Novel Irritable Bowel Syndrome Subgroups Are Reproducible in the Global Adult Population
Bibliographic record
Abstract
BACKGROUND & AIMS: Current classification systems for irritable bowel syndrome (IBS) based on bowel habit do not consider psychological impact. We validated a classification model in a UK population with confirmed IBS, using latent class analysis, incorporating psychological factors. We applied this model in the Rome Foundation Global Epidemiological Survey (RFGES), assessing impact of IBS on the individual and the health care system, and examining reproducibility. METHODS: We applied our model to 2195 individuals in the RFGES with Rome IV-defined IBS. As described previously, we identified 7 clusters, based on gastrointestinal symptom severity and psychological burden. We assessed demographics, health care-seeking, symptom severity, and quality of life in each. We also used the RFGES to derive a new model, examining whether the broader concepts of our original model were replicated, in terms of breakdown and characteristics of identified clusters. RESULTS: All 7 clusters were identified. Those in clusters with highest psychological burden, and particularly cluster 6 with high overall gastrointestinal symptom severity, were more often female, exhibited higher levels of health care-seeking, were more likely to have undergone previous abdominal surgeries, and had higher symptom severity and lower quality of life (P < .001 for trend for all). When deriving a new model, the best solution consisted of 10 clusters, although at least 2 seemed to be duplicates, and almost all mapped on to the previous clusters. CONCLUSIONS: Even in the community, our original clusters derived from patients with physician-confirmed IBS identified groups of individuals with significantly higher rates of health care-seeking and abdominal surgery, more severe symptoms, and impairments in quality of life.
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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 | 0.011 | 0.032 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 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".