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Record W2166714179 · doi:10.4021//jmc.v2i4.249

Report of a Case: Pseudoaneurysm of the Cystic Artery With Hemobilia Treated by Arterial Embolization

2011· article· en· W2166714179 on OpenAlexvenueno aff
Yoshihiro Komatsu, Hajime Orita, Mutsumi Sakurada, Hiroshi Maekawa, Toshitaka Hoppo, Koichi Sato

Bibliographic record

VenueJournal of Medical Cases · 2011
Typearticle
Languageen
FieldMedicine
TopicAbdominal vascular conditions and treatments
Canadian institutionsnot available
Fundersnot available
KeywordsMedicinePseudoaneurysmCystic arteryEmbolizationMelenaRadiologyArterial EmbolizationAngiographySurgeryCholecystectomyUpper gastrointestinal bleedingAneurysmEndoscopyCystic duct

Abstract

fetched live from OpenAlex

We report a case of hemobilia caused by pseudoaneurysm of the cystic artery in a 71-year-old woman who presented with fever and epigastric colicky pain with jaundice. Liver function tests showed signs of obstructive jaundice. On the second day, patient had a massive hematemesis and melena with hypovolemic shock. Hemobilia was diagnosed by endoscopically visualizing bleeding from the papilla of Vater. An emergent angiography demonstrated the presence of a pseudoaneurysm in the cystic artery. Selective embolization of the cystic artery was then performed to interrupt the blood flow into the pseudoaneurysm. Immediately after embolization, patient was hemodynamically stabilized. Although the patient did not undergo cholecystectomy after embolization due to severe co-morbidities, no signs of ischemic gallbladder have been observed. Hemobilia should be included in the differential diagnosis of upper gastrointestinal bleeding with unknown etiology. Embolization could be an option for pseudoaneurysms of the cystic artery especially in high-risk patients. doi:10.4021/jmc249w

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)0.004
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 score0.010
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0030.002
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0030.002
Science and technology studies0.0050.002
Scholarly communication0.0030.004
Open science0.0020.003
Research integrity0.0100.005
Insufficient payload (model declined to judge)0.0030.002

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 head0.021
GPT teacher head0.266
Teacher spread0.246 · 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

Citations5
Published2011
Admission routes1
Has abstractyes

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