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The Feasibility of Adopting Laparoscopic Incisional Hernia Repair in General Surgery Practice: Early Outcomes in an Unselected Series of Patients

2004· article· en· W2072202934 on OpenAlexaff
Fahad Bamehriz, Daniel W. Birch

Bibliographic record

VenueSurgical Laparoscopy Endoscopy & Percutaneous Techniques · 2004
Typearticle
Languageen
FieldMedicine
TopicHernia repair and management
Canadian institutionsSt. Joseph’s Healthcare HamiltonMcMaster UniversityRoyal Alexandra Hospital
Fundersnot available
KeywordsMedicineIncisional herniaSurgeryHerniaLaparoscopic surgerySurgical meshAbdominal surgeryLaparoscopyGeneral surgeryAbdominal wallBody mass indexInternal medicine

Abstract

fetched live from OpenAlex

A laparoscopic approach to incisional hernia repair has been shown to be safe and effective in selected patients. We report our early outcomes following laparoscopic ventral/incisional hernia repair (LVHR) in an unselected series of patients encountered in general surgery practice. All patients referred with incisional hernia were offered a laparoscopic repair using prosthetic mesh. Patients were not excluded from laparoscopic approach on the basis of age, previous surgery, defect size, intraperitoneal mesh, body mass index (BMI), comorbidities, or abdominal wall stomas. We followed 28 consecutive patients who underwent LVHR (17 primary, 11 recurrent hernias). Laparoscopic repair was completed in 27 patients with a mean operative time of 141.6 +/- 11.9 minutes. There were no intraoperative complications. The mean size of the abdominal wall defects was 153.4 +/- 27.5 cm and the mean mesh size was 349.2 +/- 59.1 cm. The mean hospital stay was 3.7 +/- 0.3 days. Nine patients developed large wound seromas; all spontaneously resolved. Our experience suggests that LVHR is feasible as a primary approach to most incisional hernias encountered in general surgery practice.

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)0.004
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.020
GPT teacher head0.328
Teacher spread0.308 · 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 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

Citations11
Published2004
Admission routes1
Has abstractyes

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