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Record W2129059301 · doi:10.1155/2008/603105

Esophageal Leiomyomatosis – An Unusual Cause of Pseudoachalasia

2008· article· en· W2129059301 on OpenAlexvenueno aff
Sukanta Ray, Sundeep Singh Saluja, Ruchika Gupta, Tushar Kanti Chattopadhyay

Bibliographic record

VenueCanadian Journal of Gastroenterology · 2008
Typearticle
Languageen
FieldMedicine
TopicGastrointestinal Tumor Research and Treatment
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineAchalasiaEsophagusLeiomyomatosisDysphagiaRadiologyLeiomyomaSurgery

Abstract

fetched live from OpenAlex

Esophageal leiomyomatosis is a rare hamartomatous disorder with varied presentation. In the literature, it is described mostly in children, and is associated with Alport's syndrome. A case of leiomyomatosis that presented as achalasia not associated with Alport's syndrome is described in a 35-year-old woman with a 16-year history of dysphagia. Barium swallow showed a smooth narrowing at the lower end of the esophagus with a longer than usual stricture length. Endoscopy showed a dilated esophagus with a submucosal nodule in the region of the cardia. A computed tomography scan revealed circumferential thickening of the esophagus involving the gastroesophageal junction, with fat planes maintained with the adjacent structure. Endoscopic ultrasound demonstrated a lesion arising from the muscularis propria. The manometry findings were suggestive of achalasia. She underwent transhiatal esophagectomy with gastric pull-up. Leiomyomatosis should be considered as a cause of psuedoachalasia in patients with symptoms suggestive of achalasia and atypical barium findings. Attempts should be made to confirm the diagnosis preoperatively using computed tomography and/or endoscopic ultrasound. Esophagectomy is the treatment of choice.

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)0.003
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 score0.003
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0030.001
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 head0.037
GPT teacher head0.283
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

Citations29
Published2008
Admission routes1
Has abstractyes

Explore more

Same venueCanadian Journal of GastroenterologySame topicGastrointestinal Tumor Research and TreatmentFrench-language works237,207