Anaemia of chronic kidney disease: diagnosis, assessment and treatment

2016 ◽  
Vol 1 (1) ◽  
pp. 18-25
Author(s):  
Karen Jenkins
Keyword(s):  
Chronic Kidney Disease ◽  
Kidney Disease ◽  
Disease Diagnosis ◽  
Assessment And Treatment

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

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

scholarly journals Retinal Vascular Signs as Screening and Prognostic Factors for Chronic Kidney Disease: A Systematic Review and Meta-Analysis of Current Evidence

2021 ◽  
Vol 11 (7) ◽  
pp. 665
Author(s):  
Michael Aronov ◽  
Raviv Allon ◽  
Danielle Stave ◽  
Michael Belkin ◽  
Eyal Margalit ◽  
...  
Keyword(s):  
Chronic Kidney Disease ◽  
Kidney Disease ◽  
Current Literature ◽  
Meta Analysis ◽  
Disease Diagnosis ◽  
Current Evidence ◽  
Diabetic Patients ◽  
Type 2 Diabetic Patients ◽  
Retinal Microvasculature ◽  
Retinal Microvascular Signs

Background: The substantial burden of kidney disease fosters interest in new ways of screening for early disease diagnosis, especially by non-invasive imaging. Increasing evidence for an association between retinal microvascular signs and kidney disease prompted us to investigate the relevant current literature on such an association systematically by performing a meta-analysis of our findings. Methods: We scrutinized the current literature by searching PubMed and Embase databases from for clinical studies of the association between retinal microvascular signs and prevalent or incident kidney disease. After excluding cases that did not meet our criteria, we extracted relevant data from 42 published studies (9 prospective, 32 cross-sectional, and 1 retrospective). Results: Our investigation yielded significant associations between retinal vascular changes (including retinopathy and retinal vascular diameter) and kidney dysfunction (including chronic kidney disease (CKD), end-stage renal disease (ESRD), albuminuria, and estimated glomerular filtration rate (eGFR) decline). According to our meta-analysis, retinopathy was associated with ESRD (hazard ratio (HR) 2.12 (95% confidence interval CI; 1.39–3.22)) and with CKD prevalence in the general population (odds ratio (OR) 1.31 (95% CI; 1.14–1.50)), and specifically in type 2 diabetic patients (OR 1.68 (95% CI; 1.68–2.16)). CRAE was associated with prevalent CKD (OR 1.41 (95% CI; 1.09–1.82)). Conclusions: Our findings suggest that the retinal microvasculature can provide essential data about concurrent kidney disease status and predict future risk for kidney disease development and progression.

scholarly journals Cost-sensitive Ensemble Feature Ranking and Automatic Threshold Selection for Chronic Kidney Disease Diagnosis

2020 ◽  
Author(s):  
Syed Imran Ali ◽  
Bilal Ali ◽  
Jamil Hussain ◽  
Musarrat Hussain ◽  
Fahad Ahmed Satti ◽  
...  
Keyword(s):  
Chronic Kidney Disease ◽  
Kidney Disease ◽  
Model Performance ◽  
Disease Diagnosis ◽  
Special Treatment ◽  
Feature Ranking ◽  
Classification Models ◽  
Threshold Selection ◽  
Classification Problems ◽  
The Cost

Automated medical diagnosis is one of the important machine learning applications in the domain of healthcare. In this regard, most of the approaches primarily focus on optimizing the accuracy of classification models. In this research, we argue that unlike general-purpose classification problems, medical applications, such as chronic kidney disease (CKD) diagnosis, require special treatment. In the case of CKD, apart from model performance, other factors such as the cost of data acquisition may also be taken into account to enhance the applicability of the automated diagnosis system. In this research, we have proposed two techniques for cost-sensitive feature ranking. An ensemble of decision tree models is employed in both the techniques for computing the worth of a feature in the CKD dataset. An automatic threshold selection heuristic is also introduced which is based on the intersection of features&rsquo; worth and their accumulated cost. A set of experiments are conducted to evaluate the efficacy of the proposed techniques on both tree-based and non-tree based classification models. The proposed approaches are also evaluated against several comparative techniques. Furthermore, it is demonstrated that the proposed techniques select around 1/4th of the original CKD features while reducing the cost by a factor of 7.42 of the original feature set. Based on the extensive experimentation it is concluded that the proposed techniques employing feature-cost interaction heuristic tend to select feature subsets that are both useful and cost-effective.

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