Losing Much More Than a Transplant: A Qualitative Study of Kidney Transplant Recipients’ Experiences of Graft Failure
Bibliographic record
Abstract
Introduction: Kidney transplant recipients with graft failure are a growing cohort of patients who experience high morbidity and mortality. Limited evidence guides their care delivery and patient perspective to improve care processes is lacking. We conducted an in-depth exploration of how individuals experience graft failure, and the specific research question was: "What impact does the loss of an allograft have on their lives?" Methods: We adopted an interpretive descriptive methodological design. Semistructured in-depth narrative interviews were conducted with adult recipients who had a history of ≥1 graft failure. Data were collected until data saturation was achieved and analyzed using an inductive and thematic approach. Results: Our study included 23 participants from 6 provinces of Canada. The majority were on dialysis and not waitlisted for retransplantation (60.9%). Our thematic analysis identified that the lives of participants were impacted by a range of tangible and experiential losses that go beyond the loss of the transplant itself. The themes identified include loss of control, loss of coherence, loss of certainty, loss of hope, loss of quality of life, and loss of the transplant team. Although many perceived that graft failure was inevitable, the majority were unprepared. The confusion about eligibility for retransplantation appears to contribute to these experiences. Conclusion: Individuals with graft failure experience complex mental and emotional challenges which may contribute to poor outcomes. The number of patients with graft failure globally is increasing and our findings can help guide practices aimed at supporting and guiding them toward self-management and adaptive coping.
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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 | 0.016 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.016 | 0.015 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.003 | 0.007 |
| Research integrity | 0.002 | 0.005 |
| 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".