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Evidence for a need to mandate kidney transplant living donor registries

2008· article· en· W1576297016 on OpenAlexaff
Mahmoud Emara, Ahmed Ragheb, Abubaker Hassan, Ahmed Shoker

Bibliographic record

VenueClinical Transplantation · 2008
Typearticle
Languageen
FieldMedicine
TopicOrgan Donation and Transplantation
Canadian institutionsUniversity of SaskatchewanRoyal University Hospital
Fundersnot available
KeywordsMedicineKidney donationIntensive care medicineDonationKidney transplantationKidneyTransplantationKidney diseaseOrgan donationInternal medicine

Abstract

fetched live from OpenAlex

Kidney disease is a global public health problem of growing proportions. Currently the best treatment for end-stage renal failure is transplantation. Living organ donation remains a complex ethical, moral and medical issue. It is based on a premise that kidney donation is associated with short-term minimal risks to harm the donor, and is outweighed by the definite advantages to the recipient. A growing number of patients with end-stage renal disease and shortage of kidney donors poses a pressing need to expand the criteria needed to accept kidney donors. The current donor registries are structured and are driven to expand donor pool. As living kidney donation is not without risks, more attention should be given to protect the donor health. After kidney donation, mild to moderate renal insufficiency may occur. Renal insufficiency, even mild, is associated with increased risks of hypertension, proteinuria and cardiovascular morbidity. We, therefore, foresee a need to mandate the establishment of renal transplant donor registries at all transplanting programs as a prerequisite to protect the long-term well being of kidney donors. These registries can collect the database necessary to develop standards of practice and guidelines for future kidney 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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.220
Threshold uncertainty score0.732

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.199
GPT teacher head0.411
Teacher spread0.212 · 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 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

Citations8
Published2008
Admission routes1
Has abstractyes

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