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Background: Early detection and interventions have enabled patients with sickle cell disease (SCD) to live well into adulthood. Consequently, the chronicity of SCD allows for the insidious manifestation of multisystem complications, including renal damage. Cystic renal lesions are commonly incidentally discovered on ultrasound and computerised tomography (CT) imaging of the abdomen. Most are benign simple cysts, however, difficulties may be encountered if infection, rupture, haemorrhage or cancerous changes develop. We aimed to determine whether patients with SCD have a higher prevalence of simple renal cysts compared to non-SCD individuals.Methods: Data for a group of 223 patients with SCD who had undergone an ultrasound and/or CT imaging of the abdomen were extracted for comparison with 180 control patients (haemoglobin genotype unknown), matched for age and ethnicity. Scans were evaluated for 198 SCD patients and 180 controls.Results: Renal cysts were found in 58% of the SCD group and 20% of the controls (OR 5.4 (CI 2.6-11.0), RR 2.8 (CI 1.9-4.2)). Bilateral renal cysts were found in 28% of the SCD participants in comparison with 5% of the control group. In those who had one or more cysts identified, the average number of cysts was 3.76 for the SCD group and 1.94 for the controls. Men with SCD were more likely to develop cysts than women (66% vs 53%), as were men without SCD (22% vs 17%).Conclusions: Simple renal cysts occur more frequently, are more abundant and develop at a younger age in patients with SCD than ethnically-matched controls. Further study of the mechanism underlying cyst formation may shed light on both sickle cell nephropathy and other cystic renal diseases. [ABSTRACT FROM AUTHOR]

Background Uncertainty exists regarding the optimal method to estimate glomerular filtration rate (GFR) for disease detection and monitoring. Widely used GFR estimates have not been validated in British ethnic minority populations. Methods/design Iohexol measured GFR will be the reference against which each estimating equation will be compared. The estimating equations will be based upon serum creatinine and/or cystatin C. The eGFR-C study has 5 components: 1) A prospective longitudinal cohort study of 1300 adults with stage 3 chronic kidney disease followed for 3 years with reference (measured) GFR and test (estimated GFR [eGFR] and urinary albumin-to-creatinine ratio) measurements at baseline and 3 years. Test measurements will also be undertaken every 6 months. The study population will include a representative sample of south-Asians and African- Caribbeans. People with diabetes and proteinuria (ACR ⩾30 mg/mmol) will comprise 20-30% of the study cohort. 2) A sub-study of patterns of disease progression of 375 people (125 each of Caucasian, Asian and African-Caribbean origin; in each case containing subjects at high and low risk of renal progression). Additional reference GFR measurements will be undertaken after 1 and 2 years to enable a model of disease progression and error to be built. 3) A biological variability study to establish reference change values for reference and test measures. 4) A modelling study of the performance of monitoring strategies on detecting progression, utilising estimates of accuracy, patterns of disease progression and estimates of measurement error from studies 1), 2) and 3). 5) A comprehensive cost database for each diagnostic approach will be developed to enable cost-effectiveness modelling of the optimal strategy. The performance of the estimating equations will be evaluated by assessing bias, precision and accuracy. Data will be modelled as a linear function of time utilising all available (maximum 7) time points compared with the difference between baseline and final reference values. The percentage of participants demonstrating large error with the respective estimating equations will be compared. Predictive value of GFR estimates and albumin-tocreatinine ratio will be compared amongst subjects that do or do not show progressive kidney function decline. Discussion The eGFR-C study will provide evidence to inform the optimal GFR estimate to be used in clinical practice. [ABSTRACT FROM AUTHOR]