Systematic Review of Stimulant and Nonstimulant Laxatives for the Treatment of Functional constipation
Bibliographic record
Abstract
BACKGROUND: Constipation is an uncomfortable and common condition that affects many, irrespective of age. Since 1500 BC and before, health care practitioners have provided treatments and prevention strategies to patients for chronic constipation despite the significant variation in both medical and personal perceptions of the condition. OBJECTIVE: To review relevant research evidence from clinical studies investigating the efficacy and safety of commercially available pharmacological laxatives in Canada, with emphasis on studies adopting the Rome criteria for defining functional constipation. SEARCH METHODS: PubMed, Medline, Embase and Evidence-Based Medicine Reviews databases were searched for blinded or randomized clinical trials and meta-analyses assessing the efficacy of nonstimulant and stimulant laxatives for the treatment of functional constipation. RESULTS: A total of 19 clinical studies and four meta-analyses were retrieved and abstracted regarding study design, participants, interventions and outcomes. The majority of studies focused on polyethylene glycol compared with placebo. Both nonstimulant and stimulant laxatives provided better relief of constipation symptoms than placebo according to both objective and subjective measures. Only one study compared the efficacy of a nonstimulant versus a stimulant laxative, while only two reported changes in quality of life. All studies reported minor side effects due to laxative use, regardless of treatment duration, which ranged from one week to one year. Laxatives were well tolerated by both adults and children.
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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 | 0.003 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.005 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.000 |
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.
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".