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Record W2002760882 · doi:10.4236/ss.2011.21001

Pancreas Transplant Salvage by Proximal Loop Ileostomy and Distal Ileostotomy Tube for Duodenal Stump Leak after Enteric Conversion

2011· article· en· W2002760882 on OpenAlexaff
Mauricio Monroy‐Cuadros, Rodriguez-Velez Cesar

Bibliographic record

VenueSurgical Science · 2011
Typearticle
Languageen
FieldMedicine
TopicOrgan Transplantation Techniques and Outcomes
Canadian institutionsFoothills Medical Centre
Fundersnot available
KeywordsMedicineSurgeryPancreasAnastomosisPancreatitisIleostomyLeakAcute pancreatitisMetabolic acidosisInternal medicine

Abstract

fetched live from OpenAlex

After pancreas transplantation, some patients with bladder drainage (BD) of the pancreatic duct will need to be converted to enteric drainage (ED) because of reflux pancreatitis, metabolic acidosis, and urological complications. However, ED is associated with higher rates of duodenal stump leak, intra-abdominal abscess, and peritonitis. In some cases of enteric anastomosis leakage, a primary repair can be attempted, but in more severe cases, graft pancreatectomy is indicated. We report one patient who received a combined kidney and pancreas transplant with BD of exocrine secretions, but who required ED conversion 6 years later because of persistent metabolic acidosis and adverse urological symptoms. However, a significant duodenal leak was discovered 4 days post-operatively. To salvage the transplanted pancreas, we performed a diverting loop ileostomy proximal to the entero-entero anastomosis and the distal section was drained retrogradely with an ileostostomy tube, allowing the area of the leak to heal. Three months later, the ileostomy was reversed without complications, the symptoms that led to the ED conversion resolved, and the kidney and pancreas allografts remain functional 48 months later. We suggest that this might be a method by which transplanted pancreas may be salvaged in the case of leakage after ED conversion.

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 score0.301
Threshold uncertainty score0.462

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.013
GPT teacher head0.252
Teacher spread0.239 · 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

Citations12
Published2011
Admission routes1
Has abstractyes

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