The Prevalence of Advanced Liver Fibrosis Among Patients With Type 2 Diabetes Mellitus: A Single-Centre Experience in Penang, Malaysia.

Objectives: Type 2 diabetes mellitus (T2DM) is an important risk factor for Non-alcoholic fatty liver disease (NAFLD). It worsens the course of NAFLD. We investigated the prevalence of advanced liver fibrosis among patients with T2DM. Our secondary objectives were to describe patient demographics, to explore associated clinical factors, and to compare FIB-4 Index and liver stiffness measurement (LSM). Methodology: This was a cross-sectional study on 258 patients with T2DM duration of at least 10 years. Transient elastography (FibroScan®) was performed on all subjects. Advanced liver fibrosis was diagnosed based on LSM results. The FIB-4 index formula was used. Results: The prevalence of advanced liver fibrosis was 22.1%. Associated factors were body mass index (BMI), alanine transaminase (ALT), aspartate transaminase (AST), gamma-glutamyl transferase (GGT), triglyceride (TG) and high-density lipoprotein (HDL) cholesterol. Independent factors were BMI and GGT (p=0.003 and p<0.001). FIB-4 index has 30.0% sensitivity, 85.0% specificity, 38.7% positive predictive value, and 79.4% negative predictive value in detecting advanced liver fibrosis by LSM criteria. Conclusion: Our study confirmed the high prevalence of advanced liver fibrosis among patients with long-standing T2DM. This study suggests the benefit of advanced liver fibrosis screening in patients with a minimum of 10 years of T2DM, especially those with high BMI and GGT.

Urine supernatant reveals a signature that predicts survival in clear-cell renal cell carcinoma.

OBJECTIVE: To profile the cell-free urine supernatant and plasma of a small cohort of clear-cell renal cell carcinoma (ccRCC) patients by measuring the relative concentrations of 92 proteins related to inflammation. Using The Cancer Genome Atlas (TCGA), we then performed a targeted mRNA analysis of genes encoding the above proteins and defined their effects on overall survival (OS). SUBJECTS/PATIENTS AND METHODS: Samples were collected prospectively from ccRCC patients. A multiplex proximity extension assay was used to measure the concentrations of 92 inflammation-related proteins in cell-free urine supernatants and plasma. Transcriptomic and clinical information from ccRCC patients was obtained from TCGA. Unsupervised clustering and differential protein expression analyses were performed on protein concentration data. Targeted mRNA analysis on genes encoding significant differentially expressed proteins was performed using TCGA. Backward stepwise regression analyses were used to build a nomogram. The performance of the nomogram and clinical benefit was assessed by discrimination and calibration, and a decision curve analysis, respectively. RESULTS: Unsupervised clustering analysis revealed inflammatory signatures in the cell-free urine supernatant of ccRCC patients. Backward stepwise regressions using TCGA data identified transcriptomic risk factors and risk groups associated with OS. A nomogram to predict 2-year and 5-year OS was developed using these risk factors. The decision curve analysis showed that our model was associated with a net benefit improvement compared to the treat-all/none strategies. CONCLUSION: We defined four novel biomarkers using proteomic and transcriptomic data that distinguish severity of prognosis in ccRCC. We showed that these biomarkers can be used in a model to predict 2-year and 5-year OS in ccRCC across different tumour stages. This type of analysis, if validated in the future, provides non-invasive prognostic information that could inform either management or surveillance strategies for patients.

The prevalence of advanced liver fibrosis among patients with type 2 diabetes mellitus: A single-centre experience in Penang, Malaysia / Journal of the ASEAN Federation of Endocrine Societies

Objectives@#This study aimed to compare the severity of COVID-19, inflammatory parameters and clinical outcomes among patients with normal and subnormal levels of Vitamin D.@*Methodology@# This is a retrospective cohort study of 135 patients admitted in a tertiary hospital for COVID-19. Patients were grouped according to their Vitamin D level. Primary outcome measure was the composite of all-cause mortality and morbidity. Other outcome measures determined were the comparison among the groups on the severity of COVID-19 infection, changes in inflammatory parameters, length of hospital stay and duration of respiratory support.@*Results@#There was a significant trend of higher ICU admission, mortality (p-value= 0.006) and poor clinical outcome (p-value=0.009) among the Vitamin D deficient group. No significant difference was found for most of the inflammatory parameters, duration of hospital stay and respiratory support. Overall, patients with deficient, but not insufficient Vitamin D level had 6 times higher odds of composite poor outcome than those with normal Vitamin D (crude OR=5.18, p-value= 0.003; adjusted OR =6.3, p-value=0.043).@*Conclusion@#The inverse relationship between Vitamin D level and poor composite outcome observed in our study suggests that low Vitamin D may be a risk factor for poor prognosis among patients admitted for COVID-19.