Stem cells and lower urinary tract dysfunction: Has its potential finally reached clinical maturity? ICI‐RS2018
Bibliographic record
Abstract
AIMS: Efforts to engineer and repair genitourinary tissue to treat lower urinary tract dysfunction (LUTD) have recently increased thanks in part to advances in stem cell (SC) research. At the International Consultation on Incontinence-Research Society meeting in Bristol in 2018 a proposal was convened to address the question: has the potential of SCs in treating LUTD reached clinical maturity? METHODS: The proposal conducted a literature review and an expert consensus meeting focusing on available data from animal models and clinical trials involving the use of SCs for LUTD. RESULTS: To date, there are only small studies investigating bladder replacement using scaffolds with or without SC. Results have been conflicting because of the variability in cell numbers, biomaterials types, and graft surface differences. Similarly, preclinical results suggest a possible role of SC in bladder outlet obstruction (BOO); however, SC clinical trials for BOO are lacking. Research into the use of SC for female stress urinary incontinence (SUI) is close to reaching clinical maturity. In the Canadian phase 3 randomized controlled trial (RCT), a beneficial effect of adult muscle-derived cells (AMDC) over placebo was detected in reducing the frequency of incontinence episodes, especially after prior anti-incontinence surgery. Only two small studies have been published on male SUI. CONCLUSIONS: Questions remain regarding the mechanism of action of SC injected into the LUT and the viability of cells seeded onto grafts placed into the LUT. Also, the optimal time for intervention with SC therapy in the LUT remains to be elucidated.
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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 | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.005 | 0.005 |
| Insufficient payload (model declined to judge) | 0.008 | 0.002 |
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".