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Record W2114813557 · doi:10.1186/1710-1492-7-10

Nutritional management of Eosinophilic Gastroenteropathies: Case series from the community

2011· article· en· W2114813557 on OpenAlexafffundvenue
Alfred Basilious, Joel Liem

Bibliographic record

VenueAllergy Asthma and Clinical Immunology · 2011
Typearticle
Languageen
FieldMedicine
TopicEosinophilic Esophagitis
Canadian institutionsWestern UniversityUniversity of WindsorOttawa Allergy Research Corporation
FundersUniversity of Windsor
KeywordsEosinophilic esophagitisElemental dietEosinophilicMedicinePalatabilityEosinophilGastroenterologyElimination dietColitisEosinophiliaDietary managementInternal medicineDermatologyAllergyFood allergyIntensive care medicineImmunologyPathologyAsthmaDiseaseParenteral nutrition

Abstract

fetched live from OpenAlex

Eosinophilic gastroenteropathies, such as eosinophilic esophagitis and eosinophilic colitis, have classically been treated with swallowed inhaled corticosteroids or oral corticosteroids. More recent studies have found elimination and elemental diets to be effective treatment alternatives to steroids. In this case series we describe the treatment of three children using nutritional management in a community setting. Elimination diets and elemental diets based on patch testing and skin prick tests reduced the eosinophil counts to normal levels in all three children. Food items which tested positive were then reintroduced while symptoms and eosinophil counts were monitored. Nutritional management of eosinophilic esophagitis and eosinophilic colitis was found to be effective in reducing symptoms. However, obstacles facing patients who choose this type of therapy include limitations due to the cost of repeated endoscopies, palatability of elimination/elemental diets and the availability of subspecialists trained in management (e.g. Allergy, Gastroenterology, and Pathology). It may be a worthwhile endeavour to overcome these obstacles as nutritional management minimizes the potential long-term effects of chronic steroid therapy.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.325
Threshold uncertainty score0.518

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.050
GPT teacher head0.299
Teacher spread0.249 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations17
Published2011
Admission routes3
Has abstractyes

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