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Record W4313886208 · doi:10.2147/tcrm.s269318

Assessing Quality-of-Life of Patients Taking Mirabegron for Overactive Bladder

2023· review· en· W4313886208 on OpenAlexaff
Christina Shaw, William Gibson

Bibliographic record

VenueTherapeutics and Clinical Risk Management · 2023
Typereview
Languageen
FieldMedicine
TopicUrinary Bladder and Prostate Research
Canadian institutionsUniversity of AlbertaUniversity of British Columbia
Fundersnot available
KeywordsMirabegronNocturiaMedicineOveractive bladderUrinary urgencyLower urinary tract symptomsQuality of life (healthcare)UrologyUrinary incontinencePsychological interventionUrinary systemPopulationInternal medicineGynecologyAlternative medicineNursingProstatePathology

Abstract

fetched live from OpenAlex

Lower urinary tract symptoms (LUTS), including urgency, frequency, and urgency incontinence, are highly prevalent in the general population and increase in prevalence with increasing age. All LUTS, but notable urgency and urgency incontinence, are associated with negative impact on quality-of-life (QoL), with multiple aspects of QoL affected. Urgency and urgency incontinence are most commonly caused by overactive bladder (OAB), the clinical syndrome of urinary urgency, usually accompanied by increased daytime frequency and/or nocturia in the absence of infection or other obvious etiology, which may be treated with conservative and lifestyle interventions, bladder antimuscarinic drugs, and, more recently, by mirabegron, a β3 agonist. This narrative review describes the impact of OAB on QoL, quantifies this impact, and outlines the evidence for the use of mirabegron in the treatment of, and improvement in QoL in, people with OAB.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.480
GPT teacher head0.583
Teacher spread0.103 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations6
Published2023
Admission routes1
Has abstractyes

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