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Record W2749683788 · doi:10.2215/cjn.01470217

A Scoping Review for Strategies to Increase Living Kidney Donation

2017· review· en· W2749683788 on OpenAlexaff
Lianne Barnieh, David Collister, Braden Manns, Ngan N. Lam, Soroush Shojai, Diane Lorenzetti, John S. Gill, Scott Klarenbach

Bibliographic record

VenueClinical Journal of the American Society of Nephrology · 2017
Typereview
Languageen
FieldMedicine
TopicOrgan Donation and Transplantation
Canadian institutionsCentre for Advancing Health OutcomesLibin Cardiovascular Institute of AlbertaMcMaster UniversitySt. Joseph's HospitalUniversity of CalgaryUniversity of British ColumbiaSt. Joseph’s Healthcare HamiltonUniversity of Alberta
Fundersnot available
KeywordsMedicineKidney donationObservational studyPsychological interventionDonationSystematic reviewRandomized controlled trialIntensive care medicineMEDLINEFamily medicineKidney transplantationSurgeryTransplantationNursingInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND AND OBJECTIVES: The literature on strategies to increase the number of potential living kidney donors is extensive and has yet to be characterized. Scoping reviews are a novel methodology for systematically assessing a wide breadth of a given body of literature and may be done before conducting a more targeted systematic review. DESIGN, SETTING, PARTICIPANTS, & MEASUREMENTS: We performed a scoping review and summarized the evidence for existing strategies to increase living kidney donation. RESULTS: , randomized, controlled trials) and outcome measures, all of which focused on using education targeted at potential recipients to increase living donation. Of these, two studies that targeted the potential recipients' close social network reported statistically significant results. Other interventions were identified, but their effect was assessed through quasiexperimental or observational study designs. CONCLUSIONS: We identified an important gap in the literature for evidence-based strategies to increase living kidney donation. From the limited data available, strategies directed at potential recipients and their social networks are the most promising. These results can inform transplant programs that are considering strategies to increase living kidney donation and highlight the need for conduct of high-quality study to increase living donation.

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 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)0.002
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.828
Threshold uncertainty score0.515

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0030.003
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.189
GPT teacher head0.518
Teacher spread0.329 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designOther design
Domainnot available
GenreReview

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

Citations67
Published2017
Admission routes1
Has abstractyes

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