METHODS: This cross-sectional study was performed at Hue Central Hospital from 2012-2016 on 176 CKD and 64 control subjects. ADMA levels were measured by using the enzyme linked immunosorbent assay (ELISA) method.
RESULTS: Mean ADMA level was markedly higher (p<0.001) in all patients combined (0.73±0.24μmol/L) than in control subjects (0.47±0.13μmol/L). Mean ADMA levels in advanced kidney disease were higher than control subjects. ADMA levels correlated inversely and relatively strictly to estimated glomerular filtration rate (eGFR) (r = -0.689; p<0.001), haemoglobin (r = -0.525; p<0.001) and haematocrit (r = - 0.491; p<0.001); correlated favourably and relatively strictly to serum creatinine (r = 0.569; p<0.001) and serum urea (r = 0.642; p<0.001). ADMA elevation was predicted simultaneously by eGFR<60 mL/min/1.73m2 (p<0.001), anaemia (p=0.002), body mass index (BMI) (p=0.011) and high sensitivity C-reactive protein (hs-CRP) (p=0.041). Cutoff of ≥0.68μmol/L, ADMA levels predict reduction of eGFR<60 mL/min/1.73m2, sensitivity of 86.9 %, specificity of 82.6%, area under ROC 92.4% (95%CI: 88.6-96.1%).
METHODS: We investigated serum creatinine (S-Cr) monitoring rates before and during ART and the incidence and prevalence of renal dysfunction after starting TDF by using data from a regional cohort of HIV-infected individuals in the Asia-Pacific. Time to renal dysfunction was defined as time from TDF initiation to the decline in estimated glomerular filtration rate (eGFR) to <60 ml/min/1.73m2 with >30% reduction from baseline using the Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) equation or the decision to stop TDF for reported TDF-nephrotoxicity. Predictors of S-Cr monitoring rates were assessed by Poisson regression and risk factors for developing renal dysfunction were assessed by Cox regression.
RESULTS: Among 2,425 patients who received TDF, S-Cr monitoring rates increased from 1.01 to 1.84 per person per year after starting TDF (incidence rate ratio 1.68, 95%CI 1.62-1.74, p <0.001). Renal dysfunction on TDF occurred in 103 patients over 5,368 person-years of TDF use (4.2%; incidence 1.75 per 100 person-years). Risk factors for developing renal dysfunction included older age (>50 vs. ≤30, hazard ratio [HR] 5.39, 95%CI 2.52-11.50, p <0.001; and using PI-based regimen (HR 1.93, 95%CI 1.22-3.07, p = 0.005). Having an eGFR prior to TDF (pre-TDF eGFR) of ≥60 ml/min/1.73m2 showed a protective effect (HR 0.38, 95%CI, 0.17-0.85, p = 0.018).
CONCLUSIONS: Renal dysfunction on commencing TDF use was not common, however, older age, lower baseline eGFR and PI-based ART were associated with higher risk of renal dysfunction during TDF use in adult HIV-infected individuals in the Asia-Pacific region.
OBJECTIVE: The aim of this review is to examine studies that focused on the different types of samples which may serve as a good and promising biomarker for early diagnosis of CKD or to detect rapidly declining renal function among CKD patient.
METHOD: The review of international literature was made on paper and electronic databases Nature, PubMed, Springer Link and Science Direct. The Scopus index was used to verify the scientific relevance of the papers. Publications were selected based on the inclusion and exclusion criteria.
RESULT: 63 publications were found to be compatible with the study objectives. Several biomarkers of interest with different sample types were taken for comparison.
CONCLUSION: Biomarkers from urine samples yield more significant outcome as compare to biomarkers from blood samples. But, validation and confirmation with a different type of study designed on a larger population is needed. More comparison studies on different types of samples are needed to further illuminate which biomarker is the better tool for the diagnosis and prognosis of CKD.