The profile of patients with chronic kidney disease who regularly present at an Australian general practice

Cytoprotective remedies for ameliorating nephrotoxicity induced by renal oxidative stress

AIMS

Nephrotoxicity is the hallmark of anti-neoplastic drug metabolism that causes oxidative stress. External chemical agents and prescription drugs release copious amounts of free radicals originating from molecular oxidation and unless sustainably scavenged, they stimulate membrane lipid peroxidation and disruption of the host antioxidant mechanisms. This review aims to provide a comprehensive collection of potential cytoprotective remedies in surmounting the most difficult aspect of cancer therapy as well as preventing renal oxidative stress by other means.

MATERIALS AND METHODS

Over 400 published research and review articles spanning several decades were scrutinised to obtain the relevant data which is presented in 3 categories; sources, mechanisms, and mitigation of renal oxidative stress.

KEY-FINDINGS

Drug and chemical-induced nephrotoxicity commonly manifests as chronic or acute kidney disease, nephritis, nephrotic syndrome, and nephrosis. Renal replacement therapy requirements and mortalities from end-stage renal disease are set to rapidly increase in the next decade for which 43 different cytoprotective compounds which have the capability to suppress experimental nephrotoxicity are described.

SIGNIFICANCE

The renal system performs essential homeostatic functions that play a significant role in eliminating toxicants, and its accumulation and recurrence in nephric tissues results in tubular degeneration and subsequent renal impairment. Global statistics of the latest chronic kidney disease prevalence is 13.4 % while the end-stage kidney disease requiring renal replacement therapy is 4-7 million per annum. The remedial compounds discussed herein had proven efficacy against nephrotoxicity manifested consequent to impaired antioxidant mechanisms in preclinical models produced by renal oxidative stress activators.

Clinical decision support system to predict chronic kidney disease: A fuzzy expert system approach

BACKGROUND AND OBJECTIVES

Diagnosis and early intervention of chronic kidney disease are essential to prevent loss of kidney function and a large amount of financial resources. To this end, we developed a fuzzy logic-based expert system for diagnosis and prediction of chronic kidney disease and evaluate its robustness against noisy data.

METHODS

At first, we identified the diagnostic parameters and risk factors through a literature review and a survey of 18 nephrologists. Depending on the features selected, a set of fuzzy rules for the prediction of chronic kidney disease was determined by reviewing the literature, guidelines and consulting with nephrologists. Fuzzy expert system was developed using MATLAB software and Mamdani Inference System. Finally, the fuzzy expert system was evaluated using data extracted from 216 randomly selected medical records of patients with and without chronic kidney disease. We added noisy data to our dataset and compare the performance of the system on original and noisy datasets.

RESULTS

We selected 16 parameters for the prediction of chronic kidney disease. The accuracy, sensitivity, and specificity of the final system were 92.13 %, 95.37 %, and 88.88 %, respectively. The area under the curve was 0.92 and the Kappa coefficient was 0.84, indicating a very high correlation between the system diagnosis and the final diagnosis recorded in the medical records. The performance of the system on noisy input variables indicated that in the worse scenario, the accuracy, sensitivity, and specificity of the system decreased only by 4.43 %, 7.48 %, and 5.41 %, respectively.

CONCLUSION

Considering the desirable performance of the proposed expert system, the system can be useful in the prediction of chronic kidney disease.