Gender Differences in Medication Adherence Among Adolescent and Young Adult Kidney Transplant Recipients
Bibliographic record
Abstract
BACKGROUND: Among kidney transplant recipients, gender differences in medication adherence may contribute to higher graft failure risks observed in girls and young women compared with boys and young men. Our aim was to determine whether adherence differs by gender, and whether gender differences vary by age in adolescent and young adult kidney transplant recipients. METHODS: We examined data from the 3-month run-in period (no intervention) of the randomized Teen Adherence in Kidney transplant Effectiveness of Intervention trial. Adherence was monitored using electronic pillboxes in 136 patients (11-24 y) followed in 8 transplant centers in Canada and the United States. We used ordinal logistic regression with generalized estimating equations to estimate the association between gender and each of daily taking (proportion of prescribed doses taken) and timing (proportion of prescribed doses taken on time) adherence, considering effect modification by age (11-16 y vs 17-24 y). RESULTS: No difference in taking adherence was observed by gender among participants aged 11 to 16 years (odds ratio [OR], 0.92; 95% confidence interval [CI], 0.55-1.54), whereas among participants aged 17 to 24 years, women had significantly greater odds of higher taking adherence scores (OR, 3.03; 95% CI, 1.20-7.66) than men. Results were similar for timing adherence, with no difference among participants aged 11 to 16 years (OR, 1.03; 95% CI, 0.65-1.63) but a greater odds of higher timing adherence scores in women than in men among participants aged 17 to 24 years (OR, 3.26; 95% CI, 1.43-7.45). There were no differences in adherence assessed by self-report or SD of tacrolimus trough levels. CONCLUSIONS: Gender differences in adherence vary by age. Whereas younger adolescents show no adherence differences by gender, young women show much better adherence than young men.
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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 | 0.003 |
| 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) | 0.001 | 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".