Retrograde Ureteroscopic Management of Large Renal Calculi: A Single Institutional Experience and Concise Literature Review
Bibliographic record
Abstract
INTRODUCTION: Advances in flexible ureteroscope design and accessory instrumentation have allowed for more challenging cases to be treated ureteroscopically. Here, we evaluate our experience with ureteroscopy (URS) for the management of large renal calculi (≥2 cm) and provide a concise review of recent reports. METHODS: A retrospective review was undertaken of all URS cases between 2004 and 2014 performed by the endourologic team at a single academic tertiary care institution. We identified patients with at least one stone ≥2 cm managed with retrograde URS. Stone size was defined as the largest linear diameter of the index stone. Small diameter flexible ureteroscopes were used primarily with holmium laser. Patient demographics, intraoperative data, and postoperative outcomes were evaluated. RESULTS: We evaluated 167 consecutive patients who underwent URS for large renal stones ≥2 cm. The initial reason for choosing URS included patient preference (29.5%), failure of other therapies (8.2%), anatomic considerations/body habitus (30.3%), and comorbidities (28.8%). Mean patient age was 55.5 years (22-84). The mean stone size was 2.75 cm with mean number of procedures per patient of 1.65 (1-6). The single session stone-free rate was 57.1%, two-stage procedure stone-free rate was 90.2% and three-stage stone-free rate was 94.0%. Access sheaths were used in 47% of patients. An association was identified between stone size and patient outcomes; smaller stones correlated with decreased number of procedures. Postoperative complications were minor. CONCLUSIONS: Single or multi-stage retrograde ureteroscopic lithotripsy is a safe and effective mode of surgical management of large renal calculi. Total stone burden is a reliable predictor of the need for a staged procedure and of stone-free rate.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".