Trends of Benign Prostatic Hyperplasia Procedures in Ambulatory Surgery Settings
Bibliographic record
Abstract
Introduction:Holmium laser enucleation of the prostate (HoLEP) has evidenced-based advantages in treating benign prostatic hyperplasia (BPH) relative to other interventions. Unfortunately, the adoption of HoLEP has remained relatively low in Medicare and the National Surgical Quality Improvement Program populations. HoLEPs role as an inpatient surgical intervention is changing as advancements in the technique and systems have demonstrated the feasibility of same-day discharge. Thus, our objective was to evaluate national HoLEP trends in ambulatory surgery settings from 2016 to 2019. Materials and Methods:The Nationwide Ambulatory Surgery Sample (NASS) is the largest national all-payer database of ambulatory surgical encounters, managed by the Agency for Healthcare Research and Quality. A cross-sectional retrospective analysis of the 2016 and 2019 NASS was performed. Rates of BPH surgeries were calculated and stratified by age, census region, and primary payer to compare across time points for trends. Chi-squared tests and two-sample t-tests were completed for categorical and continuous variables, respectively. Results:The total number of ambulatory BPH surgeries fell 20% between 2016 (n = 124,538) and 2019 (n = 100,593). In 2016, HoLEP lagged behind photoselective vaporization of the prostate (PVP) and transurethral resection of prostate (TURP) with 4.7% of surgeries but rose to the second most common procedure in 2019 with 8.3% of total surgeries. TURP was the most common intervention (62.6% in 2016, 90.7% in 2019). Simple prostatectomy was the most expensive intervention. By U.S. census region, more HoLEPs were carried out in the South (43.1% in 2016, 37.5% in 2019) and Midwest (26.8% in 2016, 31.7% in 2019). Conclusions:Overall, HoLEP uptake is increasing. HoLEP has replaced greenlight PVP as the second most frequently used intervention. The rate of ambulatory HoLEPs has nearly doubled despite a general decrease in the number of surgeries.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.000 | 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 teacher head, 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".