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Record W4400970007 · doi:10.24875/ciru.24000035

Trasplante de páncreas: revisión

2024· review· es· W4400970007 on OpenAlexaff
Pamela S. Espinoza-Loyola, Luis J. Fernández-López, Paul S. Mogrovejo-Vázquez, Fernando Mondragón-Rodríguez, José A. González-Moreno, Daniel A. Torres-Del Real, Víctor M. Páez-Zayas, Carla A. Escorza-Molina, Abril M. García-Sánchez, Isidoro Aczel Sánchez-Cedillo, Omar Vásquez-Gómez, Óscar Chapa-Azuela, Víctor Visag-Castillo

Bibliographic record

VenueCirugía y Cirujanos · 2024
Typereview
Languagees
FieldMedicine
TopicRenal Transplantation Outcomes and Treatments
Canadian institutionsPancreas Centre (Canada)
Fundersnot available
KeywordsMedicineImmunosuppressionPancreas transplantationPancreasDiabetes mellitusTransplantationSurgeryKidney transplantationUrologyInternal medicineIntensive care medicineEndocrinology

Abstract

fetched live from OpenAlex

Pancreas transplant (PTx) is the only treatment that establishes normal glucose levels for patients diagnosed with diabetes types 1 and 2. The paper aims to review and analyze graft survival, patient survival, and the impact on diabetic complications. We describe that the graft survival was 82-98% at 1 year, 90% at 5 years, and 75-54% at 10 years for simultaneous pancreas-kidney recipient; 71% pancreas after kidney (PAK), and 62% PTx alone at 1 year. Patient survival: At 1 year for recipients was 96.9% simultaneous pancreas-kidney transplantation (SPK); for PAK transplantation recipients, 96.3%; and for PTx alone recipients, 98.3%. In general, the pancreas transplantation improves and reverses diabetic complications. Finally, the pancreatic transplant is a morbid procedure and emerges as a significant alternative in diabetes management, directly competing with conventional insulin therapies. Results so far suggest that the most effective transplant model is the SPK. While more patients could benefit from this procedure, surgical complications and the need for immunosuppression pose significant challenges.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.754
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0040.002
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.019

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 head0.043
GPT teacher head0.368
Teacher spread0.324 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreReview

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

Citations3
Published2024
Admission routes1
Has abstractyes

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