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Intolerance to visceral distension in functional dyspepsia or irritable bowel syndrome: an organ specific defect or a pan intestinal dysregulation?

2004· article· en· W1979377324 on OpenAlexaff
Mickaël Bouin, France Lupien, Monique Riberdy, Michel Boivin, Victor Plourde, P. Poitras

Bibliographic record

VenueNeurogastroenterology & Motility · 2004
Typearticle
Languageen
FieldMedicine
TopicGastrointestinal motility and disorders
Canadian institutionsUniversité de MontréalHôpital Saint-Luc
Fundersnot available
KeywordsIrritable bowel syndromeDistensionMedicineGastroenterologyInternal medicineConcomitantRectumStomachGastric distensionAbdominal distensionVisceral painBarostatNociception

Abstract

fetched live from OpenAlex

Functional gastrointestinal disorders (FGID) are characterized by visceral hypersensitivity that could be specific to a region of the gut or reflect a diffuse pan-intestinal disorder. Sensory thresholds to distension at two visceral sites in patients with different FGIDs were determined. According to Rome II criteria, 30 patients from three groups were studied: patients with (i) functional dyspepsia (FD) or (ii) irritable bowel syndrome (IBS), and (iii) patients with concomitant symptoms of FD and IBS. Pain thresholds to balloon distension were determined in stomach and rectum. In FD patients, gastric intolerance to balloon distension was found in 91% patients; rectal hypersensitivity was documented in 18% patients. In IBS patients, rectal hypersensitivity was seen in 75% patients; while gastric hypersensitivity was never found. In patients with concomitant symptoms of FD + IBS, gastric and rectal intolerance to distension were present respectively in 82 and 91% patients. In the whole group, visceral intolerance to distension was documented at one site in 90% patients and at both sites, i.e. stomach and rectum, in 33% patients. Visceral intolerance to distension can be pan-intestinal in patients with multiple sites of symptoms, but appears organ-specific in patients exhibiting a specific site of symptoms.

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)0.001
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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.032
GPT teacher head0.278
Teacher spread0.245 · 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
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

Citations81
Published2004
Admission routes1
Has abstractyes

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