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Record W2587069462 · doi:10.1002/9781119085713.ch25

Evidence Base for Stenting

2017· other· en· W2587069462 on OpenAlexaff
Rami Elias, Edward D. Matsumoto

Bibliographic record

Venuenot available
Typeother
Languageen
FieldMedicine
TopicKidney Stones and Urolithiasis Treatments
Canadian institutionsMcMaster University
Fundersnot available
KeywordsMedicinePercutaneous nephrolithotomyUreteroscopyHydronephrosisStentUreterGeneral surgeryUreteropelvic junctionPercutaneousLithotripsySurgeryIntensive care medicineUrinary systemInternal medicine

Abstract

fetched live from OpenAlex

This chapter focuses on the most commonly contended scenarios where stents may or may not be utilized. It appraises the medical literature surrounding these scenarios and provides an examination of the supporting evidence behind their management. The chapter also focuses on ureteral calculi-related obstruction and resultant infected hydronephrosis. Ureteral stenting after endoscopic lithotripsy is thought to prevent ureteral obstruction and renal colic that may develop secondary to stone manipulation. The chapter provides references to and describes the results of critically appraised literature in order to support diagnostic and treatment measures for acute infectious obstruction. It examines the evidence for the use of ureteric stents during a percutaneous nephrolithotomy (PCNL). The current ureteral guidelines for the management of ureteral calculi endorsed by the AUA and EUA groups state the use of ureteral stenting after ureteroscopy for stone management is an optional adjunctive procedure.

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)0.019
metaresearch head score (Gemma)0.147
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 score0.030
Threshold uncertainty score0.101

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0190.147
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0040.006
Bibliometrics0.0090.006
Science and technology studies0.0020.002
Scholarly communication0.0080.005
Open science0.0040.003
Research integrity0.0060.009
Insufficient payload (model declined to judge)0.0300.006

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 head0.106
GPT teacher head0.366
Teacher spread0.260 · 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

Citations0
Published2017
Admission routes1
Has abstractyes

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