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Record W4361215842 · doi:10.3389/fruro.2023.1158260

Intermittent catheterization: A patient-centric approach is key to optimal management of neurogenic lower urinary tract dysfunction

2023· article· en· W4361215842 on OpenAlexaff
Andrei V. Krassioukov, Blayne Welk, Desiree Vrijens, Sabrina Islamoska, Kim Bundvig Barken, V. Keppenne, Michel Wyndaele, Matthias Walter

Bibliographic record

VenueFrontiers in Urology · 2023
Typearticle
Languageen
FieldMedicine
TopicUrinary Bladder and Prostate Research
Canadian institutionsWestern UniversityGF Strong Rehabilitation CentreUniversity of British ColumbiaInternational Collaboration On Repair DiscoveriesVancouver Coastal Health
FundersColoplast
KeywordsIntensive care medicineMedicineUrinary systemUrinary catheterizationQuality of life (healthcare)ScrutinyInternal medicineNursing

Abstract

fetched live from OpenAlex

The value of disposable, single-use catheters has come under scrutiny in recent years with a growing attention on environmental sustainability. Intermittent catheterization (IC) is a widely available and minimally invasive technique for management of lower urinary tract dysfunction. Effective IC for individuals with neurogenic lower urinary tract dysfunction can promote their independence and improve quality of life. Are there alternative options within IC that could minimize environmental impact without compromising the safety and effectiveness of single-use catheters? How does the future of IC look - environmentally friendly, biodegradable, disposable catheters may be complementary to certified reusable catheters? In the midst of this debate, it is important to emphasize that individuals have the right to choose the best evidence-based treatment available. Here we consider the current landscape for IC with a focus on chronic use in individuals with neurogenic lower urinary tract dysfunction.

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)0.000
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.375
Threshold uncertainty score0.532

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
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 head0.018
GPT teacher head0.264
Teacher spread0.247 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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

Citations3
Published2023
Admission routes1
Has abstractyes

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