{"id":{"repo_id":"cape-town","oai_identifier":"oai:open.uct.ac.za:11427/42407"},"canonical_url":"https://search.dev.ndltd.org/etd/cape-town/oai:open.uct.ac.za:11427/42407","repository":{"repo_id":"cape-town","name":"University of Cape Town","base_url":"https://open.uct.ac.za/oai/request"},"display":{"title":"Renal allograft biopsies at Groote Schuur Hospital: a histopathologic descriptive study with molecular insights","abstract":"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.","abstract_html":"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.","abstract_has_math":false,"creators":["Lunn, Jarryd"],"institution":"Department of Pathology","degree_name":null,"degree_level":null,"degree_discipline":null,"degree_department":null,"school":null,"contributors":[],"advisors":["Price, Brendon","Chetty, Dharshnee","Ikumi, Nadia"],"committee_chairs":[],"committee_members":[],"year":2025,"date_issued":"2025","date_published":"2025","updated_at":"2026-07-22T22:23:34Z","subjects":["Renal transplantation","Banff 2022 classification","renal rejection prevalence","rejection biomarkers","digital pathology algorithm","C4d-DSA prediction","Antibody mediated rejection","T-cell mediated rejection"],"languages":["en"],"rights":[],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"http://hdl.handle.net/11427/42407","outbound_label":"Handle","outbound_source":"dc:identifier.uri"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor.advisor","label":"Advisor","values":["Price, Brendon","Chetty, Dharshnee","Ikumi, Nadia"]},{"key":"dc:creator","label":"Author","values":["Lunn, Jarryd"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.accessioned","label":"Dc Date Accessioned","values":["2025-12-05T07:14:56Z"]},{"key":"dc:date.available","label":"Dc Date Available","values":["2025-12-05T07:14:56Z"]},{"key":"dc:date.issued","label":"Date","values":["2025"]},{"key":"dc:publisher.department","label":"Dc Publisher Department","values":["Department of Pathology"]},{"key":"dc:publisher.institution","label":"Dc Publisher Institution","values":["University of Cape Town"]},{"key":"dc:type","label":"Dc Type","values":["Thesis / Dissertation"]},{"key":"dc:type.qualificationlevel","label":"Dc Type Qualificationlevel","values":["Masters","MMed"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Renal transplantation","Banff 2022 classification","renal rejection prevalence","rejection biomarkers","digital pathology algorithm","C4d-DSA prediction","Antibody mediated rejection","T-cell mediated rejection"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language.iso","label":"Language (ISO)","values":["en"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier.uri","label":"Identifier URI","values":["http://hdl.handle.net/11427/42407"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["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."]},{"key":"dc:title","label":"Title","values":["Renal allograft biopsies at Groote Schuur Hospital: a histopathologic descriptive study with molecular insights"]}]}],"canonical_facts":{"dc:contributor.advisor":["Price, Brendon","Chetty, Dharshnee","Ikumi, Nadia"],"dc:creator":["Lunn, Jarryd"],"dc:date.accessioned":["2025-12-05T07:14:56Z"],"dc:date.available":["2025-12-05T07:14:56Z"],"dc:date.issued":["2025"],"dc:description.abstract":["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."],"dc:identifier.uri":["http://hdl.handle.net/11427/42407"],"dc:language.iso":["en"],"dc:publisher.department":["Department of Pathology"],"dc:publisher.institution":["University of Cape Town"],"dc:subject":["Renal transplantation","Banff 2022 classification","renal rejection prevalence","rejection biomarkers","digital pathology algorithm","C4d-DSA prediction","Antibody mediated rejection","T-cell mediated rejection"],"dc:title":["Renal allograft biopsies at Groote Schuur Hospital: a histopathologic descriptive study with molecular insights"],"dc:type":["Thesis / Dissertation"],"dc:type.qualificationlevel":["Masters","MMed"]},"updated_at":"2026-07-22T22:23:34Z"}