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Record W2991604854 · doi:10.14740/gr1208

Clinical Presentation, Diagnosis, and Management of Air Embolism During Endoscopic Retrograde Cholangiopancreatography

2019· review· en· W2991604854 on OpenAlexvenueno aff
Muhammad Haisum Maqsood, Nayab Mirza, Muhammad Hanif, Hira Hanif, Maleeha Saleem, Muhammad Arqam Maqsood, Ilsa Fatima, MUHAMMAD MOIZ TAHIR

Bibliographic record

VenueGastroenterology Research · 2019
Typereview
Languageen
FieldMedicine
TopicGallbladder and Bile Duct Disorders
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineEndoscopic retrograde cholangiopancreatographyAir embolismComplicationMedical diagnosisDifferential diagnosisEndoscopyRadiologySurgeryPancreatitisPathology

Abstract

fetched live from OpenAlex

Endoscopic retrograde cholangiopancreatography (ERCP) is a minimally invasive procedure that is widely used by endoscopists and has a robust therapeutic profile. It uses endoscopy and imaging for a variety of diagnostic as well as therapeutic purposes. It is used for the management of a lot of pancreaticobiliary diseases such as obstructive jaundice, obstruction related to bile ducts, pancreatic biliary tumors, and traumatic or iatrogenic damage to the bile ducts. Other therapeutic interventions that can be done via ERCP include sphincterotomy, dilation of strictures, removal of biliary stones and placement of stents. Air embolism presents with cardiovascular, pulmonary, and neurologic signs and symptoms. Treatment of air embolism should be started early in suspected cases, and it should be in the differential diagnoses of various complications secondary to high risk of ERCP, especially if a cardiopulmonary compromise is present. Air embolism is rare but a serious complication associated with ERCP. The physicians must keep this in mind while performing ERCP in patients with predisposing risk factors. This review highlights the mechanism, causes, risk factors, pathophysiology, clinical signs, diagnostic modalities, treatment, and preventive measures to deal with this catastrophic complication.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.192
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.119
GPT teacher head0.456
Teacher spread0.337 · 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.

Study designObservational
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

Citations10
Published2019
Admission routes1
Has abstractyes

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