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Record W3007653295 · doi:10.1093/jcag/gwz047.182

A183 UPPER GASTROINTESTINAL CAUSTIC INJURIES: A SINGLE CENTRE CASE SERIES

2020· article· en· W3007653295 on OpenAlexaffabout
Marc Monachese, Nadia Griller, Elaine Yong

Bibliographic record

VenueJournal of the Canadian Association of Gastroenterology · 2020
Typearticle
Languageen
FieldMedicine
TopicEsophageal and GI Pathology
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsMedicineEsophagogastroduodenoscopyGastric outlet obstructionCaustic (mathematics)General surgeryInternal medicineSurgeryEmergency medicineGastroenterologyEndoscopy

Abstract

fetched live from OpenAlex

Abstract Background Caustic esophageal and gastric injury is a rare, but potentially lethal event. The 2017 American Association of Poison Control reported only 193,000 cases of caustic ingestion (1). Caustic agents are acidic or alkaline. The pH of the ingested substance dictates the type of injury and the area of the gastrointestinal track most at risk. The most common culprit agents are alkaline including, for example, bleaches, drain openers and dishwashing detergents. Due to the rarity and natural history of this disease there are very few high-quality studies for clinicians to refer to when managing these patients. Aims We present three cases of caustic ingestion and provide a review of current best practice standards. Methods Between August and September 2019, three patients were admitted to Sunnybrook Health Sciences Centre at the University of Toronto for caustic injury. All three patients were referred to the gastroenterology service and underwent an esophagogastroduodenoscopy (EGD) to assess the degree of esophageal and gastric injury. Patients were followed both in hospital and in the outpatient setting for ongoing surveillance and repeated endoscopic evaluation. Patient demographics, treatment, endoscopic findings and outcomes were collected. Results Three patients intentionally ingested caustic agents, were admitted to hospital and managed by the gastroenterology service. Patients were a mix of ages, genders and ethnicities. All ingestions were strong alkali agents including sodium hydroxide and sodium hypochlorite. All patients underwent an EGD within 24 hours of presentation and caustic injury was graded using the Zargar classification (2). All patients were started on intravenous proton pump inhibitor therapy. All patients were initially made nothing per mouth and ability to resume feeds was assessed based on symptoms. Patient 1, Zargar grade 1, was able to resume oral intake within 48 hours and progressed to a regular diet without complications. Patient 2, Zargar grade 2a, required 5 days of TPN and bowel rest after which a liquid diet was initiated and advanced without complications. The third patient, had a severe injury (Zargar grade 3b), requiring a prolonged hospital stay. He was on TPN for three weeks before transitioned to tube feeds. Conclusions Caustic mucosal injuries are an infrequent, but potentially lethal event requiring urgent assessment and management by a team including gastroenterologists, thoracic and abdominal surgeons, dieticians and intensivists. High-quality evidence to guide management of caustic injuries remains limited. In our case series, there was a wide spectrum of degree of mucosal injury. All 3 patients were managed in a consistent fashion based on current recommendations. Two of three cases had a rapid recovery with the ability to resume oral intake and return home. The third patient remains in hospital, requiring a high level of supportive care. Funding Agencies None

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)0.005
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 score0.006
Threshold uncertainty score0.020

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.004
Science and technology studies0.0040.002
Scholarly communication0.0030.002
Open science0.0020.002
Research integrity0.0040.003
Insufficient payload (model declined to judge)0.0060.002

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 head0.012
GPT teacher head0.223
Teacher spread0.211 · 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".

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Citations0
Published2020
Admission routes2
Has abstractyes

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