The microbiota in patients with interstitial cystitis/bladder pain syndrome: a systematic review
Bibliographic record
Abstract
OBJECTIVE: To comprehensively review and critically assess the literature on microbiota differences between patients with interstitial cystitis (IC)/bladder pain syndrome (BPS) and normal controls and to provide clinical practice guidelines. MATERIALS AND METHODS: In this systematic review, we evaluated previous research on microbiota disparities between IC/BPS and normal controls, as well as distinctions among IC/BPS subgroups. A comprehensive literature search was conducted across PubMed/MEDLINE, EMBASE, Web of Science, and the Cochrane Central Register of Controlled Trials. Relevant studies were shortlisted based on predetermined inclusion and exclusion criteria, followed by quality assessment. The primary focus was identifying specific taxonomic variations among these cohorts. RESULTS: A total of 12 studies met the selection criteria. Discrepancies were adjudicated by a third reviewer. The Newcastle-Ottawa Scale was used to assess study quality. Predominantly, the studies focused on disparities in urine microbiota between IC/BPS patients and normal controls, with one study examining gut microbiota differences between the groups, and two studies exploring vaginal microbiota distinctions. Unfortunately, analyses of discrepancies in other microbiota were limited. Our findings revealed evidence of distinct bacterial abundance variations, particularly involving Lactobacillus, alongside variations in specific metabolites among IC/BPS patients compared to controls. CONCLUSIONS: Currently, there is evidence suggesting significant variations in the diversity and species composition of the urinary microbiota between individuals diagnosed with IC/BPS and control groups. In the foreseeable future, urologists should consider urine microbiota dysbiosis as a potential aetiology for IC, with potential clinical implications for diagnosis and treatment.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".