The Approach to Diagnosis and Treatment of Chronic Constipation: Suggestions for a General Practitioner
Bibliographic record
Abstract
Chronic constipation is a frequent complaint. Symptoms of obstructive defecation (straining, hard and lumpy stools, or incomplete evacuation) are more frequent and bothersome than the frequency of bowel movements. Patient assessment is clinically based on the presence or absence of red flags. Commonly used therapies (eg, bulk-forming agents, stool softeners and stimulant laxatives) have only been evaluated in small studies of short duration. Polyethylene glycol was shown to be effective and safe in several rigorous trials with durations of more than one year. New drugs (prucalopride, lubiprostone and linaclotide) were shown to be effective and safe in well-designed and rigorous studies. Trials conducted in primary care patients are lacking for all therapies. Biofeedback and behavioural therapies are effective, but should be reserved for selected patients after proper diagnostic evaluation. A practical management algorithm is proposed using a multistep approach favouring early introduction of combined therapies and long-term step-down strategy to the lowest satisfactory regimen.
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 | 0.007 | 0.012 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.003 | 0.008 |
| Open science | 0.005 | 0.004 |
| Research integrity | 0.019 | 0.021 |
| Insufficient payload (model declined to judge) | 0.013 | 0.008 |
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".