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Advances in ureteral stents.

2014· review· en· W2177234986 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenuePubMed · 2014
Typereview
Languageen
FieldMedicine
TopicInfectious Aortic and Vascular Conditions
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsStentUreterMedicineAntimicrobialSurgeryChemistry

Abstract

fetched live from OpenAlex

Ureteral stents are commonly used in urology. Every urologist is familiar with the problems that are associated with stents including infection, encrustation, and bothersome symptoms. These problems limit and affect the use of ureteral stents which are necessary, even in light of the problems they can cause. New designs such as a helically cut ureteral stent which is designed to stretch and conform to the ureter is designed to improve comfort. Drug-eluting designs with an antimicrobial (triclosan) are designed to reduce bacterial adherence to ureteral stents. Chlorhexidine, an antiseptic, has been incorporated into a stent and held in place by a slow release varnish to prevent biofilm formation. Combinations of antibiotics coated directly on the stent and administered systemically have been shown to reduce stent colonization both in vitro and in vivo. Gel-based ureteral stents were also showed to reduce bacterial infection and colonization. Bioabsorbable materials have also been designed to reduce infection, symptoms and prevent the forgotten stent syndrome. Newer designs including stents based on guidewire technology, gels, and a combination of self-expanding wire stents with polymer films are reviewed. There is hope on the horizon that new stents will be able to effectively tackle problems that are often seen with ureteral stents.

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.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.995
Threshold uncertainty score0.553

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.037
GPT teacher head0.319
Teacher spread0.282 · 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