87 for both). SOFA and CLIF-SOFA also performed well when determined at the time of ICU admission (AUROC 0.86 and 0.85, respectively). Etiology of liver disease or AKI did not influence prognosis. CONCLUSION Critically ill patients with ACLF and AKI requiring CRRT have poor hospital survival, even with provision of extracorporeal support therapy. SOFA and CLIF-SOFA are good prognostic tools of mortality in this susceptible population.
.AIMS We aim to describe the clinical and histological findings in patients with the finding of any tubular oxalate deposits in kidney biopsy specimens. BACKGROUND The prevalence, manifestation, and outcome of secondary oxalate nephropathy have not been extensively studied. MATERIALS AND METHODS In this retrospective cohort study, we analyzed the clinical and histological findings in all patients with the finding of any tubular oxalate deposits in kidney biopsy specimens between July 1, 2017, and December 31, 2018, at Northwell Health Pathology Department (Manhasset, NY, USA). RESULTS The prevalence of oxalate deposition on a kidney biopsy was 4.07% (25/615), and in 88% of cases was a major finding. Prior to biopsy, oxalate was anticipated in only 1 case. The etiology of oxalosis was clarified retrospectively in 14 cases, most commonly due to GI surgery (n = 10) and increased oxalate intake (n = 4). In 11 cases, etiology remained unknown, although at least 3 cases were exposed to antibiotics associated with secondary oxalosis. There was no significant clinical/pathological or survival difference between known vs. unknown cause groups. The overall 3-month renal survival rate was 76.0 ± 8.5%. click here Multivariate Cox regression showed that creatinine at the time of biopsy (HR 1.79, 95% CI 0.71 - 4.51), background histological chronicity change (HR 1.82, 95% CI 0.70 - 4.72) and oxalate density (HR 2.27, 95% CI 0.49 - 10.55) are associated with end-stage kidney disease. CONCLUSION Oxalate deposition is common but rarely anticipated biopsy finding. Nephrologists need to consider surgical history and other secondary causes of oxalosis as causes of acute kidney injury and chronic kidney disease.
.BACKGROUND Serum creatinine has been solely used in clinical practice to identify chronic kidney disease (CKD) staging in the elderly population. Serum cystatin C is believed to more accurately define the CKD staging and is also ratified as an endogenous biomarker by Kidney Disease Improving Global Outcomes (KDIGO) guidelines. MATERIAL AND METHODS A total of 300 elderly Malay participants (age ≥ 65 years) with CKD, attending the Hospital University Sains Malaysia were included in the study. Demographic data and history were also recorded. Serum creatinine was assayed by Chemistry Analyzer Model Architect-C8000 (Jaffe method). While serum cystatin C was examined by Human cystatin C ELISA kit (Sigma-Aldrich) using Thermo Scientific Varioskan Flash ELISA reader. RESULTS Out of 300 study participants, 169 (56.3%) were females. Mean age of patients was 67.6 ± 6.7 years. 64 male (64.6%) and 35 female (35.4%) patients were between 70 and 79 years. When estimated by MDRD equation, the prevalence of CKD stage 3 (defined as eGFR = 30 - 59 mL/min/1.73m2) was 27.7%, while based on CKD-EPIcr, CKD-EPIcys, and CKD-EPIcr-cys equations, it was 28%, 36.3%, and 36.3%, respectively. The prevalence of CKD stage 4 (defined as eGFR = 15 - 29 mL/min/1.73m2) when estimated by MDRD was 37.6%, whereas based on CKD-EPIcr, CKD-EPIcys, and CKD-EPIcr-cys equations, it was 36.3%, 46.4%, and 46.4%, respectively. CKD stage 5 (defined as eGFR less then 15 mL/min/1.73m2) when estimated by the MDRD equation was 34.7%. While based on CKD-EPIcr, CKD-EPIcys, and CKD-EPIcr-cys equations, the prevalence of CKD stage 5 was 35.7%, 17.3%, and 17.3%, respectively. CONCLUSION The staging of CKD is different between the creatinine- and cystatin C-based equations. Creatinine-based equations classify patients as having CKD stage 5 twice as often as cystatin C-based equations.
.An orange-pigmented, short-rod-shaped, aerobic and non-motile bacterial strain, designated TK008T, was isolated from the shallow-sea hydrothermal systems off Kueishantao Island in Taiwan, China, and it was studied by using a polyphasic taxonomic approach. Cells were Gram-stain-negative, and catalase- and oxidase-positive. Strain TK008T exhibited highest 16S rRNA gene sequence similarity of 97.1 % to Paracoccus pacificus F14T. The phylogenetic trees based on 16S rRNA gene sequences showed that strain TK008T was a member of the genus Paracoccus. Digital DNA-DNA hybridization values between strain TK008T and two closely related species (Paracoccus zhejiangensis and Paracoccus tegillarcae) were 20.6 and 20.9 %. The average nucleotide identity values of strain TK008T compared with P. zhejiangensis and P. tegillarcae were 75.2 and 74.6 % respectively. The major isoprenoid quinone was ubiquinone-10. The predominant fatty acids (>10 %) were summed feature 8 (C18  1ω6c and/or C18  1ω7c). The polar lipids were diphosphatidylglycerol, phosphatidylglycerol, phosphatidylethanolamine, three unidentified phospholipids, two unidentified lipids and an unidentified glycolipid. The DNA G+C content of strain TK008T from genomic sequence data was 62.54 mol%. On the basis of polyphasic analysis, strain TK008T represents a novel species, for which the name Paracoccus aurantiacus sp. nov. is proposed. The type strain is TK008T (=CGMCC 1.13898T=JCM 33630T).A large European multi-country Salmonella enterica serovar Enteritidis outbreak associated with Polish eggs was characterized by whole-genome sequencing (WGS)-based analysis, with various European institutes using different analysis workflows to identify isolates potentially related to the outbreak. The objective of our study was to compare the output of six of these different typing workflows (distance matrices of either SNP-based or allele-based workflows) in terms of cluster detection and concordance. To this end, we analysed a set of 180 isolates coming from confirmed and probable outbreak cases, which were representative of the genetic variation within the outbreak, supplemented with 22 unrelated contemporaneous S. enterica serovar Enteritidis isolates. Since the definition of a cluster cut-off based on genetic distance requires prior knowledge on the evolutionary processes that govern the bacterial populations in question, we used a variety of hierarchical clustering methods (single, average and complete) and selected the optimal number of clusters based on the consensus of the silhouette, Dunn2, and McClain-Rao internal validation indices.