Expectations and Experiences of Follow-up and Self-Care After Living Kidney Donation
Bibliographic record
Abstract
BACKGROUND: Ensuring donor wellbeing warrants ongoing monitoring after living kidney donation. However, there is considerable variability in donor follow-up processes, including information provided to donors regarding self-care. Loss to follow-up is common, suggesting that the aims and benefits of monitoring and follow-up may not be apparent. We aimed to describe the experiences and expectations of living kidney donors regarding follow-up and self-care after donation. METHODS: Participants from 3 transplant centers in Australia and Canada participated in 14 focus groups (n = 123). Transcripts were analyzed thematically. RESULTS: We identified 4 themes: lacking identification as a patient (invincibility and confidence in health, immediate return to normality, avoid burdening specialty services, redundancy of specialist attention, unnecessary travel), empowerment for health (self-preservation for devastating consequences, self-advocacy and education, needing lifestyle advice, tracking own results), safety net and reassurance (availability of psychosocial support, confidence in kidney-focused care, continuity and rapport, and access to waitlist priority), and neglect and inattention (unrecognized ongoing debilitations, primary focus on recipient, hospital abandonment, overlooking individual priorities, disconnected from system, coping with dual roles, and lacking support for financial consequences). CONCLUSIONS: Living kidney donors who felt well and confident about their health regarded specialist follow-up as largely unnecessary. However, some felt they did not receive adequate medical attention, were prematurely detached from the health system, or held unresolved anxieties about the consequences of their decision to donate. Ongoing access to healthcare, psychosocial support, and education may reassure donors that any risks to their health are minimized.
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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 | 0.011 | 0.021 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.005 | 0.006 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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".