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Record W2009680135

Efficacy of Fibrin Glue and Polyglactin Acid Sheet for Pig Liver Resection Model

2012· article· en· W2009680135 on OpenAlexvenueno aff
Mitsugi Shimoda, Masato Kato, Yoshimi Iwasaki, Keiichi Kubota

Bibliographic record

VenueJournal of Current Surgery · 2012
Typearticle
Languageen
FieldDentistry
TopicOral and Maxillofacial Pathology
Canadian institutionsnot available
Fundersnot available
KeywordsFibrin glueMedicineGLUEHepatectomySurgeryParenchymaFibrinLiver parenchymaLiver tissueBile acidResectionPathologyInternal medicine
DOInot available

Abstract

fetched live from OpenAlex

Background: Fibrin glue is commonly used to prevent bile leakage and bleeding after hepatectomy in clinical cases. Recently, several liver centers try to use polyglactin acid sheet for preventing bile leakage and bleeding in Japan. However, there is no evidence of its efficacy and safety when applied to cut liver surface after surgery. Therefore we evaluated the efficacy of fibrin glue and polyglactin acid sheet using pig liver resection model. Methods: A chevron incision was performed under general anesthesia, followed by the left hemi-hepatectomy (approximately 40%), using pig liver. Pigs were subsequently allocated randomly into 2 groups (n = 5 in both); in group A, a fibrin glue (Bolheal) with polyglactin acid sheet (Neoveil) was applied to the cut surface and in group B only Bolheal was applied. After one month, we evaluated histological findings and incidence of biloma or inflammatory change at the cut surface. Results: All of the 5 pigs in group A had fibrotic capsulated cavity at the cut surface. Inside of those cavities included necrotic liver tissues, Bolheal, and peace of Neoveil with bile juice. Histologically, Neoveil and Bolheal remained in the fibrotic tissue in normal liver tissue. In group B, only one pig had abscess at cut surface. Other four pigs showed no histological problems; Bolheal was completely integrated into the normal liver parenchyma.  Conclusion: Bolheal was very effective for liver cut surface in this experimental study. Neoveil should not be applied for cut surface. doi:10.4021/jcs54w

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)0.001
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 score0.388
Threshold uncertainty score0.351

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.093
GPT teacher head0.339
Teacher spread0.246 · 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

Citations0
Published2012
Admission routes1
Has abstractyes

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