Nephrology

Permanent URI for this collectionhttps://wiredspace.wits.ac.za/handle/10539/32807

This collection contains data collected in the course of clinical work in Nephrology across several hospitals In particular , the CMJAH Living Donor Clinic has a long history . You can see that the work of the unit has inspired or directly produced many thesis. We also have a selection of work on transplants. This collection also includes data on kidney disease from other tertiary hospitals in gauteng

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PARTICIPANT NOTICE OF DATA SHARING FOR STUDY TITLED ‘EVALUATION OF POTENTIAL KIDNEY DONORS AND OUTCOMES POST-DONATION AT CHARLOTTE MAXEKE JOHANNESBURG ACADEMIC HOSPITAL (1983-2015)’.

Good day, The Division of Nephrology at Charlotte Maxeke Johannesburg Academic Hospital ( Previously JHB GEN)conducted a research study in the unit’s Living Donor Clinic. The study assessed clinical data of all individuals who presented to this clinic from January 1983 to July 2015. Written permission to access clinical records was obtained from the Human Research Ethics Committee (Medical) of the University of the Witwatersrand, Johannesburg. The purpose of the study was to analyze living kidney donation in the South African setting with the hope that the clinical findings of this research may contribute toward the future betterment of care for all potential kidney donors and that this data may expand upon the limited information available in this important field of study. As a patient belonging to this Living Donor Transplant Community, you have the right to direct how your information is shared for use by research platforms. You may engage with the principal investigator of this study should you have any queries regarding how the data from this study is being applied. You may also withdraw consent to share any information you feel is potentially identifying at any point. Should you require any further information regarding the study, please feel free to contact the principal investigator, Dr Chandni Dayal via email

chandni.dayal@wits.ac.za

or telephonically on 011 489 0467. Please note that prior to accessing your clinical records, approval was obtained from the Human Research Ethics Committee (Medical) of the University of the Witwatersrand, Johannesburg. A principal function of this Committee is to safeguard the rights and dignity of all individuals who are a part of research projects and the integrity of the research. If you have any complaints or concerns over the way the study was conducted, please contact the Chairperson of this Committee who is Dr. Clement Penny, on telephone number 011 717 2301, or by e-mail

Clement.Penny@wits.ac.za

The telephone numbers for the Committee secretariat are 011 717 2700/1234 and the e-mail addresses are Zanele.Ndlovu@wits.ac.za and Rhulani.Mukansi@wits.ac.za Thank you for reading this notice. 11 March 2022 Dr Chandni Dayal

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Author: search.filters.author.Achilonu, Okechinyere JulietEnd date: 2019

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    Modelling graft survival after kidney transplantation using semi-parametric and parametric survival models
    (2017) Achilonu, Okechinyere Juliet
    This study presents survival modelling and evaluation of risk factors of graft survival in the context of kidney transplant data generated in South Africa. Beyond the Kaplan-Meier estimator, the Cox proportional hazard (PH) model is the standard method used in identifying risk factors of graft survival after kidney transplant. The Cox PH model depends on the proportional hazard assumption, which is rarely met. Assessing and accounting for this assumption is necessary before using this model. When the PH assumption is not valid, modi cation of the Cox PH model could o er more insight into parameter estimates and the e ect of time-varying predictors at di erent time points. This study aims to identify the survival model that will e ectively describe the study data by employing the Cox PH and parametric accelerated failure time (AFT) models. To identify the risk factors that mediate graft survival after kidney transplant, secondary data involving 751 adults that received a single kidney transplant in Charlotte Maxeke Johannesburg Academic Hospital between 1984 and 2004 was analysed. The graft survival of these patients was analysed in three phases (overall, short-term and long-term) based on the follow-up times. The Cox PH and AFT models were employed to determine the signi cant risk factors. The purposeful method of variable selection based on the Cox PH model was used for model building. The performance of each model was assessed using the Cox-Snell residuals and the Akaike Information Criterion. The t of the appropriate model was evaluated using deviance residuals and the delta-beta statistics. In order to further assess how appropriately the best model t the study data for each time period, we simulated a right-censored survival data based on the model parameter-estimates. Overall, the PH assumption was violated in this study. By extending the standard Cox PH model, the resulting models out-performed the standard Cox PH model. The evaluation methods suggest that the Weibull model is the most appropriate in describing the overall graft survival, while the log-normal model is more reasonable in describing short-and long-term graft survival. Generally, the AFT models out-performed the standard Cox regression model in all the analyses. The simulation study resulted in parameter estimates comparable with the estimates from the real data. Factors that signi cantly in uenced graft survival are recipient age, donor type, diabetes, delayed graft function, ethnicity, no surgical complications, and interaction between recipient age and diabetes. Statistical inferences made from the appropriate survival model could impact on clinical practices with regards to kidney transplant in South Africa. Finally, limitations of the study are discussed in the context of further studies.
If you, your family member or spouse was involved in the clinic , we urge you to read the notice above. You are welcome to comment on the data, express concerns or ask for changes in how the data is being shared. The library holds data in safekeeping for the researcher, for the community and for the sake of open science. You can contact the curator of the collection: Data Services Librarian: Nina Lewin at email

nina.lewin@wits.ac.za

or telephonically on 0814121940.