Nonneurogenic female bladder outlet obstruction: Conservative and medical management
Bibliographic record
Abstract
INTRODUCTION: In nonneurogenic female bladder outlet obstruction (BOO), management goals include reduction of outlet resistance to increase urinary outflow and improve bladder voiding to prevent or reduce lower and upper urinary tract (LUT and UUT) function deterioration, by correcting the underlying etiology. As significant progress has been achieved in the conservative and pharmacological management of nonneurogenic female BOO, the purpose of this article is to review and summarize the current literature. MATERIALS AND METHODS: For this narrative review, a PubMed® search was performed by cross-referencing the keywords "female bladder outlet obstruction," "female voiding dysfunction," "conservative management," "pharmacological management," and "treatment" with various terms related to the management of female BOO. Clinical practice guidelines and landmark reviews from the most renowned experts in the field were also used. MANAGEMENT: This review discusses and summarizes the conservative and pharmacological management of nonneurogenic female BOO based on the most relevant data currently available in the literature. CONCLUSION: The recent advances in the understanding of underlying mechanisms involved in female BOO allow for more individualized management. Conservative and pharmacological options show interesting outcomes, particularly in the context of a functional cause of BOO. Overall, the level of evidence is still low regarding the use of conservative and pharmacological measures and more long-term data are required.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".