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Outcomes of Commercial Renal Transplantation: A Canadian Experience

2006· article· en· W2015181703 on OpenAlexaffabout
G. V. Ramesh Prasad, Ashutosh M. Shukla, Michael Huang, R. John D’A. Honey, Jeffrey S. Zaltzman

Bibliographic record

VenueTransplantation · 2006
Typearticle
Languageen
FieldMedicine
TopicOrgan Donation and Transplantation
Canadian institutionsSt. Michael's HospitalUniversity of Toronto
Fundersnot available
KeywordsMedicineDonationLive donorDialysisTransplantationKidney transplantationSurgeryOrgan donationEnd stage renal diseaseIntensive care medicineHemodialysis

Abstract

fetched live from OpenAlex

BACKGROUND: Financial compensation in exchange for live kidney donation is prohibited in Canada. However, patients in Canada with end-stage renal disease and without a suitable biologically or emotionally related live donor face substantial waiting times on lists for deceased donor kidneys, and so may therefore choose to acquire organs from a live donor in a procedure performed outside Canada as part of a commercial transaction. METHODS: We describe the clinical outcomes in such patients transplanted between 1998 and 2005, managed after their surgery at a single Canadian transplant center. RESULTS: Patient and graft survival at three years were significantly worse in this group compared to recipients of live biologically related (P<0.0001) and emotionally related transplants (P<0.01) performed in Canada during this period. A number of different surgical and infectious complications were seen, requiring frequent and often lengthy hospitalization. CONCLUSION: Patients considering this method of acquiring live-donated kidneys should be counseled of the inherent risks and possible adverse outcomes including diminished dialysis-free survival.

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)0.001
metaresearch head score (Gemma)0.002
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 score0.261
Threshold uncertainty score0.525

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0030.001
Scholarly communication0.0010.000
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 head0.013
GPT teacher head0.267
Teacher spread0.254 · 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 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

Citations97
Published2006
Admission routes2
Has abstractyes

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