Current Issue : January - March Volume : 2020 Issue Number : 1 Articles : 5 Articles
Changes in renal dimensions, including total kidney volume, not only inform ongoing renal\ndisease but also disease progression. Determination of renal dimensions can inform drug efficacy,\nis important for matching recipients with potential donors, and to inform debulking of renal tumors.\nImaging of kidney and application of the ellipse-based formula has become standard for estimating\nrenal dimensions. Nevertheless, the existing ellipse-based formula underestimates renal dimensions\nincluding total kidney volume, regardless of the imaging modality used. Based on a model of murine\nkidney disease, this laboratory has previously proposed a modification to this formula which exhibits\nbetter estimation of renal dimensions. The present study sought to determine whether this modified\nformula is applicable to additional models of kidney disease. Kidneys were sourced from etiologically\ndistinct murine and rat models of renal scarring. In each case, renal dimensions calculated using the\nexisting ellipse-based formula was significantly lesser than the measured dimensions. By contrast,\nthere was no difference between the measured dimensions and those calculated using the modified\nformula. In a model of polycystic kidney disease, total kidney volume calculated using the existing\nformula significantly underestimated measured kidney volume whereas use of the modified formula\nyielded a calculated kidney volume in excellent agreement with the measured volume. Use of this\nmodified formula provides a better estimate of renal dimensions across a number of disease models....
Background: Patients with autosomal dominant polycystic kidney disease (ADPKD) have an increased risk of\ncardiovascular morbidity and mortality. Impaired left ventricular (LV) global longitudinal strain (GLS) can be a sign of\nsubclinical cardiac dysfunction even in patients with otherwise preserved ejection fraction (EF). Transmitral early\nfilling velocity to early diastolic strain rate (E/SRe) is a novel measure of LV filling pressure, which is often affected\nearly in cardiac disease.\nMethods: A total of 110 ADPKD patients not on dialysis were included in this prospective study. All patients underwent\nan extensive echocardiographic examination including two-dimensional speckle tracking. GLS and strain rates\nwere measured. The distribution of GLS and E/SRe was determined and patient characteristics were compared\nby median levels of GLS (- 17.8%) and E/SRe (91.4 cm). Twenty healthy participants were included as control\ngroup������....
Background: Strong evidence comparing effectiveness between nephron-sparing intervention (NSI) and active\nsurveillance (AS) is lacking. Thus, we aim to compare the outcomes of survival, including cancer-specific survival (CSS),\noverall survival (OS), and cardiovascular-specific survival (CVSS), in patients with renal masses who underwent NSI or AS.\nMethods: A systematic literature search of PubMed, Web of Science, and EMBASE was performed for citations published\nprior to September 2018 that described NSI, partial nephrectomy and thermal ablation included, and AS for patients with\nrenal masses and a standard meta-analysis on survival outcomes was then conducted.\nResults: The meta-analysis included seven studies containing 5809 patients. The results comparing NSI with AS were as\nfollows: CSS (hazard ratio (HR) = 0.64, 95% confidence interval (CI): 0.46-0.89, P < 0.001), OS (HR = 0.46, 95%CI: 0.39-0.53,\nP < 0.001), and CVSS (HR = 0.37, 95%CI: 0.24-0.57, P < 0.001).\nConclusions: This systematic review and meta-analysis indicates that NSI is associated with better OS, CSS and CVSS\nwhen compared with AS for patients with renal masses. Further better prospective cohort studies are needed to make\ndefinitive statements about these different treatment methods....
Background: The challenges in diagnosis of rare renal conditions can negatively impact patient prognosis, quality\nof life and result in significant healthcare costs. Differential methylation is emerging as an important biomarker for\nrare diseases and should be evaluated for rare renal conditions.\nMethods: A comprehensive systematic review of methylation and rare renal disorders was conducted by searching\nthe electronic databases MEDLINE, EMBASE, PubMed, Cochrane Library, alongside grey literature from GreyLit and\nOpenGrey databases, for publications published before September 2018. Additionally, the reference lists of the\nincluded papers were searched. Data was extracted and appraised including the primary focus, measurement and\nmethodological rigour of the source. Eligibility criteria were adapted using the inclusion criteria from â??The 100,000\nGenomes Projectâ?? and The National Registry of Rare Kidney Diseases, with additional focus on methylation.\nResults: Thirteen full text articles were included in the review. Diseases analysed for differential methylation\nincluded glomerular disease, IgA nephropathy, ADPKD, rare causes of proteinuria, congenital renal agenesis, and\nmembranous nephropathy.\nConclusions: Differential methylation has been observed for several rare renal diseases, highlighting its potential\nfor improving molecular characterisation of these disorders. Further investigation of methylation following a\nstandardised reporting structure is necessary to improve research quality. Multi-omic data will provide insights for\nimproved diagnosis, prognosis and support for individuals living and working with rare renal diseases....
Background: Patients with cardiovascular disease are at an increased risk of chronic kidney disease (CKD). However,\ndata on incident CKD in patients with multiple vascular comorbidities are insufficient. In this study, we identified\nthe predictors of CKD stages 3-5 in patients at risk of cardiovascular disease and used their estimated glomerular\nfiltration rate (eGFR) to construct a nomogram to predict the 5-year risk of incident CKD.\nMethods: Ambulatory data on 622 adults with preserved kidney function and one or more cardiovascular disease\nrisk factors who attended outpatient clinics at a tertiary care hospital in Al-Ain, United Arab Emirates were obtained\nretrospectively. eGFR was calculated using the Chronic Kidney Disease Epidemiology Collaboration equation and\nassessed every 3 months from baseline to December 12, 2017. Fine and Gray competing risk regression model was\nused to identify the independent variables and construct a nomogram to predict incident CKD at 5 years, which is\ndefined as eGFR < 60 mL/min/1.73m2 for greater than equal to3 months. Time-dependent area under the receiver operating characteristic\ncurve (AUC) was used to evaluate the discrimination ability of the model. Calibration curves were applied to determine\nthe calibration ability and adjusted for the competing risk of death. Internal validation of predictive accuracy\nwas performed using K-fold cross-validation.\nResults: Of the 622 patients, 71 had newly developed CKD stages 3-5 over a median follow-up of 96 months\n(interquartile range, 86-103 months). Baseline eGFR, hemoglobin A1c, total cholesterol, and history of diabetes\nmellitus were identified as significant predictors of CKD stages 3-5. The nomogram had good discrimination\nin predicting the disease stages, with a time-dependent AUC of 0.918 (95% confidence interval, 0.846-0.964)\nat 5 years, after internal validation by cross-validation.\nConclusions: This study demonstrated that incident CKD could be predicted with a simple and practical\nnomogram in patients at risk of cardiovascular disease and with preserved kidney function, which in turn\ncould help clinicians make more informed decisions for CKD management in these patients....
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