New alpha blockers to treat male lower urinary tract symptoms
Bibliographic record
Abstract
PURPOSE OF REVIEW: To date it is unclear whether the selectivity of new alpha-blockers to alpha-adrenergic receptor subtypes translates into more clinical benefits and less adverse effects in clinical practice. We performed a systematic review of the two new Abs silodosin and naftopidil. With the availability of numerous alpha-blockers to treat lower urinary tract symptoms secondary to benign prostatic hyperplasia, the findings of this review will be highly relevant to the field of urology. RECENT FINDINGS: Silodosin was found to be more effective than placebo in improving International Prostate Symptom Score (IPSS) and quality of life scores and as effective as other alpha-blockers. Although the incidence of cardiovascular adverse events of silodosin was similar compared with placebo and other alpha-blockers (tamsulosin, naftopidil, alfuzosin), the sexual adverse events were more common with silodosin. No placebo-controlled randomized trial exists investigating the effects of naftopidil in men with lower urinary tract symptoms secondary to benign prostatic hyperplasia. Naftopidil had similar efficacy with regards to IPSS and quality of life compared with tamsulosin. The rate of adverse events was similar compared with tamsulosin. SUMMARY: The two new selective alpha-blockers, silodosin, and naftopidil showed similar efficacy in IPSS and quality of life compared with other alpha-blockers. However, silodosin has more sexual adverse events.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".