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Record W2171743840 · doi:10.1186/s40697-015-0049-6

Strategies to Increase Living Kidney Donation: A Retrospective Cohort Study

2015· article· en· W2171743840 on OpenAlexafffund
Héloïse Cardinal, C. Durand, Sandra Larrivée, Jacobien C. Verhave, M Pâquet, Marie‐Chantal Fortin

Bibliographic record

VenueCanadian Journal of Kidney Health and Disease · 2015
Typearticle
Languageen
FieldMedicine
TopicOrgan Donation and Transplantation
Canadian institutionsUniversité de MontréalCentre Hospitalier de l’Université de Montréal
FundersUniversité de Montréal
KeywordsMedicineRetrospective cohort studyCohortDonationCohort studyKidney transplantationIncidence (geometry)Confidence intervalOrgan donationTransplantationKidney donationSurgeryInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND: Living kidney transplantation (LKT) offers the best medical outcomes for organ recipients. Historically, our centre had a low rate of LKT. In 2009, in an effort to increase living organ donation (LOD), a dedicated team was created. Its mandate was to promote LOD at our centre and at referring centres, to coordinate assessments of living organ donors, to facilitate the process, and to ensure long-term follow-up after the donation. In November 2010, our centre joined the national living donor paired exchange registry (LDPE). OBJECTIVE: To document the impact of the LOD team and LDPE registry on LOD rates at our centre. DESIGN: Retrospective cohort study. SETTING: Single center study in a university hospital with an adult kidney transplant program. PATIENTS: Using our electronic database, we included all potential living organ donors who contacted our centre from 01/01/2005 to 31/12/2008 and from 01/01/2009 to 31/12/2012. Follow-up was conducted until 31/12/2013. MEASUREMENTS: Number of transplantations from living donors, number of potential donors who contacted the centre, donor and recipient characteristics. METHODS: We compared the number of transplantations from living donors performed and the number of potential donors who contacted the centre before and after the creation of the LOD team and participation in the LDPE. RESULTS: A total of 50 renal transplantations were performed using organs from living donors during the first time period, whereas this increased to 73 in the 2009-2012 cohort (incidence rate difference (IRD): 0.030, 95% confidence interval (CI) 0.003-0.056). We also observed a significant increase in the number of individuals who contacted our centre to donate a kidney. During the 2005-2008 period (cohort 1), 191 individuals interested in donating a kidney contacted our centre, whereas this figure was 304 during the 2009-2012 period (cohort 2) (IRD: 0.143, 95% CI 0.091-0.196). LIMITATIONS: Single center study, relatively low sample size. CONCLUSION: The implementation of a LOD team, combined with our participation in the LDPE registry, was associated with a significant increase in the actual number of living kidney transplantations performed. These data support initiatives such as the creation of dedicated LOD teams and LDPE registry to increase LKT.

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

Direct model labels (unvalidated)

Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.

Model armCategoriesStudy designConfidence
gemmano category
Domain: not available · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: no
Observationallow
gptno category
Domain: not available · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: no
Observationallow
models agreeAgreement compares identical category sets and study designs across arms.

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)0.003
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.006
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.002
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
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 head0.018
GPT teacher head0.296
Teacher spread0.277 · 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

Labeled directly by 2 models reading the full record.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations6
Published2015
Admission routes2
Has abstractyes

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