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Record W2575409350 · doi:10.1186/s13017-017-0117-6

Pelvic trauma: WSES classification and guidelines

2017· review· en· W2575409350 on OpenAlexaff
Federico Coccolini, Philip F. Stahel, Giulia Montori, Walter Biffl, Tal M. Hörer, Fausto Catena, Yoram Kluger, Ernest E. Moore, Andrew B. Peitzman, Rao R. Ivatury, Raúl Coimbra, Gustavo Pereira Fraga, Bruno M. Pereira, Sandro Rizoli, Andrew W. Kirkpatrick, Ari Leppäniemi, Roberto Manfredi, Stefano Magnone, Osvaldo Chiara, Leonardo Solaini, Marco Ceresoli, Niccolò Allievi, C. Arvieux, George Velmahos, Zsolt J. Balogh, Noel Naidoo, Dieter Weber, Fikri M. Abu‐Zidan, Massimo Sartelli, Luca Ansaloni

Bibliographic record

VenueWorld Journal of Emergency Surgery · 2017
Typereview
Languageen
FieldMedicine
TopicPelvic and Acetabular Injuries
Canadian institutionsFoothills Medical CentreSt. Michael's Hospital
Fundersnot available
KeywordsMedicineMajor traumaPenetrating traumaIntensive care medicineSurgeryBlunt

Abstract

fetched live from OpenAlex

Complex pelvic injuries are among the most dangerous and deadly trauma related lesions. Different classification systems exist, some are based on the mechanism of injury, some on anatomic patterns and some are focusing on the resulting instability requiring operative fixation. The optimal treatment strategy, however, should keep into consideration the hemodynamic status, the anatomic impairment of pelvic ring function and the associated injuries. The management of pelvic trauma patients aims definitively to restore the homeostasis and the normal physiopathology associated to the mechanical stability of the pelvic ring. Thus the management of pelvic trauma must be multidisciplinary and should be ultimately based on the physiology of the patient and the anatomy of the injury. This paper presents the World Society of Emergency Surgery (WSES) classification of pelvic trauma and the management Guidelines.

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)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.008
Threshold uncertainty score0.020

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0080.005
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.002

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 head0.398
GPT teacher head0.473
Teacher spread0.075 · 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 designSystematic review
Domainnot available
GenreReview

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

Citations474
Published2017
Admission routes1
Has abstractyes

Explore more

Same venueWorld Journal of Emergency SurgerySame topicPelvic and Acetabular InjuriesFrench-language works237,207