Pathophysiology and Treatment of Cystinuria

2018 ◽  
Author(s):  
Jacob Britt ◽  
Ava Saidian ◽  
Dustin Whitaker ◽  
Carter Boyd ◽  
Kyle Wood ◽  
...  
Keyword(s):  
Chronic Kidney Disease ◽  
Kidney Disease ◽  
Autosomal Recessive Disorder ◽  
Disease Diagnosis ◽  
Urine Ph ◽  
Binding Agents ◽  
Stone Prevention ◽  
Thiol Binding ◽  
Dietary Modifications ◽  
Dibasic Amino Acids

Cystinuria is a relatively rare autosomal recessive disorder that manifests early in life and is associated with the development of kidney stones composed of cystine. It is due to mutations in two genes that are involved in the transport of cystine, neutral, and dibasic amino acids in the proximal tubule of the kidney. Patients are at risk for developing chronic kidney disease. Diagnosis is typically established with stone analysis and quantitative urinary cystine excretion. These patients may form extremely large stones requiring percutaneous nephrolithotomy. Stone-prevention strategies include dietary modifications (increased fluid intake and limitation of sodium and animal protein consumption), urine pH manipulation, and thiol-binding agents. These patients should be followed closely, and preemptive stone removal with ureteroscopy should be considered to limit the necessity for more invasive procedures.   This review contains 2 figures and 38 references. Key Words: a-mercaptopropionyl glycine, amino acid transport, chronic kidney disease, cystinuria, SLC3A1, SLC7A9, thiol-binding agent, urinary pH manipulation

Exploring Patients' Experiences After Chronic Kidney Disease Diagnosis: A Qualitative Study

2020 ◽  
Vol 47 (1) ◽  
pp. 67
Author(s):  
Areti Stavropoulou ◽  
Michael Rovithis ◽  
Maria G. Grammatikopoulou ◽  
Konstantina Kyriakidi ◽  
Andriani Pylarinou ◽  
...  
Keyword(s):  
Chronic Kidney Disease ◽  
Kidney Disease ◽  
Qualitative Study ◽  
Disease Diagnosis

Risk Factor Identification, Classification and Prediction Summary of Chronic Kidney Disease

2020 ◽  
Vol 13 ◽  
Author(s):  
Pramila Arulanthu ◽  
Eswaran Perumal
Keyword(s):  
Chronic Kidney Disease ◽  
Kidney Disease ◽  
Disease Diagnosis ◽  
Medical Data ◽  
Machine Learning Algorithms ◽  
World Health ◽  
Medical Field ◽  
Data Set ◽  
Medical Issues ◽  
Health Organization

: The medical data has an enormous quantity of information. This data set requires effective classification for accurate prediction. Predicting medical issues is an extremely difficult task in which Chronic Kidney Disease (CKD) is one of the major unpredictable diseases in medical field. Perhaps certain medical experts do not have identical awareness and skill to solve the issues of their patients. Most of the medical experts may have underprivileged results on disease diagnosis of their patients. Sometimes patients may lose their life in nature. As per the Global Burden of Disease (GBD-2015) study, death by CKD was ranked 17th place and GBD-2010 report 27th among the causes of death globally. Death by CKD is constituted 2·9% of all death between the year 2010 and 2013 among people from 15 to 69 age. As per World Health Organization (WHO-2005) report, 58 million people expired by CKD. Hence, this article presents the state of art review on Chronic Kidney Disease (CKD) classification and prediction. Normally, advanced data mining techniques, fuzzy and machine learning algorithms are used to classify medical data and disease diagnosis. This study reviews and summarizes many classification techniques and disease diagnosis methods presented earlier. The main intention of this review is to point out and address some of the issues and complications of the existing methods. It is also attempts to discuss the limitations and accuracy level of the existing CKD classification and disease diagnosis methods.

scholarly journals Guidelines adherence in the prevention and management of chronic kidney disease in patients with diabetes mellitus on the background of recent European recommendations – a registry-based analysis

2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Peter Bramlage ◽  
Stefanie Lanzinger ◽  
Sascha R. Tittel ◽  
Eva Hess ◽  
Simon Fahrner ◽  
...  
Keyword(s):  
Type 2 Diabetes ◽  
Chronic Kidney Disease ◽  
Clinical Practice ◽  
Kidney Disease ◽  
Analysis Data ◽  
Disease Diagnosis ◽  
Diabetic Patients ◽  
European Society Of Cardiology

Abstract Background Recent European Society of Cardiology (ESC)/European Association for the Study of Diabetes (EASD) guidelines provide recommendations for detecting and treating chronic kidney disease (CKD) in diabetic patients. We compared clinical practice with guidelines to determine areas for improvement. Methods German database analysis of 675,628 patients with type 1 or type 2 diabetes, with 134,395 included in this analysis. Data were compared with ESC/EASD recommendations. Results This analysis included 17,649 and 116,747 patients with type 1 and type 2 diabetes, respectively. The analysis showed that 44.1 and 49.1 % patients with type 1 and type 2 diabetes, respectively, were annually screened for CKD. Despite anti-diabetic treatment, only 27.2 % patients with type 1 and 43.5 % patients with type 2 achieved a target HbA1c of < 7.0 %. Use of sodium-glucose transport protein 2 inhibitors (1.5 % type 1/8.7 % type 2 diabetes) and glucagon-like peptide-1 receptor agonists (0.6 % type 1/5.2 % type 2 diabetes) was limited. Hypertension was controlled according to guidelines in 41.1 and 67.7 % patients aged 18–65 years with type 1 and 2 diabetes, respectively, (62.4 vs. 68.4 % in patients > 65 years). Renin angiotensin aldosterone inhibitors were used in 24.0 and 40.9 % patients with type 1 diabetes (micro- vs. macroalbuminuria) and 39.9 and 47.7 %, respectively, in type 2 diabetes. Conclusions Data indicate there is room for improvement in caring for diabetic patients with respect to renal disease diagnosis and treatment. While specific and potentially clinically justified reasons for non-compliance exist, the data may serve well for a critical appraisal of clinical practice decisions.

scholarly journals Provider perspectives on chronic kidney disease diagnosis delivery

2018 ◽  
Vol 89 (3) ◽  
pp. 205-213 ◽  
Author(s):  
Hannah Tiu ◽  
Angela Fagerlin ◽  
Meghan Roney ◽  
Ev Kerr ◽  
Akinlolu Ojo ◽  
...  
Keyword(s):  
Chronic Kidney Disease ◽  
Kidney Disease ◽  
Disease Diagnosis ◽  
Provider Perspectives

scholarly journals High Protein Food with Similar Phosphorus Content as Lower Protein Foods Increases Levels of Uremic Toxins

2020 ◽  
Vol 4 (Supplement_2) ◽  
pp. 683-683
Author(s):  
Eden Ephraim ◽  
Dennis Jewell
Keyword(s):  
Chronic Kidney Disease ◽  
Kidney Disease ◽  
Treatment Period ◽  
Uremic Toxins ◽  
High Protein ◽  
Phosphorus Concentration ◽  
Urine Ph ◽  
Protein Food ◽  
Protein Levels ◽  
Low Protein

Abstract Objectives The aim of this study was to determine the effect of feeding cats with reduced renal function a high protein food while maintaining phosphorus concentration across foods containing varying protein levels. Methods The study was conducted using 23 cats of 5–13 years of age with chronic kidney disease. After a 1 month washout period, cats were randomly assigned to one of the 6 groups of approximately 4 cats to receive 3 treatment foods, each for 111 days, in a sequence following the William's Latin Square design. The treatment foods contained on a dry matter basis, low (25.94%), medium (31.91%) or high (36.77%) protein and had similar other nutrient levels including Phosphorus. Average body weights were determined after each treatment period. Blood and urine samples were collected at the end of each treatment period to compare changes in levels of metabolites associated with progression of kidney disease. Results The consumption of the foods with different protein levels did not have an effect on body weight. Urine pH was significantly higher after cats were fed high protein food (P = 0.0003). Blood chemistry results showed that cats had significantly increased level of blood urea nitrogen (BUN) after the consumption of the high protein food compared with the low protein food (P = 0.005). Increased urea levels were also confirmed from results of plasma metabolomics. Levels of microbial uremic toxins such as 3-indoxyl sulfate, 5-hydroxyindole sulfate, 6-hydroxyindole sulfate and 3-hydroxyindoline-one sulfate were significantly elevated after cats were fed high protein compared to both medium and low protein foods (P &lt; 0.05). The glycine conjugate of butyric acid (butyrylglycine) was significantly lower in the plasma of cats fed the high protein compared to low protein food (P = 0.004). Levels of betaine were lower after feeding high protein compared to low (P = 0.001) and medium protein (P = 0.046) foods. Furthermore, cats had the lowest level of gamma-tocopherol/beta-tocopherol with high protein food compared to medium and low protein foods (P &lt; 0.001). Conclusions Feeding high protein food to cats with chronic kidney disease leads to higher concentrations of uremic toxins in the blood. Funding Sources The study was funded by Hill's Pet Nutrition, Topeka, Kansas, USA.

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