PD31-05 THE CANADIAN ANATOMIC KIDNEY SCORE: QUANTITATIVE MACROSCOPIC ASSESSMENT VERSUS HISTOLOGICAL GRADING IN PRE-TRANSPLANT EVALUATION OF DONOR KIDNEYS
Bibliographic record
Abstract
You have accessJournal of UrologyCME1 Apr 2023PD31-05 THE CANADIAN ANATOMIC KIDNEY SCORE: QUANTITATIVE MACROSCOPIC ASSESSMENT VERSUS HISTOLOGICAL GRADING IN PRE-TRANSPLANT EVALUATION OF DONOR KIDNEYS Jirong Lu, Juliano Offerni, Danny Matti, Haider Abed, Pavel Roshanov, Alp Sener, and Patrick Luke Jirong LuJirong Lu More articles by this author , Juliano OfferniJuliano Offerni More articles by this author , Danny MattiDanny Matti More articles by this author , Haider AbedHaider Abed More articles by this author , Pavel RoshanovPavel Roshanov More articles by this author , Alp SenerAlp Sener More articles by this author , and Patrick LukePatrick Luke More articles by this author View All Author Informationhttps://doi.org/10.1097/JU.0000000000003324.05AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookLinked InTwitterEmail Abstract INTRODUCTION AND OBJECTIVE: The Canadian Anatomic Kidney Score (CAKS) is a novel grading system that provides a framework for macroscopic description of the donor kidney that can standardize communication between clinicians on the quality of the graft. We hypothesize that the CAKS score can independently predict graft outcomes and correlates with KDPI and histologic assessment. METHODS: Between 2018-2020, donor kidneys were prospectively evaluated using CAKS by assessing the macroscopic appearance of the kidney. CAKS uses set criteria to evaluate the arterial vessel, parenchymal anatomy (presence of cysts and scars), sticky fat, and fibrosis (up to 2 points each for a maximum of 8). Renal implantation core biopsy was performed and histologically graded by Remuzzi score (RS). Neither CAKS nor RS was used to determine donor utility. Pre-operative donor score was also obtained using KDPI. Graft outcomes were prospectively tracked with graft failure defined by graft loss or GFR<30 at one year. RESULTS: 174 patients were analysed. There was a poor correlation between CAKS and RS (r2=0.03). CAKS correlated better with KDPI (r2=0.22) than RS with KDPI (r2=0.06). On logistic regression analysis, both CAKS (OR 1.48, p=0.029) and RS (OR 1.55, p=0.010) independently predicted for graft failure. On subset analysis, vascular features were the strongest predictors of graft failure for both CAKS (OR 2.26, p=0.22) and RS (OR 2.39, p=0.054). CONCLUSIONS: The novel CAKS can be used to predict graft outcomes and correlates well with KDPI scores. We seek to evaluate the replicability of CAKS in other centres and potentially develop composite scores to better predict donor graft function in the future. Source of Funding: None © 2023 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 209Issue Supplement 4April 2023Page: e902 Advertisement Copyright & Permissions© 2023 by American Urological Association Education and Research, Inc.MetricsAuthor Information Jirong Lu More articles by this author Juliano Offerni More articles by this author Danny Matti More articles by this author Haider Abed More articles by this author Pavel Roshanov More articles by this author Alp Sener More articles by this author Patrick Luke More articles by this author Expand All Advertisement PDF downloadLoading ...
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".