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Uremia/Uremic Syndrome
Published in Charles Theisler, Adjuvant Medical Care, 2023
Uremia is defined as elevated concentrations of urea, creatinine, and other nitrogenous end products of metabolism in the blood that are normally excreted by the kidneys into the urine. It is a serious condition and when left untreated can lead to death. Uremia occurs after the kidneys are damaged (chronic kidney disease) and cannot filter the blood normally. Symptoms include itchy skin, nausea, loss of appetite, weight loss, leg cramps, and fatigue. Common causes of chronic kidney disease are hypertension, polycystic kidney disease, diabetes (DM1 and DM2), glomerulitis, some cancers, and recurrent kidney stones or infections. Complications of untreated uremia can be seizures, coma, bleeding, cardiac arrest, and death.
The Arteries, the Endothelium, Endothelial Dysfunction, Glycocalyx, Glycocalyx Dysfunction, Nitric Oxide, and CHD
Published in Mark C Houston, The Truth About Heart Disease, 2023
The alterations to the arterial muscle include leaking of the blood vessel with the loss of proteins into the cells, tissues, and organs. If this happens in the kidney, then the proteins spill into the urine (proteinuria), which is very abnormal and predicts future kidney disease. Another alteration is the constriction or narrowing of the artery with reduced blood flow and hypertension. Finally, there may be abnormal growth, thickening, and stiffness of the artery which leads to arteriosclerosis and subsequent CHD and MI.
Diagnosis and Prediction of Type-2 Chronic Kidney Disease Using Machine Learning Approaches
Published in Meenu Gupta, Rachna Jain, Arun Solanki, Fadi Al-Turjman, Cancer Prediction for Industrial IoT 4.0: A Machine Learning Perspective, 2021
Ritu Aggarwal, Prateek Thakral
This chapter focuses on research on creatinine, sodium, calcium salts, blood urea, and blood nitrogen levels in patients. With the help of these factors, kidney disease can be easily detected. To decide the chance of survival or need for kidney transplantation depends on these tests. Otherwise, diagnosis of CKD is very difficult. Revathy [3] proposed a methodology to detect kidney disease by using the different classifiers of ML – SVM, Random Forest, decision tree, and feature selection – to calculate the precision.
Dialysis vintage is associated with a high prevalence and severity of unpleasant symptoms in patients on hemodialysis
Published in Renal Failure, 2023
Li Zhu, Xun-Liang Li, Rui Shi, De-Guang Wang
Physical and emotional health are important factors in the ability to live, work and study actively. Especially for patients with chronic illnesses, symptoms related to physical and emotional illnesses not only affect the quality of their daily life but also play a key role in the adequacy of treatment for their physical illnesses [1,2]. Research shows that individuals with chronic kidney disease (CKD) experience a significantly higher burden of adverse symptoms, including fatigue and anxiety, compared to the general population. This burden is estimated to be three times greater. Furthermore, the risk of mortality rates and the need for dialysis tend to be higher in CKD patients [3,4]. Despite the higher burden of unpleasant symptoms in end-stage renal disease (ESRD), most dialysis patients often consider the priority of relieving clinical symptoms and neglect the treatment of unpleasant symptom burden, which leads to the under-treatment of somatic illnesses [5]. Therefore, it is crucial to incorporate regular screening for unpleasant emotions in patients with CKD as part of clinical treatment. Providing high-quality care to patients can enhance their self-management skills and medication compliance, improve their quality of life, and significantly alleviate negative emotions [6].
Urinary exosomes derived circRNAs as biomarkers for chronic renal fibrosis
Published in Annals of Medicine, 2022
Yuhan Cao, Yuanhui Shi, Yanlang Yang, Zhangli Wu, Nana Peng, Jie Xiao, Fan Dou, Jingjing Xu, Wenjun Pei, Cong Fu, Pingsheng Chen, Yuwei Wang
Early, accurate and non-invasive diagnosis of renal fibrosis was important in treating CKD. Accurate biomarkers can not only replace traumatic pathological examination but also guided treatment and prompt prognosis. Some studies had found that markers of key biological events in renal fibrosis can be detected before pathological changes appear, and were related to the risk of progression to fibrosis [13]. For a long time, urine had become the main source of non-invasive biomarkers for the diagnosis of kidney disease because it carried a lot of kidney disease-related information. Up to now, it had been found that there were many small cells in the urine, including podocytes and tubular epithelial cells. In 2001, Li et al. firstly established a non-invasive approach to diagnosing acute renal rejection of allografts by isolating and quantifying RNA of specific genes in urine cells [4]. Urinary sediment had attracted researchers' focus and had become an attractive resource for detecting the biomarker for kidney diseases [11,14–17]. However, the current urine cell mRNA detection technology still had some limitations. There were a large proportion of non-renal cells in the urine, such as transitional epithelial cells and squamous epithelial cells. Kidney proper cells such as renal tubular epithelial cells (TEC) and podocytes were mixed in different proportions [18]. mRNA expression level in urine cannot reflect the degree of renal disease accurately [19].
Kidney tissue elastography and interstitial fibrosis observed in kidney biopsy
Published in Renal Failure, 2022
Mehmet Sami Islamoglu, Sibel Gulcicek, Nurhan Seyahi
Because of the high negative predictive value, we suggest that elastography should mainly be used as an exclusion test for the presence of fibrosis. However, we want to point out that because of the low number of patients with fibrosis our results should be confirmed in larger groups. Indeed, the most important limitation of our study was the small number of patients in the fibrosis group, since patients with proteinuria with new onset of chronic kidney disease or developing acute kidney disease rather than the end-stage chronic kidney disease group were included in the study. Despite these limitations, a significant relationship was observed between elastography measurements and fibrosis. If we included the patients with end-stage chronic kidney disease in whom fibrosis is more prevalent, the significant relationship could have been established more strongly. Further studies with more chronic kidney disease patients are needed.