#3144 KIDNEY TRANSPLANT-RELATED KNOWLEDGE AMONG SOUTH ASIAN COMPARED TO WHITE CANADIAN PATIENTS
Bibliographic record
Abstract
Abstract Background and Aims Kidney transplant (KT) is the best treatment for many patients with kidney failure. However, patients from racialized communities are less likely to receive KT. Gaps in transplant-related knowledge may be one of the potential reasons for the observed inequities in accessing KT. Here we compare patient characteristics and KT-related knowledge between South Asian (SA) versus white Canadians with kidney failure using the “Knowledge Assessment of Renal Transplantation” (KART) questionnaire. Method Secondary analysis of data from a cross-sectional convenience sample of white and SA adults with kidney failure. Sociodemographic data, self-reported information about racialized status and KART score were collected through electronic data capture. The association between racialized status and participant demographics were assessed using ANOVA, Kruskal–Wallis test or chi squared test, as appropriate. The independent association between racialized status and KART scores was assessed by multivariable adjusted linear or multinomial logistic regression, with adjustment for immigration status, age, marital status, education, gender, Ontario Marginalization Index material deprivation quintile, Charlson Comorbidity Index and ethnicity. Results Among 578 participants (mean [SD] age: 57 [14] years, 64% male), 43% were white and 16% were SA. 84% vs 27% of SA vs white participants were immigrants. The Charlson Comorbidity Index score was >=4 for of 31[40%] SA vs 105[51%] white participants (p<0.001). The median (interquartile range) KART score of white vs SA participants was 17[6] vs 14[7] (p<0.001). In a univariable linear regression model the KART score was significantly associated with SA status (B: -3.27 ([95% CI]: -4.76, -1.77, p<0.001). This association remained significant after adjustment for potential confounding (B: -3.36 ([95% CI]: -5.05, -1.67, p<0.001) (Table 1). 26% of SA vs. 41% of white participants scored in the highest tertile for KART score (p<0.001) (Fig. 1). The relative risk ratio to be in the lowest KART tertile was 3.09 [95% CI: 1.49, 6.43] for SA compared to white participants in our final, adjusted multinomial model. Conclusion SA participants with kidney failure are commonly immigrants who have poorer KT-related knowledge compared to white participants. Our findings indicate the need to develop culturally relevant KT related patient education for South Asian Canadian communities.
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 machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".