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Successful Salvage of Kidney Allografts Threatened by Ureteral Stricture Using Pyelovesical Bypass

2010· article· en· W1490656622 on OpenAlexafffund
Raed A. Azhar, Mazen Hassanain, Murad Aljiffry, Saad Aldousari, Tatiana Cabrera, Sero Andonian, Peter Metrakos, Maurice Anidjar, Steven Paraskevas

Bibliographic record

VenueAmerican Journal of Transplantation · 2010
Typearticle
Languageen
FieldMedicine
TopicRenal and Vascular Pathologies
Canadian institutionsRoyal Victoria HospitalMcGill University Health CentreRoyal Victoria Regional Health Centre
FundersMcGill University
KeywordsMedicineSurgeryUrinary systemTransplantationComplicationRefractory (planetary science)Renal functionKidneyUrologyInternal medicine

Abstract

fetched live from OpenAlex

Ureteral stricture is the most common urologic complication after renal transplantation. When endourologic management fails, open ureteral reconstruction remains the standard treatment. The complexity of some of these procedures makes it necessary to explore other means of repair. This study evaluated the intermediate-term outcome of subcutaneous pyelovesical bypass graft (SPBG) on renal transplant recipients. We reviewed 8 patients (6 male and 2 female; mean age 52 years) with refractory ureteral strictures postrenal transplantation, who received SPBG as salvage therapy. All patients failed endourologic management and half failed open management of their strictures. After a mean follow-up of 19.4 months, 7 out of 8 renal grafts have good function with mean GFR of 58.5 mL/min/1.73 m(2), without evidence of obstruction or infection. One patient lost his graft due to persistent infection of the SPBG and one patient developed a recurrent urinary tract infection managed with long-term antibiotics. SPBG offers a last resort in the treatment of ureteral stricture after renal transplantation refractory to conventional therapy.

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)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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)0.0010.000

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 head0.007
GPT teacher head0.268
Teacher spread0.261 · 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 designCase report
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

Citations29
Published2010
Admission routes2
Has abstractyes

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