Management of benign prostatic hyperplasia by the primary care physician in the 21st century: the new paradigm.
Bibliographic record
Abstract
Benign prostatic hyperplasia (BPH) is one of the commonest causes of lower urinary tract symptoms (LUTS) in men over age 50. Fifty percent of men over age 50 will require some type of management for BPH/LUTS symptoms. Until about 15 years ago, the most common management for BPH was a transurethral resection of the prostate (TURP) operation. Initially, once a diagnosis of BPH has been made, most men are treated medically. One must first rule out other serious causes of these symptoms, such as prostate cancer, bladder cancer, and other obstructions. For men with an enlarged prostate, there is a good chance that therapy with a 5-alpha-reductase inhibitor (5-ARI) can prevent disease progression and the need for surgery. There has been a lot of recent work on different combination therapies for the treatment of BPH/LUTS. If a patient's serum prostate-specific antigen (PSA) level is greater than 1.5 ng/ml and his prostate volume is greater than 30 cc and he has significant LUTS, then combination medical therapy of an alpha blocker with a 5-ARI is the most effective therapy. After a careful workup, it is quite reasonable and appropriate for the primary care physician to initiate this therapy for a patient with BPH/LUTS.
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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 | 0.005 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.004 | 0.006 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.007 | 0.006 |
| Insufficient payload (model declined to judge) | 0.009 | 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".