958 Prostatic Artery Embolisation vs. Transurethral Resection for Benign Prostatic Hyperplasia: A Systematic Review and Meta-Analysis
Bibliographic record
Abstract
Abstract Background This systematic review and meta-analysis aimed to comprehensively compare these two therapeutic approaches regarding peri-operative and post-operative outcomes. Method Studies reporting on peri-operative and post-operative outcomes of PAE and TURP in BPH patients were included. Meta-analyses were performed to assess differences in outcomes such as IPSS, post-void residual (PVR), maximum urinary flow rate (Qmax), Prostate volume, procedural time, and Quality of Life (QoL) scores using RevMan 5.4.Methodological assessment was done by using the Newcastle-Ottawa Scale (NOS) for observational studies. Results Our analysis included a total of 9 studies involving 1138 patients. The postoperative subgroup analysis revealed significant differences in IPSS (HR of 1.37 (95% CI: -2.27 to 5.01, p = 0.00001; I2 = 98%), PVR (HR 43.29 (95% CI: -10.38 to 96.96, p = 0.00001; I2 = 99%). In the comprehensive analysis, substantial heterogeneity (98%) was noted, yielding an HR of -9.58 (95% CI: -48.20 to 29.30; p = 0.00001), Prostate volume 13.94 (with a 95% CI: 9.34 to 18.54, resulting in a highly significant p-value of 0.0001 and an I2 statistic indicating 83% heterogeneity), procedural time and QoL, with an HR (54.70) CI: 23-86.39, p<0.00001, I2=96%, and HR (0.27) CI: -0.39-0.93, p<0.00001 and I2=97%, respectively, these all outcomes favoured TURP over PAE. However, post-operative Qmax, (HR -8.48 (95% CI: -13.89 to -3.07, p=0.00001 and an I2 =99%) favoring PAE over TURP. Conversely, PAE exhibited a slower but sustained improvement in QoL scores over time. Complication rates were almost same between the two groups. Conclusions TURP may offer a quicker improvement in BPH; however, PAE also provides a viable alternative with sustained QoL improvements and a potentially lower risk of post-operative complications. Individualized treatment decisions should consider patient preferences and clinical factors.
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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 | 0.012 | 0.025 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.019 | 0.040 |
| Bibliometrics | 0.007 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".