Familial Consent for Deceased Organ Donation Among Immigrants and Long-term Residents in Ontario, Canada: A Population-Based Retrospective Cohort Study
Bibliographic record
Abstract
BACKGROUND: Many families choose not to consent to organ donation at the time of their loved one's death. In Ontario, Canada, whether these decisions vary by ethnicity remains unclear. OBJECTIVE: To compare the proportion of families of immigrants who consented for deceased organ donation with families of long-term residents. DESIGN: Population-based retrospective cohort study. SETTING: Potential donors in Ontario, Canada, between November 2008 and March 2013. METHODS: We used linked administrative databases to study the proportion of families who consented for deceased organ donation. RESULTS: Overall, of the 2873 families of potential donors approached, 1912 (67%) provided consent for deceased organ donation. Families of immigrants were less likely to provide consent compared with families of long-term residents (46% [135 of 291] vs 69% [1777 of 2582]; adjusted rate ratio (RR): 0.72; 95% confidence interval [CI]: 0.63-0.81). When examined by the country of birth, families of immigrants from the following regions were less likely to consent to organ donation compared with long-term residents: South Asia (RR: 0.71; 95% CI: 0.55-0.91), East Asia and Pacific (RR: 0.68; 95% CI: 0.53-0.88) and Middle East, North Africa, and sub-Saharan Africa (RR: 0.58; 95% CI: 0.37-0.91). LIMITATIONS: We could not determine why consent was not obtained. We had a small sample of immigrants. We only had access to the potential donors' information and not the family member who was approached for consent. Many characteristics that we examined were nonmodifiable (eg, age, sex). CONCLUSIONS: In Ontario, families of immigrants are less likely to consent to deceased organ donation. There is an opportunity to better understand the reasons for lower consent among certain immigrant groups.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".