ABSTRACT
Objective:To determine whether the early stage platelet count can predict the outcome of peritoneal dialysis-associated peritonitis (PDAP).Methods:A retrospective cohort study was conducted by selecting PDAP patients who were hospitalized in the First People's Hospital of Foshan from January 2012 to January 2019. According to the final treatment outcome, the patients were divided into cured group and withdrawn group. The withdrawn group included patients who transferred to hemodialysis or died. Basic data on demography, blood routine examination, peritoneal fluid, biochemical indicators were compared between the two groups. Logistic regression analysis was used to analyze the withdrawn risk factors of PDAP.Results:There were 180 patients included in the study, including 112 cases in the cured group and 68 cases in the withdrawn group. Compared with the cured group, there were older age [(53.38±14.17) years old vs (48.41±13.04) years old, t=2.407, P=0.017], longer age of dialysis [(49.20±26.05) months vs (30.36±32.97) months, t=4.034, P<0.001], longer hospital stay [(23.88±11.50) d vs (17.80±3.95) d, t=5.133, P<0.001] and higher platelet count [(285.55±107.23)×10 9/L vs (234.90±74.03)×10 9/L, t=3.450, P=0.001], lower serum albumin [(31.72±7.47) g/L vs (35.40±4.93) g/L, t=-3.972, P<0.001] in the withdrawn group. Multivariate logistic regression analysis showed that longer dialysis age ( OR=1.012, 95% CI 1.007-1.024, P=0.015) and higher platelet count ( OR=1.013, 95% CI 1.004-1.026, P=0.008) were independent risk factors, and higher serum albumin ( OR=0.941, 95% CI 0.896-0.988, P=0.005) was an independent protective factor of withdrawal from peritoneal dialysis in PDAP patients. Conclusions:The long dialysis age, early high platelet count are independent risk factors and high serum albumin level is an independent protective factor for withdrawal from peritoneal dialysis in PDAP patients.
ABSTRACT
Objective@#To analyze non-alcoholic steatohepatitis (NASH)-related differentially expressed genes (DEGs) by bioinformatics methods to find key pathways and potential therapeutic targets for NASH.@*Methods@#GSE61260 chip was downloaded from the public microarray database and liver biopsy samples from 24 NASH cases and 38 healthy controls were included. The Limma software package in R language was used to screen DEGs under the condition of difference multiple > 1.5 and adj. P < 0.05. The clusterProfiler software package was used for GO analysis and KEGG analysis. The STRING online database was used for protein-protein interaction analysis, and the L1000 and DrugBank databases were used for drug prediction.@*Results@#Compared with healthy control group, 857 DEGs were screened out in NASH group including 167 up-regulated genes and 690 down-regulated genes. GO analysis showed that DEGs were mainly involved in inflammation and cholesterol metabolism. KEGG analysis showed that DEGs were mainly enriched in PPAR, non-alcoholic fatty liver disease, oxidative phosphorylation and other signaling pathways. Among them, eight genes of ACSL4, CYP7A1, FABP4, FABP5, lipoprotein lipase, ME1, OLR1 and PLIN1 were enriched in PPAR signaling pathway, and 165 interaction nodes were formed with 47 DEGs-encoded proteins. Lipoprotein lipase interacted with 21 DEGs, and its up-regulated expression had improved lipid metabolism, insulin resistance and anti-inflammatory effects. Four drugs (gemfibrozil, bezafibrate, omega-3 carboxylic acid and glycyrrhizic acid) were screened by L1000 and DrugBank to activate lipoprotein lipase. Presently, these four drugs are clinically used to treat hypertriglyceridemia or to improve inflammation. In this regard, we speculated that the pharmacological effects of these four drugs had improved NASH by activating lipoprotein lipase to promote liver lipid metabolism and alleviate inflammation.@*Conclusion@#PPAR signaling pathway is closely associated to the occurrence and development of NASH, and thereby lipoprotein lipase agonist is a new attempt to treat NASH.