Browsing by Subject "Renal transplantation"

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    Renal allograft biopsies at Groote Schuur Hospital: a histopathologic descriptive study with molecular insights
    (2025) Lunn, Jarryd; Price, Brendon; Chetty, Dharshnee; Ikumi, Nadia
    Background: Kidney transplantation is the definitive treatment for end-stage kidney disease. Immune-mediated rejection remains a barrier to success. It is diagnosed through the Banff classification, which incorporates histopathology and biomarkers (C4d/donor specific antibodies (DSA)). In resource-limited settings, DSA testing can be challenging, necessitating reliable alternatives. Aim: This study evaluated: (1) rejection patterns at our hospital; (2) the impact of the Banff 2022 criteria with a computer-assisted tool; and (3) the utility of C4d as a predictor of DSA status. Methods: We analysed 197 for-cause historic biopsy reports between 2015-2022 for details of rejection- and non-rejection pathologies, Banff lesion scores and DSA status. A computer- based tool was used on historic data to re-calculate Banff 2022 classification diagnoses, which were compared to historic diagnoses. Logistic regression assessed C4d as a predictor of DSA. Results: The cohort showed a male predominance (59.3%). Sixty-three percent of cases showed non-rejection pathology, with acute tubular injury and pyelonephritis being the most frequent. TCMR was the most common form of rejection (17.3%), with AMR being the least common (7.6%). The computer-based tool demonstrated agreement of 92.4% for AMR/TCMR and 84.6% of borderline TCMR, but was confounded by non-rejection pathologies. C4d predicted DSA-positivity with 95% specificity but only 29.5% sensitivity. Conclusion: The Banff 2022 criteria were additive in rejection diagnosis, with a computer-based tool acting as a guide but not a pure diagnostic tool. The high specificity of C4d makes it valuable where DSA testing is limited. Contribution: This study validates the role of the Banff 2022 in our setting, aided by a computer-based tool that aims to decrease logical- and transcription errors when using the complex Banff classification. It also demonstrates C4d's role as a practical DSA proxy, offering actionable solutions in resource-limited settings.
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    Risk models to predict chronic kidney disease and its progression: a systematic review
    (Public Library of Science, 2012) Echouffo-Tcheugui, Justin B; Kengne, Andre P
    A systematic review of risk prediction models conducted by Justin Echouffo-Tcheugui and Andre Kengne examines the evidence base for prediction of chronic kidney disease risk and its progression, and suitability of such models for clinical use.
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    Use of the 'Accountability for Reasonableness' Approach to Improve Fairness in Accessing Dialysis in a Middle-Income Country
    (Public Library of Science, 2016) Moosa, Mohammed Rafique; Maree, Jonathan David; Chirehwa, Maxwell T; Benatar, Solomon R
    Universal access to renal replacement therapy is beyond the economic capability of most low and middle-income countries due to large patient numbers and the high recurrent cost of treating end stage kidney disease. In countries where limited access is available, no systems exist that allow for optimal use of the scarce dialysis facilities. We previously reported that using national guidelines to select patients for renal replacement therapy resulted in biased allocation. We reengineered selection guidelines using the 'Accountability for Reasonableness' (procedural fairness) framework in collaboration with relevant stakeholders, applying these in a novel way to categorize and prioritize patients in a unique hierarchical fashion. The guidelines were primarily premised on patients being transplantable. We examined whether the revised guidelines enhanced fairness of dialysis resource allocation. This is a descriptive study of 1101 end stage kidney failure patients presenting to a tertiary renal unit in a middle-income country, evaluated for dialysis treatment over a seven-year period. The Assessment Committee used the accountability for reasonableness-based guidelines to allocate patients to one of three assessment groups. Category 1 patients were guaranteed renal replacement therapy, Category 3 patients were palliated, and Category 2 were offered treatment if resources allowed. Only 25.2% of all end stage kidney disease patients assessed were accepted for renal replacement treatment. The majority of patients (48%) were allocated to Category 2. Of 134 Category 1 patients, 98% were accepted for treatment while 438 (99.5%) Category 3 patients were excluded. Compared with those palliated, patients accepted for dialysis treatment were almost 10 years younger, employed, married with children and not diabetic. Compared with our previous selection process our current method of priority setting based on procedural fairness arguably resulted in more equitable allocation of treatment but, more importantly, it is a model that is morally, legally and ethically more defensible.