MétaCan
Menu
Back to cohort

Management of stab wounds to the anterior abdominal wall

2014· article· en· W2023122449 on OpenAlexaff
João Rezende-Neto, Hélio Machado Vieira, Bruno de Lima Rodrigues, Sandro Rizoli, Barto Nascimento, Gustavo Pereira Fraga

Bibliographic record

VenueRevista do Colégio Brasileiro de Cirurgiões · 2014
Typearticle
Languageen
FieldMedicine
TopicAbdominal Trauma and Injuries
Canadian institutionsUniversity of TorontoSt. Michael's Hospital
Fundersnot available
KeywordsMedicineStab woundEvisceration (ophthalmology)LaparotomyPeritonitisSurgeryAbdominal wallDiagnostic peritoneal lavageAbdominal cavityTrauma centerLaparoscopyAbdominal traumaRadiologyStabPneumoperitoneumBluntRetrospective cohort study

Abstract

fetched live from OpenAlex

The meeting of the Publication "Evidence Based Telemedicine - Trauma and Emergency Surgery" (TBE-CiTE), through literature review, selected three recent articles on the treatment of victims stab wounds to the abdominal wall. The first study looked at the role of computed tomography (CT) in the treatment of patients with stab wounds to the abdominal wall. The second examined the use of laparoscopy over serial physical examinations to evaluate patients in need of laparotomy. The third did a review of surgical exploration of the abdominal wound, use of diagnostic peritoneal lavage and CT for the early identification of significant lesions and the best time for intervention. There was consensus to laparotomy in the presence of hemodynamic instability or signs of peritonitis, or evisceration. The wound should be explored under local anesthesia and if there is no injury to the aponeurosis the patient can be discharged. In the presence of penetration into the abdominal cavity, serial abdominal examinations are safe without CT. Laparoscopy is well indicated when there is doubt about any intracavitary lesion, in centers experienced in this method.

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)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.014
GPT teacher head0.290
Teacher spread0.276 · 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 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

Citations7
Published2014
Admission routes1
Has abstractyes

Explore more

Same venueRevista do Colégio Brasileiro de CirurgiõesSame topicAbdominal Trauma and InjuriesFrench-language works237,207