The impact of opioid-induced constipation among chronic pain patients with sufficient laxative use
Bibliographic record
Abstract
BACKGROUND: The impact of sufficient laxative use on opioid-induced constipation (OIC) is not known. AIM: To understand the experience and symptom burden over time among chronic non-cancer pain patients with OIC who are sufficient laxative users. METHODS: A prospective longitudinal study was conducted in United States, Canada, Germany and UK which included medical record abstraction, patient surveys and physician surveys. Patients on daily opioid therapy for ≥ 4 weeks for chronic non-cancer pain with OIC were recruited from physician offices and completed the survey at Baseline and Weeks 2, 4, 6, 8, 12, 16, 20 and 24. Sufficient laxative use was defined as at least one laxative remedy 4 or more times in the prior 2 weeks. RESULTS: Of the 489 patients who completed the Baseline survey and met OIC criteria, 234 (48%) were categorised as sufficient laxative users; 65% were female; 90% were white and 75 (32%) maintained sufficient laxative use for > 7 of the 8 follow-up periods. Patient Assessment of Constipation-Symptom (PAC-SYM) and Patient Assessment of Constipation-Quality of Life (PAC-QOL) scores indicated moderate symptom severity and impact. PAC-SYM and PAC-QOL scores remained relatively unchanged over time with a maximum score change of 0.5 points. Work productivity and activity impairment remained relatively constant. Mean per cent activity impairment because of constipation was 37% at Baseline and 34% at Week 24. CONCLUSIONS: These findings demonstrate constipation persists despite sufficient laxative use with little improvement in symptoms, HRQL or activity impairment. This ongoing burden emphasises the need to identify more efficacious constipation therapies for this chronic pain patient population.
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 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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".