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Record W2019700091 · doi:10.1159/000279811

A Novel Technique for the Management of Pancreaticojejunal Anastomosis Dehiscence following Pancreaticoduodenectomy

2010· article· en· W2019700091 on OpenAlexaff
Xianmin Bu, Jin Xu, Xian-wei Dai

Bibliographic record

VenueDigestive Surgery · 2010
Typearticle
Languageen
FieldMedicine
TopicPancreatic and Hepatic Oncology Research
Canadian institutionsPancreas Centre (Canada)
Fundersnot available
KeywordsMedicinePancreaticoduodenectomyAnastomosisDehiscenceSurgeryPancreatic ductBowel functionPancreasPancreatectomyGeneral surgeryInternal medicineResectionPancreatitis

Abstract

fetched live from OpenAlex

BACKGROUND: To report a novel technique for management of pancreaticojejunal anastomosis dehiscence after pancreaticoduodenectomy. MATERIAL AND METHODS: The anastomosis is disconnected and the blind jejunal limb is shortened and closed. A silicon tube in the pancreatic duct introduced in the first operation is fixed at the pancreatic stump. If no tube was placed during pancreaticoduodenectomy, it is placed at reoperation. The transected edge of the pancreas is stitched, and the distal part of the silicon tube is inserted into the jejunal loop and fixed in the jejunal wall. Drains and a catheter for continuous irrigation are placed. RESULTS: All patients tolerated reoperation and experienced unremarkable postoperative courses. Follow-up ranged from 5 to 27 months, and all patients exhibited normal pancreatic function and no pseudocyst formation. CONCLUSION: This technique is an effective method for management of pancreaticojejunal anastomosis dehiscence that avoids complications associated with completion pancreatectomy and preserves pancreatic function.

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 score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.040
GPT teacher head0.335
Teacher spread0.296 · 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

Citations8
Published2010
Admission routes1
Has abstractyes

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