Knowledge and practices of primary care physicians or general practitioners treating post-infectious Irritable Bowel Syndrome
Bibliographic record
Abstract
BACKGROUND: Post-infectious Irritable Bowel Syndrome (PI-IBS) is a functional bowel disorder which has significant impacts to a patient's quality of life. No IBS-specific biomarker or treatment regimen for PI-IBS currently exists, therefore understanding practice patterns and variance is of interest. METHODS: This online survey of primary care physicians and general practitioners in the USA aimed to understand the knowledge and treatment of PI-IBS within the physician's current practice. Summary statistics are provided with a commentary on implications for practices and treatment of PI-IBS. RESULTS: Most physician survey respondents (n = 50) were aware of PI-IBS, but less than half discussed this condition as a possible outcome in their patients with a recent gastrointestinal infection. Most physicians indicated that they would treat the patients themselves with a focus on managing IBS through different treatment modalities based on severity. Treatment for PI-IBS followed IBS recommendations, but most physicians also prescribed a probiotic for therapy. Physicians estimated that 4 out of 10 patients who develop PI-IBS will have life-long symptoms and described significant impacts to their patient's quality of life. Additionally, physicians estimated a significant financial burden for PI-IBS patients, ranging from $100-1000 (USD) over the course of their illness. Most physicians agreed that they would use a risk score to predict the probability of their patients developing PI-IBS, if available. CONCLUSIONS: While this survey is limited due to sample size, physician knowledge and treatment of PI-IBS was consistent across respondents. Overall, the physicians identified significant impacts to patient's quality of life due to PI-IBS.
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 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".