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Record W4408446704 · doi:10.1177/20543581251324548

“They Know You Better Than the Transplant Team”: An Interpretive Description Study Exploring the Perspectives of Living Kidney Donors About Care Received From Family Physicians

2025· article· en· W4408446704 on OpenAlexaffabout
Katya Loban, Charo Rodríguez, Antoine Przybylak‐Brouillard, Elie Fadel, Heather Badenoch, Peter Nugus, Ann Bugeja, Justin Gill, Marie‐Chantal Fortin, Emilie Trinh, Scott McKay, Shaifali Sandal

Bibliographic record

VenueCanadian Journal of Kidney Health and Disease · 2025
Typearticle
Languageen
FieldMedicine
TopicOrgan Donation and Transplantation
Canadian institutionsWestern UniversityUniversity of OttawaOttawa HospitalCentre Hospitalier de l’Université de MontréalMcGill UniversityUniversity of British ColumbiaTranslational Research in OncologyMcGill University Health Centre
Fundersnot available
KeywordsMedicineThematic analysisDonationQualitative researchFamily medicineKidney donationHealth careTransplantationNursingOrgan donationKidney transplantationSurgery

Abstract

fetched live from OpenAlex

Background: Given the significant benefits of living donor kidney transplantation, the nephrology and transplant communities are augmenting efforts to increase living kidney donation. However, prior living kidney donors (LKDs) report suboptimal experiences and unmet care needs. The LKDs are healthy, and the vast majority have good outcomes post-donation. Thus, in clinical practice, their care is primarily assumed by practitioners, such as family physicians (FPs). Objective: This study aimed to better understand the integration of primary care in LKDs' donation trajectory from the point of view of the latter. Our specific research questions were: (1) How do LKDs perceive the role of FPs currently integrated into the donation trajectory? (2) What are their needs and expectations from their FPs? Design: An interpretive description methodology. Setting and Participants: Canadian LKDs who donated a kidney prior to 2020. Methods: Qualitative interviews and inductive thematic analysis. Results: In our sample of 49 LKDs who donated between 2007 and 2020, 61.2% were women and 87.8% were white. Also, 87.8% and 83.7% were attached to an FP pre- and post-donation (1 by a nurse practitioner) with 16.3% reporting no regular FP post-donation. Although participants provided varying accounts, an overwhelming majority described challenges with timely access to needed care; lack of cohesive continuity of care; variability in the services offered by FPs; and challenges with coordination of care between providers. Many reported poor coordination and communication between FPs and donor teams. Most articulated the desire to see an expanded role for FPs. This included improvements in knowledge regarding living donor care, information and care brokerage, continuous integrative care, and mental and emotional support. Limitations: Limited transferability of our findings to other countries with variable payment structures. Conclusions: Our work suggests that improving LKD care requires developing care pathways that facilitate donor transition and care coordination between donor teams and primary care practitioners. Given the challenges being faced by primary care in Canada, we believe that pragmatic strategies to better support primary care practitioners and a stronger integration of primary care with the living kidney donation process are essential. In addition, strategies to better support the mental health of LKDs are also needed. The LKDs provide a valuable gift to our health systems and to patients with kidney failure. It is our responsibility to optimize their experiences and improve their care.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.024
metaresearch head score (Gemma)0.040
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.111
Threshold uncertainty score0.222

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0240.040
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0150.017
Scholarly communication0.0070.007
Open science0.0030.007
Research integrity0.0020.005
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.016
GPT teacher head0.267
Teacher spread0.251 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

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".

Quick stats

Citations2
Published2025
Admission routes2
Has abstractyes

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