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Record W4403842625 · doi:10.1186/s40779-024-00562-3

International Alliance of Urolithiasis (IAU) consensus on miniaturized percutaneous nephrolithotomy

2024· article· en· W4403842625 on OpenAlexafffund
Guohua Zeng, Wen Zhong, Giorgio Mazzon, Wei Zhu, Sven Lahme, Sanjay Khadgi, Janak Desai, Madhu Agrawal, David A. Schulsinger, Mantu Gupta, E. Montanari, J. Martı́nez, Shabir Almousawi, Vincent Emanuel F. Malonzo, Seshadri Sriprasad, Chu Ann Chai, Vimoshan Arumuham, Stefania Ferretti, Wissam Kamal, Kewei Xu, Fan Cheng, Xiaofeng Gao, Jiwen Cheng, Bhaskar Somani, Mordechai Duvdevani, Christian Seitz, Norberto Bernardo, Tarek Ibrahim, Albert Aquino, Takahiro Yasui, Cristian Fiori, Thomas Knoll, Athanasios Papatsoris, Nariman Gadzhiev, Ulanbek Zhanbyrbekuly, Oriol Angerri, Hugo López‐Ramos, Iliya Saltirov, Mohamad Moussa, Guido Giusti, Fábio C. Vicentini, Edgar Beltrán Suárez, Margaret S. Pearle, Glenn M. Preminger, Qinghui Wu, Otaš Durutović, Khurshid R. Ghani, Marcus Vinícius Osorio Maroccolo, Marianne Brehmer, Palle Jørn Sloth Osther, Marek Zawadzki, Azimdjon Tursunkulov, Monolov Nurbek Kytaibekovich, Abdusamad Abdukakhorovich Abuvohidov, C. Lara, Zamari Noori, S.P. Zanetti, Sunil Shrestha, Jean de la Rosette, John D. Denstedt, Zhangqun Ye, Kemal Sarıca, Simon Choong

Bibliographic record

VenueMilitary Medical Research · 2024
Typearticle
Languageen
FieldMedicine
TopicKidney Stones and Urolithiasis Treatments
Canadian institutionsWestern University
FundersSchulich School of Medicine and DentistryTongji Medical College, Huazhong University of Science and TechnologyFondazione IRCCS Ca' Granda Ospedale Maggiore PoliclinicoTongji UniversityHuazhong University of Science and Technologyİstanbul Medipol ÜniversitesiUniversità degli Studi di Milano
KeywordsMedicinePercutaneous nephrolithotomyAllianceGeneral surgeryPercutaneousUrologySurgeryLaw

Abstract

fetched live from OpenAlex

Over the past three decades, there has been increasing interest in miniaturized percutaneous nephrolithotomy (mPCNL) techniques featuring smaller tracts as they offer potential solutions to mitigate complications associated with standard PCNL (sPCNL). However, despite this growing acceptance and recognition of its benefits, unresolved controversies and acknowledged limitations continue to impede widespread adoption due to a lack of consensus on optimal perioperative management strategies and procedural tips and tricks. In response to these challenges, an international panel comprising experts from the International Alliance of Urolithiasis (IAU) took on the task of compiling an expert consensus document on mPCNL procedures aimed at providing urologists with a comprehensive clinical framework for practice. This endeavor involved conducting a systematic literature review to identify research gaps (RGs), which formed the foundation for developing a structured questionnaire survey. Subsequently, a two-round modified Delphi survey was implemented, culminating in a group meeting to generate final evidence-based comments. All 64 experts completed the second-round survey, resulting in a response rate of 100.0%. Fifty-eight key questions were raised focusing on mPCNLs within 4 main domains, including general information (13 questions), preoperative work-up (13 questions), procedural tips and tricks (19 questions), and postoperative evaluation and follow-up (13 questions). Additionally, 9 questions evaluated the experts' experience with PCNLs. Consensus was reached on 30 questions after the second-round survey, while professional statements for the remaining 28 key questions were provided after discussion in an online panel meeting. mPCNL, characterized by a tract smaller than 18 Fr and an innovative lithotripsy technique, has firmly established itself as a viable and effective approach for managing upper urinary tract stones in both adults and pediatrics. It offers several advantages over sPCNL including reduced bleeding, fewer requirements for nephrostomy tubes, decreased pain, and shorter hospital stays. The series of detailed techniques presented here serve as a comprehensive guide for urologists, aiming to improve their procedural understanding and optimize patient outcomes.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.159
metaresearch head score (Gemma)0.173
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.159
Threshold uncertainty score0.839

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.1590.173
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.004
Bibliometrics0.0110.008
Science and technology studies0.0040.004
Scholarly communication0.0050.006
Open science0.0060.014
Research integrity0.0090.008
Insufficient payload (model declined to judge)0.0070.003

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.

Opus teacher head0.060
GPT teacher head0.416
Teacher spread0.356 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreOther

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".

Quick stats

Citations21
Published2024
Admission routes2
Has abstractyes

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