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Record W3158850682 · doi:10.1136/bcr-2021-242609

Massive traumatic abdominal wall hernia with significant tissue loss: challenges in management

2021· article· en· W3158850682 on OpenAlexaff
Graham Skelhorne‐Gross, Jordan Nantais, Noah Ditkofsky, David Gómez

Bibliographic record

VenueBMJ Case Reports · 2021
Typearticle
Languageen
FieldMedicine
TopicHernia repair and management
Canadian institutionsUniversity of ManitobaUniversity of Toronto
Fundersnot available
KeywordsMedicineAbdominal wallSurgeryEvisceration (ophthalmology)HerniaAbdominal wall defectAbdomenConcomitant

Abstract

fetched live from OpenAlex

A 41-year-old woman presented to our trauma centre following a high-speed motor vehicle collision with a seatbelt pattern of injury resulting in extensive rupture of her abdominal wall musculature and associated hollow viscus injuries. The abdominal wall had vertical separation between transected rectus, bilateral transverse abdominis and oblique muscles allowing evisceration of small and large bowel into the flanks without skin rupture. Intraoperatively, extensive liquefaction and tissue loss of the abdominal wall was found with significant retraction of the remaining musculature. Initial operative management focused on repair of concomitant intra-abdominal injuries with definitive repair performed in delayed, preplanned stages including bridging with absorbable mesh and placement of an overlying split-thickness skin graft. The patient was discharged from hospital and underwent extensive rehabilitation. One year later, the abdominal wall was definitively repaired with components separation and biological mesh underlay. This stepwise repair process provided her with a robust and enduring abdominal wall reconstruction.

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: Case report · Consensus signal: Case report
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.077
Threshold uncertainty score0.739

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.043
GPT teacher head0.314
Teacher spread0.271 · 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 designCase report
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

Citations1
Published2021
Admission routes1
Has abstractyes

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