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Record W4294024963 · doi:10.1503/cjs.008521

Technical considerations in the management of penetrating cardiac injury

2022· review· en· W4294024963 on OpenAlexaffvenue
Chad G. Ball, Alex Lee, Matthew Kaminsky, S. Morad Hameed

Bibliographic record

VenueCanadian Journal of Surgery · 2022
Typereview
Languageen
FieldMedicine
TopicTrauma Management and Diagnosis
Canadian institutionsUniversity of CalgaryUniversity of British Columbia
Fundersnot available
KeywordsMedicineThoracotomyDamage controlMedian sternotomyIntensive care medicineSurgery

Abstract

fetched live from OpenAlex

Penetrating cardiac injuries require rapid diagnosis, efficient exposure and nuanced technical approaches, within a framework of highly coordinated and integrated multidisciplinary care. Acute care surgeons, with both strategic and technical expertise, are ideally positioned to address the potentially devastating consequences of these injuries. The aim of this narrative review is to offer a technical approach to the rapid evaluation, exposure, operative repair and postoperative care of penetrating cardiac injuries. A comprehensive review of the cardiac trauma literature, dating back to 1970, has provided a detailed toolbox of approaches to subxiphoid pericardial windows, resuscitative thoracotomy, median sternotomy, pericardiotomy, aortic clamping, cardiac hemorrhage control, cardiac repair, coronary artery injuries, pericardial closure, drain placement, chest wall closures, damage control thoracic procedures and immediate postoperative cardiac care, all based on fundamental physiological principles and anatomical considerations.

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)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.005
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.002
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.001

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 head0.163
GPT teacher head0.344
Teacher spread0.181 · 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 designNot applicable
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

Citations21
Published2022
Admission routes2
Has abstractyes

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