Research Data
Permanent URI for this communityhttps://wiredspace.wits.ac.za/handle/10539/20690
All the data below is licensed under unique access conditions and constraints
News
It not new but its important to note that the NRF demands open access
http://www.nrf.ac.za/media-room/news/statement-open-access-research-publications-national-research-foundation-nrf-funded
Browse
3 results
Search Results
Item Data Set : Prevalence, characterization and response to chronic kidney disease in an urban and rural setting in South Africa(2016-11-18) Naicker, Saraladevi; Fabian, June; Jaya A George; Harriet R Etheredge; Manuel van Deventer; Robert Kalyesubula; Alisha N Wade; Laurie A Tomlinson; Stephen TollmanGlobally, chronic kidney disease (CKD) is an emerging public health challenge but accurate data on its true prevalence are scarce, particularly in poorly resourced regions such as sub-Saharan Africa (SSA). Limited funding for population-based studies, poor laboratory infrastructure and the absence of a validated estimating equation for kidney function in Africans are contributing factors. Consequently, most available studies used to estimate population prevalence are hospital-based, with small samples of participants who are at high risk for kidney disease. While serum creatinine is most commonly used to estimate glomerular filtration, there is considerable potential bias in the measurement of creatinine that might lead to inaccurate estimates of kidney disease at individual and population level. To address this, the Laboratory Working Group of the National Kidney Disease Education Program published recommendations in 2006 to standardize the laboratory measurement of creatinine. The primary objective of this review was to appraise implementation of these recommendations in studies conducted in SSA after 2006. Secondary objectives were to assess bias relating to choice of estimating equations for assessing glomerular function in Africans and to evaluate use of recommended diagnostic criteria for CKD. This study was registered with Prospero (CRD42017068151), and using PubMed, African Journals Online and Web of Science, 5845 abstracts were reviewed and 252 full-text articles included for narrative analysis. Overall, two-thirds of studies did not report laboratory methods for creatinine measurement and just over 80% did not report whether their creatinine measurement was isotope dilution mass spectroscopy (IDMS) traceable. For those reporting a method, Jaffe was the most common (93%). The four-variable Modification of Diet in Renal Disease (4-v MDRD) equation was most frequently used (42%), followed by the CKD Epidemiology Collaboration (CKD-EPI) equation for creatinine (26%). For the 4-v MDRD equation and CKD-EPI equations, respectively, one-third to one half of studies clarified use of the coefficient for African-American (AA) ethnicity. When reporting CKD prevalence, <15% of studies fulfilled Kidney Disease: Improving Global Outcomes criteria and even fewer used a population-based sample. Six studies compared performance of estimating equations to measured glomerular filtration rate (GFR) demonstrating that coefficients for AA ethnicity used in the 4-v MDRD and the CKD-EPI equations overestimated GFR in Africans. To improve on reporting in future studies, we propose an 'easy to use' checklist that will standardize reporting of kidney function and improve the quality of studies in the region. This research contributes some understanding of the factors requiring attention to ensure accurate assessment of the burden of kidney disease in SSA. Many of these factors are difficult to address and extend beyond individual researchers to health systems and governmental policy, but understanding the burden of kidney disease is a critical first step to informing an integrated public health response that would provide appropriate screening, prevention and management of kidney disease in countries from SSA. This is particularly relevant as CKD is a common pathway in both infectious and non-communicable diseases, and multimorbidity is now commonplace, and even more so when those living with severe kidney disease have limited or no access to renal replacement therapy.Item Dataset from: Chronic kidney disease (CKD) and associated risk in rural South Africa: a population-based cohort study(2022-07-13) Fabian, June; Gondwe, Mwawi; Mayindi, Nokthula; Khoza, Bongekile; Gaylard, Petra; Wade, Alisha N.; Gómez‑Olivé, F. Xavier; Tomlinson, Laurie A.; Ramsay, Michele; Tollman, Stephen Meir; Winkler, Cheryl; George, Jaya Anna; Naicker, Saraladevi; Study data were collected and managed using opensource REDCap electronic data capture tools hosted at the University of the WitwatersrandStudy Methods This longitudinal cohort study was conducted from November 2017 to September 2018 in the Medical Research Council (MRC)/Wits Rural Public Health and Health Transitions Research Unit (otherwise referred to as "Agincourt") in Bushbuckridge, a rural subdistrict of the Mpumalanga province in north-eastern South Africa. Agincourt is a Health and Socio-Demographic Surveillance System (HDSS) site that includes approximately 115,000 people. For this study, a minimum sample size of 1800 was required to provide at least 80% power to determine CKD prevalence of at least 5%, provided the true prevalence was equal to or more than 6.5%. Proportional allocation of Black African adults aged 20 to 79 years ensured a representative sample based on the most recent annual population census. Sample size was increased proportionately to 2759 individuals to accommodate a 25% non-participation rate. Dataset is 2022 cases Variables are: 1. age 2. Gender 3. Years of Education (refers to completed years of schooling) 4. Height (cm) (one decimal place) 5. weight (kg) (one decimal place) 6. BMI (body mass index) 7. POC random cholesterol (mmol/L) (2 decimal places) 8. POC random glucose (mmol/L) (1 decimal place) 9. HIV status is: Based on (i) prior HIV testing history OR (ii) HIV PCR testing for ARK 10. Using the urine pregnancy test, is this participant pregnant? ( 11. ERY (erythrocytes, blood) 12. Hb (haemoglobin, blood) LEU (leucocytes) 13. NIT (nitrites) 14. PRO (protein) 15. hepatitis B surface antigen 16. Serum creatinine (umol/L) 17. Systolic BP(1) 18. Diastolic BP (1) 19. Systolic BP(2) 20. Diastolic BP (2) 21. Systolic BP(3) 22. Diastolic BP (3) 23. Serum creatinine (umol/L) 24. Urine microalbumin (mg/L) 25. Urine creatinine (mmol/L) 26. Urine microalbumin (mg/L) 27. Urine creatinine (mmol/L) 28. APOL1 haplotypeItem Dataset from: Clinicopathological correlation of kidney disease in HIV infection pre- and post- ART rollout: VERSION 2(2022-04-14) Diana, Nina Elisabeth; Davies, Malcolm; Mosiane, Pulane; Vermeulen, Alda; Naicker, SaraladeviData note Methods Ethics approval for this study was granted in writing by the Human Research Ethics Committee (Medical) of the University of the Witwatersrand, Johannesburg, South Africa (clearance certificate numbers M1511104, M121184, M120874). This approval permitted a record review of all HIV-positive patients who underwent a kidney biopsy at two tertiary hospitals in Johannesburg within the defined study period. Informed consent for this retrospective record review was waived. Data from included patients was anonymised prior to statistical analysis. Renal biopsies performed at these two tertiary hospitals, on HIV-positive individuals, from January 1989 to December 2014 were retrospectively analysed. Demographic data (age, sex and race), clinical parameters (CD4 count, HIV viral load, serum creatinine and urine protein creatinine ratio), indication for biopsy and renal histological pattern was recorded at time of kidney biopsy. The estimated glomerular filtration rate (eGFR) was calculated according to the CKD-EPI creatinine equation without ethnicity correction. ART rollout began in April 2004 in South Africa. Patients were divided into 2 groups - those who were biopsied pre-ART rollout and those biopsied post-ART rollout. These two groups were compared with respect to the above parameters. In a subgroup of the patients biopsied between 2004 and 2014, additional data laboratory parameters (serum haemoglobin, serum albumin, serial serum creatinine and eGFR) and ART use (at time of biopsy) were recorded. All renal biopsies were processed according to standard techniques for light microscopy, immunofluorescence and electron microscopy. All biopsies were reviewed by the National Health Laboratory Service histopathology team who were aware of the HIV status of the patient at time of biopsy. Histological diagnoses were tabulated using the 2018 Kidney Disease Improving Global Outcomes (KDIGO) Controversies Conference guidelines. As per this guideline FSGS (NOS) in the setting of HIV describes all non-collapsing forms of FSGS. Those ICGN with no identifiable comparative etiology other than HIV were categorized as uncharacterized ICGN with no etiology other than HIV. The biopsies with multiple diagnoses were assigned its major clinical-pathological diagnosis for the purposes of analysis. All data was collected by Dr Nina Diana and Dr Alda Vermeulen from paper based patient hospital records and the electronic hospital laboratory system. All data was checked twice to ensure accuracy. Each patient was allocated a study number and data anonymised prior to entry into Microsoft Excel. Shapiro Wilk W testing and visual inspection of the histogram plot indicated non-parametric distribution of baseline characteristics of the cohort; accordingly, central and dispersal measurements were described using the median and interquartile range (IQR), and the Kruskal Wallis ANOVA and Mann-Whitney U tests were used for comparative analyses. Kidney survival, defined by an eGFR above threshold for consideration for dialysis initiation in these institutions (15mL/min/1.73m²), censored for patient default with preserved function, was fitted for patients in the subgroup using the Kaplan Meyer method; histological diagnoses were compared using Log-rank testing.