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Record W2171160708 · doi:10.4021/gr238e

Does Timing of Colon Procedures Affect Outcomes in D-IBS Trials?

2010· article· en· W2171160708 on OpenAlexvenueno aff
Jianmin Wang

Bibliographic record

VenueGastroenterology Research · 2010
Typearticle
Languageen
FieldMedicine
TopicGastrointestinal motility and disorders
Canadian institutionsnot available
FundersRTI International
KeywordsMedicineAffect (linguistics)Internal medicineGastroenterology

Abstract

fetched live from OpenAlex

BACKGROUND: Sigmoidoscopy/colonoscopy is usually performed prior to enrollment into clinical trials of irritable bowel syndrome (IBS). Two main reasons are to rule out alternative diagnoses and to ensure that colitis is not present. However, the possible impact of a recent versus remote colon procedure on symptoms in IBS trials has not been evaluated. The aim of this study was to evaluate the effect of timing of colon procedures on symptoms in IBS trials. METHODS: Post hoc analyses were conducted using placebo patients with diarrhea-predominant IBS in a phase 2 trial. Pain, frequency, consistency, and urgency were analyzed using repeated measures models during the first 7 days of treatment and over the entire 12-week treatment period. RESULTS: Fifty-two placebo patients were grouped by whether they had a colon exam performed between screening and randomization (Group 1) or had a normal colon procedure during the 3 years prior to screening for this trial (Group 2). Average screening symptom scores were comparable between the two groups. Evaluation of various symptoms showed that there were no consistent significant differences between the two groups in pain, frequency, consistency, or urgency. CONCLUSIONS: After the required 3-day post-procedure recovery period, there was no evidence that colonoscopy timing affected subsequent IBS 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 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)0.145
metaresearch head score (Gemma)0.252
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.145
Threshold uncertainty score0.767

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.1450.252
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0040.006
Bibliometrics0.0010.002
Science and technology studies0.0010.002
Scholarly communication0.0020.003
Open science0.0010.001
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.104
GPT teacher head0.441
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 source (direct Gemma or distilled Codex), 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

Citations0
Published2010
Admission routes1
Has abstractyes

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