Procedural Intervention for Benign Prostatic Hyperplasia in Men ≥ Age 70 Years – A Review of Published Literature
Bibliographic record
Abstract
Objective: We set out to review studies reporting on the use of surgical intervention to treat Benign Prostatic Hyperplasia in elderly men ≥70 years of age. Methods: A systematic literature search was conducted using Scopus, PubMed-MEDLINE, Cochrane, and Wiley Online Library databases including studies published between January 2012 through December 2022. This 10-year interval was chosen given the recent plethora of new modalities that have entered the BPH armamentarium, many of which have been marketed as appropriate for older and high-risk patients. The following database search words were used either individually or in conjunction: "BPH", "elderly", "surgical", "ablation", "resection", "embolization", and "aging". Results: We identified 28 studies for inclusion in this review. The pros and cons of these modalities are presented, specifically as applicable to an older and higher risk population. Conclusion: There are a wide variety of surgical procedures available for surgically treating BPH in elderly men with varying states of health. Each of these comes with different risks and benefits, supporting that individualized approaches are important. Long-term data and further studies comparing modalities, specifically as regards the elderly and frail, would enhance our approaches to BPH treatment in this patient population.
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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 | 0.003 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.011 | 0.011 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".