PD31-12 THE CANADIAN ANATOMIC KIDNEY SCORE (CAKS): ASSESSMENT OF REPRODUCIBILITY AMONG SURGEONS AND TRAINEES ACROSS CANADA
Bibliographic record
Abstract
You have accessJournal of UrologyCME1 Apr 2023PD31-12 THE CANADIAN ANATOMIC KIDNEY SCORE (CAKS): ASSESSMENT OF REPRODUCIBILITY AMONG SURGEONS AND TRAINEES ACROSS CANADA William Luke, Juliano Chrystian Mello Offerni, Danny Matti, Haider Abed, Yanbo Guo, Pavel Roshanov, Carol Wang, Alp Sener, and Patrick Luke William LukeWilliam Luke More articles by this author , Juliano Chrystian Mello OfferniJuliano Chrystian Mello Offerni More articles by this author , Danny MattiDanny Matti More articles by this author , Haider AbedHaider Abed More articles by this author , Yanbo GuoYanbo Guo More articles by this author , Pavel RoshanovPavel Roshanov More articles by this author , Carol WangCarol Wang 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.0000000000003324.12AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookLinked InTwitterEmail Abstract INTRODUCTION AND OBJECTIVE: As the Canadian population has aged the gap between renal graft availability and recipient need has continued to widen. Intra-operative organ assessment is known to be associated with organ discard. The Canadian Anatomic Kidney Score (CAKS) is a numeric, multifactorial system, we have shown to be correlated with delayed graft function as well as KDPI. We hypothesize that this system is highly reproducible across clinicians with variable levels of experience, enabling implementation across institutions. METHODS: An anonymous survey was distributed to surgical attendings, fellows and residents at teaching centres across Canada. These surveys contained images of 6 separate kidneys (2 images each) at the time of intra-operative back table dissection. Participant demographics were collected. Images were given scores for 3 factors: vascular (calcifications/location), anatomic (cysts/scars), and sticky fat (proportion of adherent fat); with scores between 0 points (ideal) and 2 points (unfavourable). Respondents were stratified by level of training and specialty. Participant scores were compared in subgroups of residents, fellows and staff using a one way ANOVA. Pair-wise exclusion a Cronbach’s alpha was calculated overall and for each scoring factor RESULTS: Of the 46 respondents, 31 had undergone or were undergoing Urology residency, 12 General Surgery, and 2 Vascular Surgery (Table 1). 61% of participants were attending physicians, 13% fellows and 26% residents. Of the 18 questions during the survey there was no significant difference between fellow, resident and attending scoring except for 2/6 sticky fat image sets (Table 2). Cronbach α=0.98, for overall CAKS. CONCLUSIONS: Overall the CAKS represents a reproducible scoring system across multiple levels of training, in centres across Canada. These scores were reliably generated, despite only 2 images shown of each kidney. Increasing training level correlated with consistency in rating suggesting that this score can capture some degree of surgical judgement. CAKS may offer a concrete system to incorporate clinical judgement into prognostication and graft selection in kidneys with an equivocal KDPI score. Source of Funding: None © 2023 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 209Issue Supplement 4April 2023Page: e905 Advertisement Copyright & Permissions© 2023 by American Urological Association Education and Research, Inc.MetricsAuthor Information William Luke More articles by this author Juliano Chrystian Mello Offerni More articles by this author Danny Matti More articles by this author Haider Abed More articles by this author Yanbo Guo More articles by this author Pavel Roshanov More articles by this author Carol Wang More articles by this author Alp Sener More articles by this author Patrick Luke More articles by this author Expand All Advertisement PDF downloadLoading ...
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.005 | 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".