Identifying the Views and Needs of Family Physicians on Providing Care to Living Kidney Donors: A Cross‐Sectional Survey
Bibliographic record
Abstract
Optimizing the long-term care and follow-up of living kidney donors (LKDs) has been challenging, and prior LKDs have reported suboptimal healthcare experiences. Long-term care of LKDs is largely undertaken by primary care practitioners such as family physicians (FPs). We conducted a cross-sectional survey of Canadian FPs (n = 151). In our sample, 21.9% of participants reported that ≥1 patient had expressed interest in becoming a LKD, and 39.9% provided care to prior LKDs. While 55.5% knew how to find information on living kidney donation, 75.5% reported that information was not available in their practice. Only a minority had formal training in living kidney donation (<5%), and self-reported knowledge was low (median = 3 [scale 1 = not strong to 10 = very strong]). Knowledge improved significantly with educational activities, resources, experience, and practice needs. Attitudes toward living kidney donation were generally favorable with 71.5% stating that FPs should be involved in post-donation care. Clinical care guidelines (78.8%) were the most desired resource, followed by clear communication and reliable contact at transplant centers. Our findings inform the transplant community of an avenue to optimize LKD care by better-supporting FPs, who provide care to LKDs. This may enhance data collection on LKD outcomes and potentially increase donation rates.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".