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Record W2041714914 · doi:10.1097/mou.0b013e328323d6d2

Eliminating biofilm from ureteral stents: the holy grail

2009· review· en· W2041714914 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

VenueCurrent Opinion in Urology · 2009
Typereview
Languageen
FieldMedicine
TopicKidney Stones and Urolithiasis Treatments
Canadian institutionsLawson Health Research InstituteWestern UniversitySt Joseph's Health Care
Fundersnot available
KeywordsBiofilmMedicineBiofoulingLimitingIntensive care medicineStentAntibioticsNew horizonsMicrobiologyBacteriaSurgeryBiology

Abstract

fetched live from OpenAlex

PURPOSE OF REVIEW: Biofilms continue to be a major limiting factor in the long-term use of ureteral stents, promoting the development of chronic infections and antibiotic resistance and encrustation. Apart from stent removal in conjunction with antibiotic therapy, there is currently no treatment proven successful for completely eradicating a biofilm-related infection, highlighting the need for continued research in this area. RECENT FINDINGS: Research continues to focus mainly on biofilm prevention, specifically the development of novel coatings comprising antibacterial, antifouling or bacterial signalling compounds. Notably, all three strategies have generated candidate coatings showing recent success both in vitro and in vivo. SUMMARY: Despite the current lack of a completely biofilm-resistant device, coating or treatment strategy, continued research into the causation of bacterial biofilm formation and the continued development of novel antibacterial, antifouling and antibiofilm compounds is promising. Future work should be aimed at more rigorous testing of candidate coatings from both physical and bacterial challenge standpoints as well as increased in-vivo investigation via clinical trials.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.994
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.129
GPT teacher head0.417
Teacher spread0.289 · 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