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Record W3110955056 · doi:10.1080/17434440.2020.1848538

Device profile of the LithoVue single-use digital flexible ureteroscope in the removal of kidney stones: overview of safety and efficacy

2020· review· en· W3110955056 on OpenAlexaff
Connor M. Forbes, Colin Lundeen, Sarah C. Beebe, Jonathan P. Moore, Bodo E. Knudsen, Mitchell R. Humphreys, Ben H. Chew

Bibliographic record

VenueExpert Review of Medical Devices · 2020
Typereview
Languageen
FieldMedicine
TopicKidney Stones and Urolithiasis Treatments
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsURETEROSCOPEMedicineUreteroscopySingle useExpert opinionMedical physicsSurgeryIntensive care medicineUreterEngineering

Abstract

fetched live from OpenAlex

Introduction: Flexible ureteroscopy is a commonly performed urologic procedure for visualization and treatment of the upper urinary tracts. Traditionally, ureteroscopy has been performed with reusable scopes, which have large initial purchasing costs. LithoVue was the first widely adopted single-use flexible ureteroscope clinically available in 2016 and has caused reevaluation of this paradigm.Areas covered: This review is an objective assessment of the LithoVue single-use ureteroscope based on available studies at the time of publication. The authors searched major databases for papers that included the term ‘LithoVue’ and included relevant papers. The state of the market, technical specifications, results from clinical studies and cost analyses, and competitors are discussed.Expert opinion: The LithoVue single-use flexible ureteroscope has comparable clinical performance to existing reusable ureteroscopes based on available data. Direct clinical comparisons to competing single-use ureteroscopes, many of which are relatively new, are limited. In numerous pre-clinical studies LithoVue performed favorably compared to available competitors. Cost analyses suggest that benefit of single-use ureteroscopes is institution-specific, and will likely be favorable at a low volume of cases and with high local costs for repairs of reusable scopes.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.008
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.673
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.008
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0050.001
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.085
GPT teacher head0.401
Teacher spread0.316 · 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 teacher head, not a consensus.

Study designSystematic review
Domainnot available
GenreReview

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

Citations5
Published2020
Admission routes1
Has abstractyes

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