Age and Sex Disparities in Discussions About Kidney Transplantation in Adults Undergoing Dialysis
Bibliographic record
Abstract
OBJECTIVES: To explore whether disparities in age and sex in access to kidney transplantation (KT) originate at the time of prereferral discussions about KT. DESIGN: Cross-sectional survey. SETTING: Outpatient dialysis centers in Maryland (n = 26). PARTICIPANTS: Individuals who had recently initiated hemodialysis treatment (N = 416). MEASUREMENTS: Participants reported whether medical professionals (nephrologist, primary medical doctor, dialysis staff) and social group members (significant other, family member, friend) discussed KT with them and, when applicable, rated the tone of discussions. Relative risks were estimated using modified Poisson regression. RESULTS: Participants aged 65 and older were much less likely than those who were younger to have had discussions with medical professionals (44.5% vs 74.8%, P < .001) or social group members (47.3% vs 63.1%, P = .005). Irrespective of sex and independent of race, health-related factors, and dialysis-related characteristics, older adults were more likely not to have had discussions with medical professionals (relative risk (RR) = 1.13, 95% confidence interval (CI) = 1.03-1.24, for each 5-year increase in age through 65; RR = 1.28, 95% CI = 1.14-1.42, for each 5-year increase in age beyond 65). Irrespective of age, women were more likely (RR = 1.45, 95% CI = 1.12-1.89) not to have had discussions with medical professionals. For each 5-year increase in age, men (RR = 1.04, 95% CI = 0.99-1.10) and women (RR = 1.17, 95% CI = 1.10-1.24) were more likely not to have discussions with social group members. Of those who had discussions with medical professionals or social group members, older participants described these discussions as less encouraging (all P < .01). CONCLUSION: Older adults and women undergoing hemodialysis are less likely than younger adults and men to have discussions about KT as a treatment option, supporting a need for better clinical guidelines and education for these individuals, their social network, and their providers.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".