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Record W4404420128 · doi:10.24908/pocus.v9i2.17699

Diagnosis and Treatment of a Morel-Lavallee Lesion via Point-of-Care Ultrasound (POCUS)

2024· article· en· W4404420128 on OpenAlexvenueno aff
D. Mack, J G Miller, Frank Yuan, Edison Lee, Trent She

Bibliographic record

VenuePOCUS Journal · 2024
Typearticle
Languageen
FieldMedicine
TopicPelvic and Acetabular Injuries
Canadian institutionsnot available
Fundersnot available
KeywordsEcchymosisMedicineDeglovingPoint of care ultrasoundRadiologyLesionUltrasoundSoft tissueSurgery

Abstract

fetched live from OpenAlex

Morel-Lavallee Lesion (MLL) is a rare diagnosis of a closed internal degloving injury that can occur with high energy trauma. The pain, soft tissue swelling, and ecchymosis that patients describe mimic many other emergent diagnoses to include compartment syndrome and fractures. The following case highlights the importance of the role of Emergency Medicine physicians using point-of-care ultrasound (POCUS) to recognize and treat a potentially life-threatening injury. Our patient was initially managed with a bedside needle aspiration with drainage of 25cc of serosanguinous fluid that resulted in immediate pain relief. Patient was then admitted for further Interventional Radiology drainage of 160cc of serosanguinous fluid by Interventional Radiology.

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)0.000
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: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.699
Threshold uncertainty score0.371

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.021
GPT teacher head0.305
Teacher spread0.285 · 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 designOther design
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

Citations0
Published2024
Admission routes1
Has abstractyes

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