Psychological impact of kidney graft failure and implications for the psychological evaluation of re-transplant candidates
Bibliographic record
Abstract
Approximately 30% of kidney transplant recipients experience a transplant failure during the first 5 years following transplantation. Although transplant failure is experienced as an adverse event, more than two thirds of patients who lose their graft desire another transplantation because it is less intrusive than dialysis and is associated with a better quality of life. We present a review of the scientific literature on the psychological impact of graft loss, and follow with a series of criteria specific to the assessment of re-transplant candidates. The psychological reactions to organ loss that have been identified, ranging from denial to grief, need to be assessed in re-transplant candidates. Moreover, the significance of graft loss for patients, their attitude about re-transplantation, and their motivation to go through surgery once more should be evaluated. Issues of compliance also warrant particular attention. Pre-transplant psychological evaluation of patients who have lost their previous graft is paramount because it can enable detection of psychological morbidity, which, along with risk factors for postoperative noncompliance, should be addressed prior to re-transplantation.
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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 | 0.003 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".