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Record W2995234885 · doi:10.1002/nau.23964

Are there different patterns of detrusor overactivity which are clinically relevant? ICI‐RS 2018

2019· review· en· W2995234885 on OpenAlexaff
Jerzy B. Gajewski, Andrew Gammie, John E. Speich, Ruth Kirschner‐Hermanns, Stefan De Wachter, Brigitte Schurch, Cees Korstanje, Françoise A. Valentini, Mohammad Sajjad Rahnama’i

Bibliographic record

VenueNeurourology and Urodynamics · 2019
Typereview
Languageen
FieldMedicine
TopicUrinary Bladder and Prostate Research
Canadian institutionsDalhousie University
Fundersnot available
KeywordsMedicineTerminologyClinical significanceRelevance (law)Overactive bladderStandardizationAlternative medicinePathology

Abstract

fetched live from OpenAlex

INTRODUCTION: Different patterns of detrusor overactivity (DO) have been described and included in several standardization terminology documents. However, it is unclear if these different patterns have any clinical significance. METHODS: This is a report of the proceedings of Proposal 3: "Are there different patterns of detrusor overactivity which are clinically relevant?" from the annual International Consultation on Incontinence-Research Society (ICIRS) meeting, which took place from 14 to 16 June 2018, in Bristol, UK. RESULTS: We have collected and discussed, as a committee, the evidence about different urodynamic (UD) patterns of detrusor overactivity and their potential clinical significance. We reviewed the important previous basic research and clinical studies and compiled summaries. The discussion focused on clinical relevance of different UD patterns of DO and what further research is required. CONCLUSIONS: There are several UD definitions of patterns of detrusor overactivity, however the clinical relevance of these definitions remains unclear. Future research should concentrate on defining the pattern of DO in relation to clinical diagnosis, gender, age, and treatment outcomes.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.495
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0030.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.003
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 head0.077
GPT teacher head0.382
Teacher spread0.305 · 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 designObservational
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

Citations7
Published2019
Admission routes1
Has abstractyes

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