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Record W4404506820 · doi:10.1002/nau.25627

Trends in Overactive Bladder Therapy: Associations Between Clinical Care Pathways, Practice Guidelines, and Therapy Utilization Patterns

2024· article· en· W4404506820 on OpenAlexaff
Hodan Mohamud, Shada Sinclair, Susanna Gunamany, Claire S. Burton, Chiyuan A. Zhang, Raveen Syan, Ekene Enemchukwu

Bibliographic record

VenueNeurourology and Urodynamics · 2024
Typearticle
Languageen
FieldMedicine
TopicUrinary Bladder and Prostate Research
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsMedicineOveractive bladderPharmacotherapyGuidelineManual therapyRetrospective cohort studyCurrent Procedural TerminologyPhysical therapyInternal medicineAlternative medicineSurgery

Abstract

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INTRODUCTION: Overactive bladder (OAB) is a chronic condition with significant financial and health-related consequences. Guidelines and treatment pathways were created to optimize care and provide a clinical framework for diagnosing and managing OAB. However, the impact of these efforts and patterns of medical treatment for OAB are poorly understood. Therefore, we sought to evaluate overall trends in therapy utilization before and after the 2014 American Urological Association (AUA)/Society of Urodynamics, Female Pelvic Medicine and Urogenital Reconstruction (SUFU) OAB guideline amendment and publication of the OAB clinical care pathway in 2016. METHODS: In this retrospective cohort study, we analyzed data from Optum, a national administrative health and pharmacy claims database, between 2013 and 2018. All adult patients diagnosed with idiopathic OAB were identified by the International Classification of Diseases 9th and 10th Revision codes. Oral OAB therapies were identified using National Drug Codes, while third-line therapy procedures, onabotulinumtoxinA (BTX), sacral neuromodulation (SNM), and percutaneous tibial nerve stimulation (PTNS), were identified using Current Procedural Terminology (CPT) codes. The study's primary outcome was the annual number of OAB prescriptions filled by pharmacotherapy class and the number of minimally invasive therapies performed during the study period. The secondary outcome was the association between OAB therapy utilization and various clinical and sociodemographic factors. Patterns of care were analyzed from 2013 to 2018, and initial treatment with each therapy was collected, excluding repeat procedures from the analysis. RESULTS: 1 825 782 patients were included in the study. The mean age was 61.1 ± 16.7 years, and 1 071 420 patients were female (58.7%). The number of new OAB diagnoses increased by 369% from 2013 to 2017. During the 6-year study period, 347 052 (19%) patients were treated with oral and/or third-line therapies. The overall number of oral medications prescribed peaked in 2016, followed by a 17% decline between 2016 and 2018. In 2013, the two most prescribed oral medications were oxybutynin (46%) and solifenacin (31.8%). By 2018, mirabegron (18.5%) surpassed solifenacin (16.5%), with oxybutynin still accounting for most prescriptions written (55%). Eighty percent of all initial mirabegron prescriptions were filled by patients over the age of 65. The rate of third-line therapy procedures almost doubled between 2013 and 2018 (9-17 procedures per 1000 OAB patients, p < 0.001). CONCLUSIONS: Following the publication of the first OAB guidelines, there was an increase in OAB diagnoses, followed by a decrease in anticholinergic medication use, and a rise in beta-3 agonist utilization in patients over 65 years old. Additionally, there was greater adoption of third-line OAB therapies. These trends indicate that OAB therapy guidelines and clinical practice pathways may influence treatment patterns. Given the recent publication of the OAB guidelines, further studies are necessary to assess their impact on therapy utilization patterns.

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)0.001
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 score0.523
Threshold uncertainty score0.556

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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 head0.185
GPT teacher head0.464
Teacher spread0.279 · 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

Citations10
Published2024
Admission routes1
Has abstractyes

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