Use of the ureteral access sheath during ureteroscopy: A systematic review and meta-analysis
Bibliographic record
Abstract
The debate still rages on for the usefulness of ureteral access sheath (UAS). Therefore, a meta-analysis to discuss the effects of applying UAS during ureteroscopy was performed. The protocol for the review is available on PROSPERO (CRD42017052327). A literature search was conducted up to November, 2017 using the Web of science, PUBMED, EMBASE and Cochrane Library. The quality of articles was assessed by the Jadad scale and Newcastle Ottawa Scale (NOS). Egger's test and the trim-and-fill method were used to evaluate publication bias. Effect sizes were calculated by pooled odds ratio (ORs) and mean differences (MDs). Sensitivity analyses and subgroup analyses were performed to explore the origin of heterogeneity. Eight trials with a total of 3099 patients and 3127 procedures were identified. Results showed no significant difference in stone-free rate (SFR) (OR = 0.83, 95% CI 0.52-1.33, P = 0.45), intraoperative complications (OR = 1.16, 95% CI 0.81-7.69, P = 0.88), operative time (MD = 4.09, 95% CI -15.08-23.26, P = 0.68) and hospitalization duration (MD = -0.13, 95% CI -0.32-0.06, P = 0.18). However, the incidence of postoperative complications was higher in UAS group (OR = 1.46, 95% CI 1.06-2.00, P = 0.02). Evidence from meta-analysis indicated that the use of UAS during ureteroscopy did not manifest advantages. However, given the intrinsic restrictions of the quality of selected articles, more randomized controlled trials (RCTs) are warranted to update the findings of this analysis.
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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 | 0.015 | 0.028 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.020 | 0.041 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| 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".