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Record W2466554778 · doi:10.14740/jmc.v7i7.2543

Spontaneous Rupture of a Deep Femoral Pseudoaneurysm Mimicking Lymphedema After Radical Hysterectomy in a Woman Who Was Receiving Warfarin

2016· article· en· W2466554778 on OpenAlexvenueno aff
Shun‐ichi Ikeda, Tomoko Manabe, Shunsuke Sugawara, Miyuki Sone, Mitsuya Ishikawa, Tomoyasu Kato

Bibliographic record

VenueJournal of Medical Cases · 2016
Typearticle
Languageen
FieldMedicine
TopicVascular Procedures and Complications
Canadian institutionsnot available
Fundersnot available
KeywordsMedicinePseudoaneurysmThighDeep veinSurgeryRadiologyPulmonary embolismWarfarinDissection (medical)Femoral arteryThrombosisFemoral veinHysterectomyFemurHematomaAneurysm

Abstract

fetched live from OpenAlex

Pseudoaneurysms of the deep femoral artery have been reported after external injury to the thigh and orthopedic surgery of the femur. We describe our experience with a case of spontaneous rupture of a deep femoral pseudoaneurysm in a woman who was receiving warfarin within the therapeutic range. She received a choledocholithotomy after a radical hysterectomy for uterine cervical cancer (stage IB1). Pulmonary embolism and deep-vein thrombosis developed after choledocholithotomy, and an inferior vena cava filter was left in place permanently. She was receiving warfarin since then. This time, the patient presented with a pseudoaneurysm of the deep femoral artery and a large hematoma in the adductor muscle of the thigh. Swelling of the thigh in this condition resembled the lower-extremity edema that occurs after pelvic lymph-node dissection. Contrast-enhanced computed tomography (CT) was useful for diagnosis of the pseudoaneurysm and evaluation of the extent of muscle damage. J Med Cases. 2016;7(7):299-302 doi: http://dx.doi.org/10.14740/jmc2543w

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)0.006
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: Case report
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.006
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.018
GPT teacher head0.284
Teacher spread0.266 · 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

Citations2
Published2016
Admission routes1
Has abstractyes

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