Effect of alprostadil in the treatment of intensive care unit patients with acute renal injury

BACKGROUND Acute kidney injury(AKI)is a sudden or rapid decline in the filtration function of the kidneys which is marked by increased serum creatinine or blood urea nitrogen.AIM To examine the value of alprostadil-assisted continuous venous-venous hemofiltration(CVVH)in the treatment of severe AKI in severely ill patients.METHODS This was a retrospective study and the inclusion criteria were as follows:(1)Age of patients(≥18 years);(2)Admission to intensive care unit due to non-renal primary disease,APACHE II score(≥18 points);(3)The diagnostic criteria of AKI guidelines were formulated with reference to the Global Organization for the Improvement of Prognosis in Kidney Diseases,with AKI grades of II-III;(4)All patients were treated with CVVH;and(5)Complete basic data were obtained for all patients.RESULTS The clinical effect of alprostadil administered in the treatment group was better than that observed in the control group(P<0.05).The urine output of patients in the alprostadil group returned to normal time(9.1±2.0 d)and was lower than that in the control group(10.6±2.5 d),the difference was statistically significant(P<0.05);adverse reactions occurred in the alprostadil group compared with the control group,but the difference was not statistically significant(P>0.05).CONCLUSION Alprostadil-assisted CVVH in the treatment of severely ill patients with AKI can effectively improve the renal resistance index and partial pressure of urine oxygen,and has a positive effect on improving renal function.

Evaluation of 10 Different Pipelines for Bacterial Single-Nucleotide Variant Detection

Bacterial genome sequencing is a powerful technique for studying the genetic diversity and evolution ofmicrobial populations.However,the detection of genomic variants from sequencing data is challenging due to the presence of contamination,sequencing errors and multiple strains within the same species.Several bioinformatics tools have been developed to address these issues,but their performance and accuracy have not been systematically evaluated.In this study,we compared 10 variant detection pipelines using 18 simulated and 17 real datasets of high-throughput sequences froma bundle of representative bacteria.We assessed the sensitivity of each pipeline under different conditions of coverage,simulation and strain diversity.We also demonstrated the application of these tools to identify consistentmutations in a 30-time repeated sequencing dataset of Staphylococcus hominis.We found that HaplotypeCaller,but not Mutect2,from the GATK tool set showed the best performance in terms of accuracy and robustness.CFSAN and Snippy performed not as well in several simulated and real sequencing datasets.Our results provided a comprehensive benchmark and guidance for choosing the optimal variant detection pipeline for high-throughput bacterial genome sequencing data.