Bibliographic record
Abstract
Introduction: Ureteropelvic junction obstruction causes upper urinary tract obstruction, resulting in pain, infections, and renal impairment. Pyeloplasty with Double-J stents is the standard treatment, but stents cause significant morbidity. Stentless approaches may reduce symptoms while maintaining efficacy. Methods: Systematic review following Preferred Reporting Items for Systematic Reviews and Meta-analyses 2020 guidelines (International Prospective Register of Systematic Reviews: CRD42025643943). PubMed, Embase, and Cochrane were searched through March 2025. “Studies comparing stented versus stentless pyeloplasty in adults (≥18 years) were included”. Primary outcomes were surgical success and complications. Secondary outcomes included urinary leakage, reintervention, and hospital stay. Narrative synthesis was performed due to heterogeneity. Results: Ten studies encompassing 5820 patients were included, comprising one randomized controlled trial, four prospective, and five retrospective studies. Success rates ranged from 66.7% to 100% for stented procedures and 88%–100% for stentless approaches, with no significant difference in most studies. Stented patients experienced higher rates of lower urinary tract symptoms (64.7%–100%) compared to stentless groups (0%–3.8%), as well as hematuria (27%–95.4%) versus 0%–4.3%, with variable urinary tract infection rates. Stentless groups showed increased urinary leakage up to 24%, though mostly self-limited. Twenty-three stentless patients required secondary stenting, while thirteen stented patients needed reintervention for stricture or complications. Conclusions: Stentless pyeloplasty is effective in selected adults, significantly reducing stent-related morbidity without compromising success rates when performed with meticulous technique and appropriate patient selection.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".