Suction use in ureterorenoscopy: A systematic review and meta‐analysis of comparative studies
Bibliographic record
Abstract
Objectives: Ureterorenoscopy is seeing a bloom of technological advances, one of which is incorporating suction. The objective of this study is to systematically review existing literature regarding suction use in rigid and flexible ureterorenoscopy and perform meta-analysis of studies comparing suction versus no suction ureteroscopy or mini percutaneous nephrolithotomy (PCNL). Methods: A literature search was performed (November 2023) in MEDLINE, Embase and Cochrane CENTRAL. Study protocol was registered at PROSPERO (CRD42023482360). Comparative studies (observational and randomized) were eligible for inclusion if they compared suction versus no suction group and reported at least one primary outcome of interest (stone-free or complication rate). Results: Sixteen studies (5 randomized and 11 observational), analysing 1086 and 1109 patients in standard and suction groups, respectively, were included. Final stone-free rates (SFRs), overall and infectious complications and length of hospital stay exhibited significant improvement when suction was used. When mini-PCNL was compared with flexible ureterorenoscopy with suction, no differences were found in terms of stone-free and infectious complications rates. Conclusions: Ureterorenoscopy is a commonly performed endoscopic procedure for urolithiasis treatment, the success of which is defined by SFRs and complication rates. Application of suction via ureteral access sheaths, ureteral catheters or scopes may provide improved SFRs, reduced overall and infectious complication rates, along with a reduction in length of hospital stay. Further randomized studies are needed to validate these findings and standardize indications and protocols.
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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 | 0.019 | 0.036 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.018 | 0.034 |
| Bibliometrics | 0.006 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".