Retreatment Rates and Postprocedural Complications are Higher than Expected after BPH Surgeries: A US Healthcare Claims and Utilization Study
Bibliographic record
Abstract
Abstract Background Up to 50% of men over 50 and 80% over 80 are affected by BPH. Shared decision-making regarding BPH treatment options can benefit from an improved understanding of relative risks and benefits for various treatments. Methods Data for this longitudinal retrospective population-based cohort study were obtained from a random sample of US Medicare and commercial claims (IBM Watson MarketScan) and restricted to men undergoing BPH surgery (TURP, PVP, PUL, WVTT) from 2015 to 2021 across all sites of service. Retreatments included Holmium laser enucleation and index procedures. Main outcomes were rates of retreatment and procedural complications over 1y, identified via CPT and ICD-9/10CM codes. Considered were procedural complications ≥1d post-index treatment and retreatment for patients with ≥1y data. Univariate cumulative incidence estimates, cumulative proportion and log-rank tests justified inclusion for covariate adjustment in Cox proportional hazard models. Results 43,147 men diagnosed with BPH underwent 22,629 TURP, 11,392 PVP, 7,529 PUL, and 1,597 WVTT. At 1-year post-index: PUL was associated with the lowest rate of complication (PUL 15%, TURP 17%; PVP 19%, ; WVTT 26%); retreatment rates were not different (TURP 5.3%, PVP 5.3%, PUL 5.9%, WVTT 6.2%). At 5yr post-index: retreatment was lowest for TURP (7.0%) and was not significantly different between PVP and PUL (8.9% and 11.6%, respectively). Conclusions The results suggest that within one year of BPH surgery, one-in-twenty patients may require retreatment regardless of treatment choice, and for some technologies as many as one-in-four may require treatment for a complication.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".