Stage 4 Chronic Kidney Disease

Machine Learning to Compare Frequent Medical Problems of African American and Caucasian Diabetic Kidney Patients

Objectives

End-stage renal disease (ESRD), which is primarily a consequence of diabetes mellitus, shows an exemplary health disparity between African American and Caucasian patients in the United States. Because diabetic chronic kidney disease (CKD) patients of these two groups show differences in their medical problems, the markers leading to ESRD are also expected to differ. The purpose of this study was, therefore, to compare their medical complications at various levels of kidney function and to identify markers that can be used to predict ESRD.

Methods

The data of type 2 diabetic patients was obtained from the 2012 Cerner database, which totaled 1,038,499 records. The data was then filtered to include only African American and Caucasian outpatients with estimated glomerular filtration rates (eGFR), leaving 4,623 records. A priori machine learning was used to discover frequently appearing medical problems within the filtered data. CKD is defined as abnormalities of kidney structure, present for >3 months.

Results

This study found that African Americans have much higher rates of CKD-related medical problems than Caucasians for all five stages, and prominent markers leading to ESRD were discovered only for the African American group. These markers are high glucose, high systolic blood pressure (BP), obesity, alcohol/drug use, and low hematocrit. Additionally, the roles of systolic BP and diastolic BP vary depending on the CKD stage.

Conclusions

This research discovered frequently appearing medical problems across five stages of CKD and further showed that many of the markers reported in previous studies are more applicable to African American patients than Caucasian patients.

Health-related quality of life of children and adolescents with CKD stages 4-5 and their caregivers

BACKGROUND

Renal replacement therapies may affect the quality of life of patients and their primary caregivers (PC).

METHODS

This study describes the perception of health-related quality of life (HRQoL) of children/adolescents with CKD stages 4-5, as well as of their PC (n = 64), in comparison to healthy peers and their PC (n = 129), respectively, based on the Peds QL™ 4.0 and Short Form-36 (SF-36) questionnaires and selected biomarkers.

RESULTS

Patients reported a deleterious impact on physical capacity and on social and school activities. A negative influence on emotional aspects was reported by older patients, but not by their PC. Hemodialysis, followed by peritoneal dialysis, had a more negative impact on patients' physical functioning domain. PC HRQol proxy reports differed from those of their children, especially in older patients. PC of both groups presented similar SF-36 scores. An association was demonstrated between the magnitude of treatment target inadequacies, lower specific dominion scores in the patients/PC proxy reports and PC SF-36 general health scores.

CONCLUSION

The HRQoL of patients with CKD stages 4-5 is negatively affected to different degrees depending on age and treatment modality. The results suggest an association between worsening HRQoL parameters and inadequate control of recognized therapeutic CKD treatment targets.

[Structural equation modeling on quality of life in pre-dialysis patients with chronic kidney disease]

PURPOSE

This study was designed to test structural equation modeling of the quality of life of pre-dialysis patients, in order to provide guidelines for the development of interventions and strategies to improve the quality of life of patients with Chronic Kidney Disease (CKD).

METHODS

Participants were patients who visited the nephrology outpatient department of a tertiary hospital located in Seoul. Data on demographic factors, social support, nutritional status, physical factors and biobehavioral factors and quality of life were collected between March 4 and March 31, 2011.

RESULTS

In the final analysis 208 patients were included. Of the patients 42% were in a malnourished state. Anxious or depressed patients accounted for 62.0%, 72.6%, respectively. Model fit indices for the hypothetical model were in good agreement with the recommended levels (GFI=.94 and CFI=.99). Quality of life in pre-dialysis patients with CKD was significantly affected by demographic factors, social support, nutritional status, physical factors and biobehavioral factors. Biobehavioral factors had the strongest and most direct influence on quality of life of patients with CKD.

CONCLUSION

In order to improve the quality of life in pre-dialysis patients with CKD, comprehensive interventions are necessary to assess and manage biobehavioral factors, physical factors and nutritional status.