Systematic review and meta‐analysis: the incidence and prognosis of post‐infectious irritable bowel syndrome
Bibliographic record
Abstract
BACKGROUND: Individual studies suggest that post-infectious irritable bowel syndrome is common, but symptoms gradually improve. AIM: To review evidence for an association between intestinal infection and development of irritable bowel syndrome, assess the prognosis of post-infectious irritable bowel syndrome and explore factors that increase the risk. METHODS: MEDLINE (1966-2007) and EMBASE (1980-2007) databases were searched to identify the studies of post-infectious irritable bowel syndrome epidemiology. Data were extracted by two independent reviewers. Pooled odds ratios (POR) and corresponding 95% CI for incidence of irritable bowel syndrome were estimated among the exposed and unexposed groups. RESULTS: Eighteen of 26 studies identified were eligible for inclusion. Intestinal infection was associated with increased odds of developing irritable bowel syndrome at study end (POR = 5.86; 95% CI: 3.60-9.54). In subgroup analysis, the odds of developing irritable bowel syndrome was increased at 3 months (POR = 7.58; 95% CI: 4.27-13.45), 6 months (POR = 5.18; 95% CI: 3.24-8.26), 12 months (POR = 6.37; 95% CI: 2.63-15.40) and 24-36 months (POR = 3.85; 95% CI: 2.95-5.02). Among all studies (controlled and uncontrolled), the pooled incidence of irritable bowel syndrome at study conclusion was 10% (95% CI: 9.4-85.6). Subjects with post-infectious irritable bowel syndrome were younger and more anxious and depressed than those without post-infectious irritable bowel syndrome. CONCLUSION: The odds of developing irritable bowel syndrome are increased sixfold after acute gastrointestinal infection. Young age, prolonged fever, anxiety and depression are risk factors for post-infectious irritable bowel syndrome.
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 | 0.018 | 0.056 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.020 | 0.034 |
| Bibliometrics | 0.006 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".