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Record W4408567436 · doi:10.1007/s00467-025-06661-0

Bariatric surgery as bridging therapy to kidney transplantation

2025· article· en· W4408567436 on OpenAlexaff
Anke Raaijmakers, Belinda Dooley, Blake Sandery, Swasti Chaturvedi, Renee Le Jambre, David Links, Seán Kennedy

Bibliographic record

VenuePediatric Nephrology · 2025
Typearticle
Languageen
FieldMedicine
TopicRenal Transplantation Outcomes and Treatments
Canadian institutionsBC Children's HospitalUniversity of British Columbia
FundersUniversity of New South Wales
KeywordsMedicinePeritoneal dialysisNephrologyDialysisKidney transplantationTransplantationSurgeryWeight lossObesityIntensive care medicineInternal medicine

Abstract

fetched live from OpenAlex

Abstract The prevalence of obesity in adolescents is rising, including in those with kidney failure. Obesity increases the risk of complications during dialysis and may be associated with poorer outcomes after transplantation. Bariatric surgery has been found safe and effective in adults on dialysis. This Clinical Insights is about a 14-year-old female with kidney failure and obesity. She was initially managed on peritoneal dialysis but subsequently gained further weight. Multiple interventions for weight loss were unsuccessful, including the switch to haemodialysis. The patient underwent laparoscopic sleeve gastrectomy after extensive multidisciplinary assessment. She lost > 30 kg over 6 months (BMI decreased from 48 to 32 kg/m 2 ) which made it possible for her to be activated on the deceased donor kidney transplant waiting list. Managing weight gain in patients on peritoneal dialysis is important, especially in obese adolescents. Bariatric surgery should be considered early where morbid obesity is a major impediment to listing for kidney transplantation.

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)0.000
metaresearch head score (Gemma)0.000
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 score0.017
Threshold uncertainty score0.577

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
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 head0.015
GPT teacher head0.293
Teacher spread0.278 · 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

Citations2
Published2025
Admission routes1
Has abstractyes

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