ArticleInternational journal of clinical practice2022
CT-Based Predictor for the Success of 12/14-Fr Ureteral Access Sheath Placement.
Article in International journal of clinical practice, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
3 citing papers in PubMed, 5 citations in OpenAlex.
- Machine learning to predict ureteral access sheath placement failure in flexible ureteroscopy: development and prospective validation.BMC urology · 2026Article
- Iatrogenic upper urinary tract injuries during ureteroscopy for urolithiasis: a comprehensive review on incidence, mechanisms and preventative strategies.Nature reviews. Urology · 2025Review
- Development and validation of a predictive model for failure of ureteral access sheath placement in patients with ureteral calculi.BMC urology · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Purpose: Ureteral access sheaths (UAS) are widely used in retrograde intrarenal surgery (RIRS), and this study aimed to develop a model for predicting the success of UAS placement based on computed tomography. Methods: We analyzed the clinical data of 847 patients who received ureteroscopy. Data on patient and stone characteristics and several computed tomography (CT)-based measurements were collected. A nomogram predicting the success of UAS placement was developed and validated using Results: Two hundred and forty-seven patients were identified. Twenty-five patients (10.1%) failed to pass through the UAS. A model with three factors including the short diameter of ureteral calculi, the short diameter of hydronephrosis, and the diameter of the narrowest part of the renal parenchyma was to be strongly practical and had a high area under the curve on internal validation (80.3%). Using a threshold cutoff of 92%, the sensitivity and specificity for predicting UAS placement were 0.35 and 0.92, respectively. Conclusion: Our study provides a nomogram for predicting the success of UAS placement, and this model could help discriminate patients who are likely to suffer from failed UAS insertion; preoperative ureteral stenting is recommended according to the prediction.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.