Extended LUTS medication use following BPH surgical treatment: a US healthcare claims analysis
Bibliographic record
Abstract
BACKGROUND: Postoperative medication use is an important yet relatively unexplored element of the benign prostatic hyperplasia patient journey. We assessed and compared the percentage of patients who required medication postoperatively after the three most common BPH surgeries in the real world: transurethral resection of the prostate (TURP), photovaporization procedure with GreenLight Laser (PVP), and prostatic urethral lift (PUL) with the UroLift system. METHODS: Within a random representative sample of US Medicare and commercial insurance claims, patients with at least one year of follow-up data available after an outpatient TURP, PVP, or PUL procedure were linked to pharmaceutical claims to elucidate rates of continuous and de novo use of alpha-blockers, 5-alpha reductase inhibitors, or combination medical therapy. Periods of interest were perioperative (use within three months postoperatively and not beyond) and one and five years postoperatively. RESULTS: 36 629 men diagnosed with BPH underwent outpatient TURP (n = 20 319), GreenLight PVP (n = 10 517) and PUL (n = 5 793) procedures within the claims dataset. The rate of medical therapy use through one year was lowest for PUL (4.1%) compared to TURP (6.2%) and PVP (6.6%), and was equivalent between procedures through five years (10.6% TURP, 10.4% PVP, and 10.3% PUL). CONCLUSIONS: Patients who undergo surgery to treat BPH may desire to discontinue or bypass BPH medications. However, these data demonstrated that approximately 10% of BPH patients used medication through five years postoperatively, regardless of which procedure they underwent.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".