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Long-Term Risks of Living Kidney Donation: State of the Evidence and Strategies to Resolve Knowledge Gaps

2025· review· en· W4406863146 on OpenAlex
Vidya A. Fleetwood, Ngan N. Lam, Krista L. Lentine

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueAnnual Review of Medicine · 2025
Typereview
Languageen
FieldMedicine
TopicOrgan Donation and Transplantation
Canadian institutionsUniversity of Calgary
FundersNational Institute of Diabetes and Digestive and Kidney Diseases
KeywordsKidney donationMedicineDonationPsychosocialKidney transplantationIntensive care medicineKidney diseaseDiseaseTransplantationSurgeryInternal medicinePsychiatry

Abstract

fetched live from OpenAlex

Living-donor kidney transplantation is the preferred treatment for kidney failure. In the United States, rates of living kidney donation have been stagnant, which is partly related to concerns over medical and financial risks. Recent research has better characterized the risks of living kidney donation, although the field is limited by a lack of robust registries. Available evidence supports small increases in the risks of end-stage kidney disease and hypertensive disorders of pregnancy in living donors. For most donors, the 15-year risk of kidney failure is less than 1%, but for certain populations this risk may be higher. New tools such as genetic kidney disease panels may assist with risk stratification. Living kidney donors generally have similar or improved psychosocial health following donation compared to prior to donation and nondonor experience. Postdonation care allows for preventative care measures to mitigate risk as well as ongoing surveillance of donor outcomes. Continuing efforts to capture and report outcomes of living donation are necessary to safely expand living donation worldwide.

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.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.006
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.466
Threshold uncertainty score0.694

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.082
GPT teacher head0.445
Teacher spread0.364 · 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