International Alliance of Urolithiasis (IAU) guideline on retrograde intrarenal surgery (Russian adaptation)
Bibliographic record
Abstract
Introduction. The emergence of new scientific and clinical evidence on the use of retrograde intrarenal surgery (RIRS) for the management of kidney stones has prompted periodic systematisation, analysis, and evaluation of outcomes to standardise its application and determine future directions for research and development. Objective. To present the Russian adaptation of a guideline on retrograde intrarenal surgery from the International Urolithiasis Alliance guideline series to provide a theoretical basis for urologists performing RIRS. Materials & Methods. A systematic review was conducted on the RIRS-associated publications available in the PubMed database to prepare a set of recommendations during the period from 1 January 1964 until 1 October 2021. The recommendations were evaluated using the GRADE (Grading of Recommendations, Assessment, Development, and Evaluation) system, which classifies, evaluates, develops, and examines recommendations. The modified Oxford Centre for Evidence-Based Medicine's (OCEBM) system for categorising the level of evidence and relevant comments have been applied to assess the strength of the conclusions. Results. The research team conducted a comprehensive analysis of 36 published clinical guidelines on the following topics: 1. Indications and Contraindications 2. Preoperative Imaging 3. Preoperative Ureteral Stenting 4. Preoperative Medications 5. Perioperative Use of Antibiotics 6. Use of Antithrombotic Therapy 7. Anesthesia Issues 8. Intraoperative Positioning 9. Equipment 10. Complications. Conclusion. A series of recommendations for RIRS, offered here should help provide safe and effective performance of RIRS.
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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 | 0.011 | 0.035 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.007 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".