rate of 44%, {Age, NEUT, LYMC} with a selection rate of 38%, and {Age, WBC, LYMC} with a selection rate of 9%. Using these feature subsets, the optimized prediction model could achieve an accuracy of 0.82 and an AUC of 0.93. These results indicated that Age, WBC, LYMC, NEUT were the key factors for COVID-19 severity prediction. Using age and the indicators selected by the MCDM algorithm from initial blood routine test results can effectively predict the severity of COVID-19. Our research could not only help medical workers identify patients with severe COVID-19 at an early stage, but also help doctors understand the pathogenesis of COVID-19 through key indicators.

The -173 G/C polymorphism in the macrophage migration inhibitory factor (MIF) gene has been implicated in susceptibility to inflammatory bowel disease (IBD), but the results are inconclusive. The present meta-analysis aimed to investigate the overall association between the -173 G/C polymorphism and IBD risk. We searched in Pubmed, and Embase for studies evaluating the association between the -173G/C gene polymorphism and IBD risk. Data were extracted and statistical analysis was performed using Revman 5.1 and STATA 12.0 software. A total of seven publications involving 4729 subjects (2282 IBD cases and 2447 controls) were included in this meta-analysis. Combined analysis revealed a clear association between this polymorphism and IBD susceptibility (OR = 1.48, 95% CI: 1.10–2.00, p = 0.009 for CC vs. CG + GG). Subgroup analysis by ethnicity showed that the IBD risk associated with the -173G/C gene polymorphism was significantly elevated among Asians (OR = 1.79, 95% CI: 1.08–2.96, p = 0.02), but not among Caucasians. Subgroup analysis by disease suggested that the -173G/C gene polymorphism is a risk factor for ulcerative colitis (OR = 1.62, 95% CI: 1.10–2.37, p = 0.01), but that it was not associated with Crohn’s disease. This meta-analysis suggests that the -173 G/C polymorphism in the macrophage MIF gene contributes to IBD susceptibility, specifically in Asian populations. Further studies are needed to validate these findings.

BACKGROUND: This study aimed to determine the correlation between human-immunodeficiency-virus (HIV) infection and stroke, as well as to estimate the global, regional, and national burden of HIV-associated stroke. METHODS: A registered meta-analysis was performed by searching PubMed, Embase, and Web of Science for relevant literature up to October 31, 2022. The pooled relative risk of stroke in HIV-infected people was calculated using a random-effects model. HIV prevalence and disability-adjusted life years (DALYs) datasets were obtained from the Joint United Nations Program on HIV and AIDS, and the Global Health Data Exchange, respectively. The population attributable fraction was estimated and delivered to calculate the HIV-associated DALYs of stroke from 1990 to 2019, at the global, regional, and national levels. Pearson correlation analysis were conducted to assess the correlation between the age-standardized rate or estimated annual percentage changes and the sociodemographic index. RESULTS: Out of 10 080 identified studies, 11 were included in this meta-analysis. Compared with individuals without HIV-infection, the pooled relative risk of stroke in HIV-infected individuals was 1.40 (95% CI, 1.18–1.65). From 1990 to 2019, the global population attributable fraction of HIV-associated stroke increased almost 3-fold, while the HIV-associated DALYs increased from 18 595 (95% CI, 7485–31 196) in 1990 to 60 684 (95% CI, 24 281–101 894) in 2019. Meanwhile, HIV-associated DALYs varied by region, with Eastern and Southern Africa having the highest value of 126 160 in 2019. Moreover, countries with middle social development index were shouldering the highest increase trend of the HIV-associated DALYs age-standardized rates. CONCLUSIONS: HIV-infected individuals face a significantly higher risk of stroke, and the global burden of HIV-associated stroke has increased over the past 3 decades, showing regional variations. Eastern and Southern Africa bear the highest burden, while Eastern Europe and Central Asia have seen significant growth. Health care providers, researchers, and decision-makers should give increased attention to stroke prevention and management in HIV-endemic areas. REGISTRATION: URL: https://www.clinicaltrials.gov ; Unique identifier: CRD42022367450.

Background. The association between the lymphotoxin‐α (LTA) A252G polymorphism and sepsis risk has been extensively studied, but the results have been controversial. This study is aimed at investigating the overall association between the LTA A252G polymorphism and the risk of sepsis/septic shock and sepsis‐related mortality. Methods. We searched the PubMed and EMBASE databases to identify studies that investigated the association between the LTA A252G polymorphism and risks of sepsis, septic shock, and mortality. The relevant data were extracted, and statistical analyses were performed using the Revman 5.0 and STATA 12 software. Results. A total of 32 publications were included in the meta‐analysis. The results demonstrated that the LTA A252G polymorphism showed no significant association with sepsis risk (GG+GA vs. AA: OR = 0.92, 95%CI = 0.79–1.07, p = 0.27) or with sepsis shock risk (GG+GA vs. AA: OR = 1.01, 95%CI = 0.84–1.22, p = 0.91). However, in the subgroup analyzed by ethnicity, the LTA A252G polymorphism significantly decreased sepsis risk in the Asian population for the recessive model [GG vs. GA+AA: OR = 0.82, 95%CI = 0.68–0.99, p = 0.04] but not in the Caucasian population. Moreover, comparisons between sepsis patients who survived and those who did not suggested that the LTA A252G polymorphism decreases the risk of mortality [GG+GA vs. AA: OR = 0.57, 95%CI = 0.41–0.80, p < 0.01]. Conclusion. Our results suggested that the A252G polymorphism in the LTA gene decreased the risk of sepsis in Asians and may reduce mortality in septic individuals.

Clear cell renal cell carcinoma (ccRCC) is a prevalent tumor in the urinary system, presenting a poor prognosis yet being accompanied by a high degree of immune infiltration. Understanding the mechanisms underlying this abnormal infiltration and identifying prognostic biomarkers in this regard is crucial for improving therapeutic outcomes. The expression of GPD1L in ccRCC was analyzed using a common database (TCGA). The expression of GPD1L in ccRCC cell lines and tissue samples was verified by western blotting, real time qPCR and immunohistochemistry. The predictive value of GPD1L was evaluated by survival analysis, ROC curve and Cox regression analysis. We used GO, KEGG and gene set enrichment analysis (GSEA) to verify each other. Then the single cell sequencing dataset (GEO) was further analyzed and verified, and the functional phenotype of GPD1L in ccRCC was explored by functional experiments. In addition, the correlation between the expression level of GPD1L and drug resistance of AKT-mTOR pathway was analyzed based on Genomics of Drug Sensitivity in Cancer database (GDSC). We identified glycerol-3-phosphate dehydrogenase 1-like (GPD1L) as a tumor suppressor gene in ccRCC, and downregulation of GPD1L may facilitate the adaptive survival of tumor cells via enhanced regulatory T cells (Tregs) infiltration and lipid metabolism reprogramming in ccRCC. Our results suggest that there is a significantly diminished GPD1L in ccRCC patients with poorer survival probability. Mechanically, a significant negative correlation between GPD1L expression and Tregs infiltration, and GPD1L-related metabolic analysis reflected the correlation between Tregs and lipid metabolism. In addition, GPD1L expression levels also influence the malignant phenotype of ccRCC and the drug resistance to AKT and mTOR targeted therapy. Taken together, our results supported GPD1L could be a valuable biomarker for predicting and intervening in ccRCC progression. These insights could shed light on the complex interplay between tumor cell adaptive survival and Treg infiltration, which reflected that the comprehensive and systemic role of GPD1L in ccRCC.