Diarrhea-Predominant Irritable Bowel Syndrome: Medical Management Update
Bibliographic record
Abstract
Irritable bowel syndrome (IBS) is a prevalent gastrointestinal disorder, which impacts the quality of life, work productivity and social activities of patients. Diarrhea-predominant IBS (IBS-D) is one of several subtypes, and accounts for approximately one third of all cases. Currently available treatments are typically unable to alleviate the cardinal symptoms of IBS-D, including abdominal pain and diarrhea, and a clinical unmet need remains for an effective treatment which simultaneously relieves multiple symptoms. Patients may benefit from a multipronged, individualized approach, including dietary modifications, and psychological and pharmacological therapies. The aim of this review is to provide an update on the available and upcoming treatment options for IBS-D in Canada, with reference to the recently updated Canadian IBS consensus guidelines. Initial treatment approaches include lifestyle modifications, dietary modifications, and non-prescription therapies such as peppermint oil. While some medications such as tricyclic antidepressants are also used to treat IBS-D symptoms, eluxadoline and rifaximin are the only two pharmacological therapies approved for the treatment of IBS-D in Canada. Key clinical trial data for the currently available pharmacological options are presented to provide an overview of the efficacy and safety of these agents.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 0.002 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".