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Record W1981487166 · doi:10.1089/lap.2010.0351

Technical Report of a Novel Surgical Technique: Laparoscopic Cyst Fenestration and Falciform Ligament Pedicle Graft for Treatment of Symptomatic Simple Hepatic Cysts

2010· article· en· W1981487166 on OpenAlexaff
Jason Faulds, Charles H. Scudamore

Bibliographic record

VenueJournal of Laparoendoscopic & Advanced Surgical Techniques · 2010
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenetic and Kidney Cyst Diseases
Canadian institutionsStornoway Diamond (Canada)
Fundersnot available
KeywordsMedicineFalciform ligamentFenestrationSurgeryCystLaparoscopy

Abstract

fetched live from OpenAlex

BACKGROUND: Simple hepatic cysts are common and infrequently develop into large symptomatic cysts that require surgical therapy. These benign cysts have been shown to be amenable to minimally invasive surgery; however, recurrences of symptoms have been reported. Our experience with over 200 simple hepatic cysts has lead to the development of a novel therapy to resolve symptoms associated with large simple hepatic cysts and reduce the rate of recurrent symptoms. METHODS: An observational study demonstrating our experience with a novel minimally invasive technique for the management of symptomatic simple hepatic cyst. RESULTS: A total of 6 cases were identified where laparoscopic mini-fenestration and placement of a falciform pedicle graft was used. There were no operative complications and 4 of 6 patients were discharged home the day of surgery. With mean follow-up of 9.6 months, there has not been any recurrence to date. One patient required an open hepatic resection for the treatment of a cystadenoma. CONCLUSION: Laparoscopic mini-fenestration and placement of a falciform ligament pedicle graft shows promising early results as a treatment for the simple hepatic cyst. Long term follow-up data is required.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.053
Threshold uncertainty score0.861

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.010
GPT teacher head0.309
Teacher spread0.299 · 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 designBench or experimental
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

Citations10
Published2010
Admission routes1
Has abstractyes

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