The Impact of MISTs on Australian BPO Surgical Trends
Bibliographic record
Abstract
Background/Objectives: To evaluate the impact of Minimally Invasive Surgical Therapies (MISTs) on Australian trends for surgeries treating lower urinary tract symptoms (LUTSs) caused by benign prostatic obstruction (BPO). The recent adoption of the prostatic urethral lift (PUL) and water vapour thermal therapy (such as Rezum) into the Medicare Benefits Scheme (MBS) item schedule on the 1 March 2024 has likely had an impact on Australian surgical trends and we aim to describe their impact on the use of other commonly offered BPO-related surgeries. Methods: This study analyses population-adjusted rates of BPO-related surgeries in Australia from January 2004 to September 2024 using publicly available online Medicare Statistics and Census Data. Independent t-tests and significance levels were calculated to compare procedure rates before and after the introduction of PUL and Rezum in March 2024. Results: In total, 301,648 BPO surgical procedures were claimed under MBS in Australia from January 2004 to September 2024, with transurethral resection of the prostate (TURP) being the most common (78%). Procedure rates increased overall with significant shifts in treatment preference: TURP rates have steadily declined in Australia after peaking in 2009 (123.4 per 100,000 adult men), whilst photo-selective vaporisation of the prostate (PVP) and enucleation have risen. Following the introduction of PUL and Rezum on 1 March 2024, enucleation and simple prostatectomy rates increased, while Transurethral needle ablation (TUNA) and urethral and prostatic prosthesis (UPP) decreased. TURP rates were unaffected. Conclusions: Throughout the past two decades, BPO surgical trends in Australia have shifted, with TURP declining as PVP and enucleation have risen. The 2024 MBS listing for PUL and Rezum has boosted their uptake whilst reducing both TUNA and UPP claims. Simple prostatectomy rates remained stable.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".