Measuring the efficacy of Serenoa repens (USPlus) extract with mobile uroflowmetry.
Bibliographic record
Abstract
INTRODUCTION: Benign prostatic hyperplasia (BPH) is a prevalent condition affecting a significant portion of the male population, leading to secondary lower urinary tract symptoms (LUTS). Alternative therapies such as phytotherapy using Lipidosterolic extract of Serenoa repens (LSESR USPlus) are commonly used. However, the efficacy of LSESr remains controversial due to conflicting data. We sought to determine the effect of a standardized USP-verified Saw Palmetto extract on male LUTS secondary to BPH. MATERIALS AND METHODS: In this prospective single-arm trial, we investigated the efficacy of a standardized USP-verified Saw Palmetto extract in treating male LUTS secondary to BPH. We utilized the ProudP mobile application for home uroflowmetry and symptom assessment. RESULTS: Results from 46 patients using 320 mg daily of USP-verified Saw Palmetto extract revealed significant improvements in IPSS and QoL scores at 12 weeks compared to baseline, particularly in patients with moderate symptoms. Uroflowmetry parameters also improved with increased flow rates, primarily in patients with mild symptoms. CONCLUSION: Our findings support the efficacy of USP-verified Saw Palmetto extract in alleviating LUTS in men with BPH. Further studies are warranted in larger, diverse cohorts over longer follow up periods.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| 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 | 0.000 |
| 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".