Cystolitholapaxy Without Transurethral Resection of the Prostate: Clinical Outcomes and Predictors of Subsequent Resection
Bibliographic record
Abstract
Background/Objectives: Limited data exist on the outcomes of men with bladder stones undergoing cystolitholapaxy alone versus cystolitholapaxy with concurrent transurethral resection of the prostate (TURP). Additionally, factors associated with the need for subsequent TURP in these patients are not well defined. This study aimed to compare the clinical outcomes in men undergoing cystolitholapaxy alone with those undergoing concurrent cystolitholapaxy with TURP, and determine what factors were associated with the need for subsequent TURP. Methods: A retrospective review was conducted of men undergoing cystolitholapaxy at a single Australian hospital between 2014 and 2021. Patients were grouped into cystolitholapaxy alone (Group A) and cystolitholapaxy with concurrent TURP (Group B). Clinical outcomes compared included rates of acute urinary retention (AUR), urinary tract infection (UTI), and subsequent TURP. Prostate volume (PV), stone size, and the presence of intravesical prostatic protrusion (IPP) were evaluated as potential predictors of subsequent TURP in Group A. Results: Fifty men were included in the final analysis, with a median follow-up of 50 months (interquartile range [IQR] 24–81). Baseline characteristics did not differ significantly between groups. There was no statistically significant difference in the rates of AUR (11% vs. 13%) or UTI (22% vs. 30%) between Group A and Group B, respectively. However, 41% of Group A underwent subsequent TURP, compared to 9% in Group B (p = 0.0112). Within Group A, those requiring subsequent TURP had a significantly greater PV (65 vs. 34 cc, p = 0.0059), larger stone size (3.5 vs. 2.0 cm, p = 0.0175), and a higher prevalence of IPP (82% vs. 6%, p < 0.001). Conclusions: Cystolitholapaxy alone is a viable initial treatment for bladder stones, with comparable clinical outcomes to concurrent TURP. PV, stone size, and IPP may help identify patients likely to require future TURP, enabling more tailored treatment and potential reduction in TURP-related morbidity.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".