Use of Serotonergic Drugs in Canada for Gastrointestinal Motility Disorders: Results of a Retrospective Cohort Study
Bibliographic record
Abstract
Background. Surgery for GI dysmotility is limited to those with severe refractory disease. Though effective, use of serotonergic promotility drugs has been restricted in Canada due to adverse events. We aimed to investigate utilization of promotility serotonergic drugs in patients under consideration for surgical management. Methods. A retrospective cohort study was conducted using prospectively collected data. The study population included consecutive patients referred to a motility clinic for consideration of bowel resection at a Canadian tertiary hospital (1996-2011). Univariable tests and multivariable logistic regression analyses were used to assess predictors of serotonergic drug use. Results. Of 128 patients, the majority (n = 98, 76.6%) had constipation-dominant symptoms. Only 25% (n = 32) had tried serotonergic promotility drugs. There was no association between use of these drugs and severity of constipation nor was there an association between serotonergic drug use and presence of diffuse dysmotility (all p > 0.05). The majority of patients (n = 97, 75.8%) underwent some type of surgical resection, which was associated with considerable morbidity (n = 13, 13.4%). Conclusions. Surgical management of GI dysmotility results in serious morbidity. Serotonergic promotility drugs may allow patients to avoid surgery but disease severity does not predict use of these drugs.
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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) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".