Impact of Perioperative Complications on Living Kidney Donor Health-Related Quality of Life and Mental Health: Results From a Prospective Cohort Study
Bibliographic record
Abstract
Background:Although living kidney donation is safe, some donors experience perioperative complications.Objective:This study explored how perioperative complications affected donor-reported health-related quality of life, depression, and anxiety.Design:This research was a conducted as a prospective cohort study.Setting:Twelve transplant centers across Canada.Patients:A total of 912 living kidney donors were included in this study.Measurements:Short Form 36 health survey, Beck Depression Inventory and Beck Anxiety Inventory.Methods:Living kidney donors were prospectively enrolled predonation between 2009 to 2014. Donor perioperative complications were graded using the Clavien-Dindo classification system. Mental and physical health-related quality of life was assessed with the 3 measurements; measurements were taken predonation and at 3- and 12-months postdonation.Results:Seventy-four donors (8%) experienced a perioperative complication; most were minor (n = 67 [91%]), and all minor complications resolved before hospital discharge. The presence (versus absence) of a perioperative complication was associated with lower mental health-related quality of life and higher depression symptoms 3-month postdonation; neither of these differences persisted at 12-month. Perioperative complications were not associated with any changes in physical health-related quality of life or anxiety 3-month postdonation.Limitations:Minor complications may have been missed and information on complications postdischarge were not collected. No minimal clinically significant change has been defined for kidney donors across the 3 measurements.Conclusions:These findings highlight a potential opportunity to better support the psychosocial needs of donors who experience perioperative complications in the months following donation.Trial registration:NCT00319579 and NCT00936078.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".