Chronic Kidney Disease in Cirrhosis: Emerging Complication With Negative Impact in the Liver Transplant Setting

2020 ◽  
Vol 26 (4) ◽  
pp. 483-484
Author(s):  
Elsa Solà ◽  
Pere Ginès
2014 ◽  
Vol 2014 ◽  
pp. 1-13 ◽  
Author(s):  
María M. Adeva-Andany ◽  
Carlos Fernández-Fernández ◽  
David Mouriño-Bayolo ◽  
Elvira Castro-Quintela ◽  
Alberto Domínguez-Montero

Metabolic acidosis occurs when a relative accumulation of plasma anions in excess of cations reduces plasma pH. Replacement of sodium bicarbonate to patients with sodium bicarbonate loss due to diarrhea or renal proximal tubular acidosis is useful, but there is no definite evidence that sodium bicarbonate administration to patients with acute metabolic acidosis, including diabetic ketoacidosis, lactic acidosis, septic shock, intraoperative metabolic acidosis, or cardiac arrest, is beneficial regarding clinical outcomes or mortality rate. Patients with advanced chronic kidney disease usually show metabolic acidosis due to increased unmeasured anions and hyperchloremia. It has been suggested that metabolic acidosis might have a negative impact on progression of kidney dysfunction and that sodium bicarbonate administration might attenuate this effect, but further evaluation is required to validate such a renoprotective strategy. Sodium bicarbonate is the predominant buffer used in dialysis fluids and patients on maintenance dialysis are subjected to a load of sodium bicarbonate during the sessions, suffering a transient metabolic alkalosis of variable severity. Side effects associated with sodium bicarbonate therapy include hypercapnia, hypokalemia, ionized hypocalcemia, and QTc interval prolongation. The potential impact of regular sodium bicarbonate therapy on worsening vascular calcifications in patients with chronic kidney disease has been insufficiently investigated.


2020 ◽  
Vol 26 (4) ◽  
pp. 498-506 ◽  
Author(s):  
Giuseppe Cullaro ◽  
Elizabeth C. Verna ◽  
Brian P. Lee ◽  
Jennifer C. Lai

2014 ◽  
Vol 45 (2) ◽  
pp. 220-227 ◽  
Author(s):  
Kazushige Sato ◽  
Naoki Kawagishi ◽  
Keisei Fujimori ◽  
Noriaki Ohuchi ◽  
Susumu Satomi

PLoS ONE ◽  
2019 ◽  
Vol 14 (7) ◽  
pp. e0219856
Author(s):  
Rachael B. Leek ◽  
Jeong M. Park ◽  
Claire Koerschner ◽  
Jennifer Mawby ◽  
Christopher J. Sonnenday ◽  
...  

2010 ◽  
Vol 85 (9) ◽  
pp. 814-820 ◽  
Author(s):  
Kiran Bambha ◽  
W. Ray Kim ◽  
Charles B. Rosen ◽  
Rachel A. Pedersen ◽  
Cynthia Rys ◽  
...  

2021 ◽  
Vol 35 (6) ◽  
pp. 447-456
Author(s):  
Preet Kamal Kaur ◽  
Kanwal Preet Singh Attwal ◽  
Harmandeep Singh

With the continuous advancements in Information and Communication Technology, healthcare data is stored in the electronic forms and accessed remotely according to the requirements. However, there is a negative impact like unauthorized access, misuse, stealing of the data, which violates the privacy concern of patients. Sensitive information, if not protected, can become the basis for linkage attacks. Paper proposes an improved Privacy-Preserving Data Classification System for Chronic Kidney Disease dataset. Focus of the work is to predict the disease of patients’ while preventing the privacy breach of their sensitive information. To accomplish this goal, a metaheuristic Firefly Optimization Algorithm (FOA) is deployed for random noise generation (instead of fixed noise) and this noise is added to the least significant bits of sensitive data. Then, random forest classifier is applied on both original and perturbed dataset to predict the disease. Even after perturbation, technique preserves required significance of prediction results by maintaining the balance between utility and security of data. In order to validate the results, proposed method is compared with the existing technology on the basis of various evaluation parameters. Results show that proposed technique is suitable for healthcare applications where both privacy protection and accurate prediction are necessary conditions.


Sign in / Sign up

Export Citation Format

Share Document