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Record W2122226375 · doi:10.1136/gut.52.5.621

Tegaserod and IBS: a perfect match?

2003· letter· en· W2122226375 on OpenAlexaff
Wade Thompson

Bibliographic record

VenueGut · 2003
Typeletter
Languageen
FieldMedicine
TopicGastrointestinal motility and disorders
Canadian institutionsUniversity of Ottawa
FundersNational Institutes of Health
KeywordsTegaserodMedicineIrritable bowel syndromeInternal medicine

Abstract

fetched live from OpenAlex

IBS patients require diagnosis, advice, and a reassuring doctor. For constipated patients who need it, tegaserod is safe and effective. Until recently, there existed little evidence that any therapy was effective for irritable bowel syndrome (IBS). The quality of clinical trials was poor,1,2 and no systematic review3,4 can redeem faulty data.5 Mindful of this, pharmaceutical companies now employ modern clinical trial principles to test IBS drugs. The latest of these efforts is an Asia-Pacific randomised controlled trial of tegaserod by Kellow et al , described in this issue of Gut 6 [see page 671] .6 To judge how well tegaserod matches the needs of IBS patients we must examine the trial methods, results, and conclusions, and divine what is missing from the reports. The Asia-Pacific study is similar to Western IBS trials of tegaserod.7,8 These represent substantial improvements in trial methodology. The entered subjects had criteria defined IBS and most had a “non-diarrhoea” bowel habit suitable to the drug’s effects. Recruitment was sufficient to show definitive results, and subjects were double blinded and randomly allocated. A primary global outcome was selected with appropriate secondary measures, and the analysis was “intention to treat”. Primary outcome differences were consistently significant at the pre-decided end point, and over 12 weeks. Tegaserod appears safe (sine qua non for IBS), and post-marketing surveillance should detect unexpected adverse effects. The Kellow study achieved greater therapeutic gain (absolute benefit increase) than prior tegaserod studies (21% v 11.8%7 and …

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: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.050
Threshold uncertainty score0.793

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 studies0.0000.000
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 head0.016
GPT teacher head0.236
Teacher spread0.219 · 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 designNot applicable
Domainnot available
GenreCommentary

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

Citations1
Published2003
Admission routes1
Has abstractyes

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