Recommendations on Chronic Constipation (including Constipation Associated with Irritable Bowel Syndrome) Treatment
Bibliographic record
Abstract
While chronic constipation (CC) has a high prevalence in primary care, there are no existing treatment recommendations to guide health care professionals. To address this, a consensus group of 10 gastroenterologists was formed to develop treatment recommendations. Although constipation may occur as a result of organic disease, the present paper addresses only the management of primary CC or constipation associated with irritable bowel syndrome. The final consensus group was assembled and the recommendations were created following the exact process outlined by the Canadian Association of Gastroenterology for the following areas: epidemiology, quality of life and threshold for treatment; definitions and diagnostic criteria; lifestyle changes; bulking agents and stool softeners; osmotic agents; prokinetics; stimulant laxatives; suppositories; enemas; other drugs; biofeedback and behavioural approaches; surgery; and probiotics. A treatment algorithm was developed by the group for CC and constipation associated with irritable bowel syndrome. Where possible, an evidence-based approach and expert opinions were used to develop the statements in areas with insufficient evidence. The nature of the underlying pathophysiology for constipation is often unclear, and it can be tricky for physicians to decide on an appropriate treatment strategy for the individual patient. The myriad of treatment options available to Canadian physicians can be confusing; thus, the main aim of the recommendations and treatment algorithm is to optimize the approach in clinical care based on available evidence.
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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 | 0.006 | 0.024 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.004 | 0.001 |
| Research integrity | 0.006 | 0.007 |
| Insufficient payload (model declined to judge) | 0.008 | 0.003 |
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".