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Record W2039648472 · doi:10.1155/2011/624060

The Use of Bovine Pericardial Buttress on Linear Stapler Fails to Reduce Pancreatic Fistula Incidence in a Porcine Pancreatic Transection Model

2011· article· en· W2039648472 on OpenAlexafffund
Allison H. Maciver, Michael McCall, D. Mihalicz, David Al‐Adra, Rena Pawlick, A. M. James Shapiro

Bibliographic record

VenueHPB Surgery · 2011
Typearticle
Languageen
FieldMedicine
TopicPancreatic and Hepatic Oncology Research
Canadian institutionsUniversity of Alberta Hospital
FundersNational Institutes of HealthUniversity of AlbertaAlberta InnovatesDiabetes Research Institute Foundation
KeywordsMedicinePancreatic fistulaPancreatic ductDistal pancreatectomySurgeryFistulaPancreasPancreatitisResectionInternal medicine

Abstract

fetched live from OpenAlex

We investigate the effectiveness of buttressing the surgical stapler to reduce postoperative pancreatic fistulae in a porcine model. As a pilot study, pigs (n = 6) underwent laparoscopic distal pancreatectomy using a standard stapler. Daily drain output and lipase were measured postoperative day 5 and 14. In a second study, pancreatic transection was performed to occlude the proximal and distal duct at the pancreatic neck using a standard stapler (n = 6), or stapler with bovine pericardial strip buttress (n = 6). Results. In pilot study, 3/6 animals had drain lipase greater than 3x serum on day 14. In the second series, drain volumes were not significantly different between buttressed and control groups on day 5 (55.3 ± 31.6 and 29.3 ± 14.2 cc, resp.), nor on day 14 (9.5 ± 4.2 cc and 2.5 ± 0.8 cc, resp., P = 0.13). Drain lipase was not statistically significant on day 5 (3,166 ± 1,433 and 6,063 ± 1,872 U/L, resp., P = 0.25) or day 14 (924 ± 541 and 360 ± 250 U/L). By definition, 3/6 developed pancreatic fistula; only one (control) demonstrating a contained collection arising from the staple line. Conclusion. Buttressed stapler failed to protect against pancreatic fistula in this rigorous surgical model.

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)0.002
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 score0.045
Threshold uncertainty score0.647

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
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 head0.167
GPT teacher head0.343
Teacher spread0.176 · 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
Published2011
Admission routes2
Has abstractyes

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