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Record W2018323734 · doi:10.4021/gr249e

Prevention of Biliary Duct Injury in Laparoscopic Cholecystectomy Using Optical Fiber Illumination in Common Bile Duct

2010· article· en· W2018323734 on OpenAlexvenueno aff
Zhi Yong Wang

Bibliographic record

VenueGastroenterology Research · 2010
Typearticle
Languageen
FieldMedicine
TopicGallbladder and Bile Duct Disorders
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineCommon bile ductCystic ductCommon hepatic ductGallbladderCholecystectomyLaparoscopic cholecystectomyBile ductDuct (anatomy)InfundibulumEndoscopic retrograde cholangiopancreatographySurgeryGeneral surgeryAnatomyPancreatitis

Abstract

fetched live from OpenAlex

BACKGROUND: Biliary duct injury (BDI) is one of the most common complications in laparoscopic cholectecystomy (LC), in this study, we have tried to place an illuminating optical fiber via endoscopy in the CBD during LC, the biliary duct anatomy can be clearly delineated, thus CBD injury is avoided. METHODS: Sixteen patients with chronic cholecystitis or/and cholelithiasis from February 2007 to June 2008 were performed LC with placement of optical fiber in CBD, the fiber with cold light illuminates the whole extrahepatic biliary system. Three 6-mm titanium clips were applied to the soft tissue surrounding the hepatic duct, CBD and the cystic duct confluence with CBD, respectively; one titanium clip was applied to the surface of cystic duct near the infundibulum of gallbladder. The cytic duct, CBD and common hepatic duct were clearly identified and delineated in the operating field and LC was performed. RESULTS: All the 16 patients were performed LC using this procedure successfully, there were no LC-related complications, nor complications related to endoscopic retrograde cholangiopanceatography (ERCP). CONCLUSIONS: The endoscopically placed optical fiber in the CBD can clearly identify the CBD, Calot's triangle and the common hepatic duct, this can reduce the bile duct injury in LC and imporve the safety of LC.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.136
Threshold uncertainty score0.494

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 integrity0.0000.001
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 head0.041
GPT teacher head0.390
Teacher spread0.348 · 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
Published2010
Admission routes1
Has abstractyes

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