scholarly journals Accuracy of the urinary albumin to creatinine ratio as a predictor of albuminuria in adults with sickle cell disease

2002 ◽  
Vol 55 (12) ◽  
pp. 973-975 ◽  
Author(s):  
C S P Lima
Blood ◽  
2020 ◽  
Vol 136 (Supplement 1) ◽  
pp. 1-2
Author(s):  
Baba PD Inusa ◽  
Caroline Booth ◽  
Nosa Iduoriyekemwen

Background:Renal abnormalities in sickle cell disease commence early in childhood. Glomerular hyperfiltration and albuminuria are the most prevalent renal abnormalities in sickle cell disease. However, these renal abnormalities of SCD have not been considered exclusively in the adolescent age group. Objective:To determine the prevalence of glomerular hyperfiltration and albuminuria as well as identify the determinants for glomerular hyperfiltration in adolescents with SCD. Patients and Methods:Ethical permission was through the Trust audit and service evaluation governance review board to implement quality assessment of clinical service. Electronic patient records (charts) of 153 adolescents with SCD aged 10->19 years, attending the Paediatrics Haematology Clinic at Evelina children Hospital, London, United Kingdom. Clinical information obtained included demographics age, gender sickle cell type, as well as history of acute event, treatment history, anthropometric indices and blood pressure. The laboratory parameters obtained were urine albumin-creatinine ratio or protein-creatinine ratio, haemoglobin level, white blood cell count, red blood cell count, platelet count, reticulocyte count, foetal haemoglobin level, lactate dehydrogenase level, serum creatinine and serum ferritin level. The glomerular filtration rate was derived using the Bedside Schwartz's method. Grouping of the adolescents was based on present and absence of glomerular hyperfiltration, which was defined as glomerular filtration rate > 140ml/min/m2. The presence of albuminuria was defined as urine albumin-to-creatinine ratio >3mg/mmol or protein- to- creatinine ratio of > 15mg/mmol. Investigated were the clinical and laboratory determinants of glomerular hyperfiltration in the total study population. Result:Prevalence of glomerular hyperfiltration was 33.3% in the adolescents studied (age bracket please) , and that of albuminuria was 15.7% amongst the adolescents with SCD studies (microalbuminuria 14.4%, and 1.3% overt proteinuria) of which 13.7% of those with glomerular hyperfiltration also had albuminuria. The mean eGFR of the adolescents with SCD who had glomerular hyperfiltration was 160.2 ± 20.0 ml/min/1.73m2, and that of those with no glomerular hyperfiltration was 109.9 ± 19.3ml/min/m2. A significantly higher proportion of the adolescents with SCD who had glomerular hyperfiltration had the haemoglobin SS disease (47 (92.2%) versus 68 (66.7%);P=0.007). On univariable analysis, the adolescent with glomerular hyperfiltration had significantly lower weight (48.0 ± 18.0 versus 54.8 ± 17.0 kg;p= 0.02), height (155.1 ± 13.1 versus 160.6 ± 13.1 cm;p= 0.01), body mass index (19.4 ± 5.0 versus 21.0 ± 4.3 ;p= 0.04), haemoglobin level (88.7 ± 13.3 versus 98.1 ± 21.7 g/L;p= 0.001), and serum creatinine level (0.4 ± 0.1 versus 0.6 ± 0.2mg/dl;p= 0.0001) as compared to those with no glomerular hyperfiltration. The adolescents with glomerular hyperfiltration also had significantly higher lactate dehydrogenase level (525.9 ± 180.3 versus 449.6 ± 170.3 IU/L;p= 0.01) as compared to those with no glomerular hyperfiltration. However, no association was found on multivariable analysis. Conclusion:This study revealed that the prevalence of glomerular hyperfiltration in the adolescent age group was high, and the high glomerular filtration rates begin to decline toward normal values in middle adolescent age not before. Figure Disclosures Inusa: AstraZeneca:Honoraria, Other: Steering committee participation, Research Funding, Speakers Bureau;Vertex:Research Funding;Global Blood Therapeutics:Honoraria, Other: Steering committee participation, Research Funding, Speakers Bureau;Bluebird bio:Research Funding;Novartis:Honoraria, Other: Steering committee participation, Research Funding, Speakers Bureau.


Blood ◽  
2015 ◽  
Vol 126 (23) ◽  
pp. 3418-3418
Author(s):  
Xionghao Lin ◽  
Elena Afia Adjei ◽  
Namita Kumari ◽  
Sharmin Diaz ◽  
Marina Jerebtsova ◽  
...  

Abstract Background Urinary hepcidin is a potential biomarker of renal inflammation and acute kidney injury (AKI) which is elevated in sickle cell disease (SCD). Hepcidin in circulation is filtered through glomeruli filtration barrier and reabsorbed by the renal tubules. Hepcidin can also be synthesized by the kidney tubular cells. Thus, increased urinary levels of hepcidin may reflect either a reduction in tubular uptake or an increase in renal production. Recent studies suggested that urinary hepcidin may protect against AKI by attenuating heme-mediated injury. Thus decreased hepcidin levels in SCD patients may contribute to AKI and serve as potentially informative marker of SCD-associated kidney injury. Previously, hepcidin was measured by ELISA and mass spectrometry. Immunoassays are limited due to the cross-reactivity of antibodies to prohepcidin and truncated hepcidin-20, -22, and -24 isoforms of active hepcidin-25. Mass spectrometric assays are specific for hepcidin-25 but sample preparation remains a challenge. Objective To develop a sensitive, reliable and reproducible nanoLC/FT-MS method with simplified sample preparation for measuring of hepcidin in urine samples. Also to correlate urinary hepcidin with urinary albumin and urinary protein to access the degree of kidney dysfunction. Methods Samples were enriched and purified semi-automaticaly on 10-uL ZipTip and online trap column. Stable isotope-labeled hepcidin was used as internal standard. The standard concentration range was 1.56-800 nM and quality control samples were 5 nM, 20 nM, 80 nM and 400 nM. Samples were subjected to an LC-20AD nano HPLC system coupled to an LTQ XL™ Orbitrap mass spectrometer with an in-house made nano-HPLC column. High resolution/selected reaction monitoring (HR/SRM) scan was carried out and the narrow mass range ([M+H]+ ±0.01 Da) was used to extract ion chromatograms (EICs) for quantification. Urinary samples were collected from 20 SCD patients and 13 controls. Urinary albumin, protein and creatinine were detected by ELISA. The urine hepcidin concentrations were normalized to urine creatinine (Cr) values. Results Semi-automatic approach simplified sample preparation and accelerated the analysis. At least 24 samples could be prepared and processed at the same time. Online column trapping further purified and enriched hepcidin and improved the sensitivity and specificity of this method by eliminating interferences from urine. Hepcidin showed a good linearity within the concentration range of 1.56-800 nM with an r2 value of 0.9994. The precision intraday (n = 5) and interday (n = 5) and the repeatability (n=5) of the method were good with relative standard deviations (RSDs) lower than 5%. The analyzed samples were stable for 3 days at +4°C (RSDs<5%). The percent mean recoveries of hepcidin was within the acceptable range of 89.65-104.79%. We found that SCD patients had significantly lower (about 2-fold) urinary hepcidin levels compared to controls, and urinary hepcidin levels in 2 SCD patients were below the lower limit of detection (<0.5 nM). We found that there was no difference in urine albumin between SCD and control subjects, total urine protein was significantly increased in SCD patients. There was no positive correlation between urine hepcidin and urine albumin or total protein. Conclusion We developed an LC-MS based method for measuring levels of urinary hepcidin. This method is promising in terms of recovery, sensitivity, selectivity, repeatability and simplicity of sample preparation. SCD patients showed significantly decreased hepcidin levels in urine suggesting a potentially novel mechanism of AKI in SCD. Acknowledgments This work was supported by NIH Research Grants (1P50HL118006, 1R01HL125005 and 5G12MD007597). The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. Disclosures No relevant conflicts of interest to declare.


2016 ◽  
Vol 4 ◽  
Author(s):  
Ibrahim F. Shatat ◽  
Suparna Qanungo ◽  
Shannon Hudson ◽  
Marilyn A. Laken ◽  
Susan M. Hailpern

1974 ◽  
Vol 133 (4) ◽  
pp. 624-631 ◽  
Author(s):  
T. A. Bensinger

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