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MP03-01 THE BURDEN OF URETHRAL STRICTURE DISEASE IN THE PROVINCE OF ONTARIO

2021· article· en· W3191599006 on OpenAlexaboutno aff
R. Christopher Doiron, Marlo Whitehead, Christopher M. Booth, D. Robert Siemens

Bibliographic record

VenueThe Journal of Urology · 2021
Typearticle
Languageen
FieldMedicine
TopicUrological Disorders and Treatments
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineUrethral strictureIncidence (geometry)UrethroplastyGeneral surgerySurgeryUrethra

Abstract

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You have accessJournal of UrologyTrauma/Reconstruction/Diversion: Urethral Reconstruction (including Stricture, Diverticulum) I (MP03)1 Sep 2021MP03-01 THE BURDEN OF URETHRAL STRICTURE DISEASE IN THE PROVINCE OF ONTARIO R. Christopher Doiron, Marlo Whitehead, Christopher M. Booth, and D. Robert Siemens R. Christopher DoironR. Christopher Doiron More articles by this author , Marlo WhiteheadMarlo Whitehead More articles by this author , Christopher M. BoothChristopher M. Booth More articles by this author , and D. Robert SiemensD. Robert Siemens More articles by this author View All Author Informationhttps://doi.org/10.1097/JU.0000000000001964.01AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookLinked InTwitterEmail Abstract INTRODUCTION AND OBJECTIVE: Urethral stricture disease (USD) is a rare, but frequently morbid condition while access to Canadian surgeons with expertise in urethroplasty is lacking. We describe the burden of USD in the province of Ontario and explore management patterns. METHODS: All male patients with USD in the province of Ontario who received care related to their diagnosis between Apr 2002 – Mar 2020 were identified using data from the Institute for Clinical Evaluative Sciences. Stricture incidence was calculated while an analysis of health care utilization included outpatient, inpatient and emergency department visits for care related to their stricture diagnosis. RESULTS: A total of 118,721 men were identified with a urethral stricture diagnosis during the study period – 66,868 incident cases and 51,853 prevalent cases. Incidence of urethral stricture over the study period was 8 cases/10,000 person years. Overall median (IQR) age at time of diagnosis was 61 (44-72). Over the study period, 2.1% (n=2,448) of patients visited emergency departments (ED) ≥1 due to USD, while 27.3% (n=32,390) had ≥1 ED visit for diagnoses other than USD, determined to be complications secondary to USD. A total of 12.2% (n=14,464) of patients required ≥1 urologic USD–associated intervention in the ED, while 1.7% (n=2,102) required ≥3. Over half (52.2%; n=61,982) of patients were seen in outpatient consultation directly related to USD and 68% (n=80,773) were seen for a non-USD diagnosis determined to be a complication secondary to USD. Patients underwent a mean (SD) of 7.6 (±23.5) diagnostic procedures and 1.4 (±5.4) endoscopic interventions as treatment of their USD during the study period. A total of 1,386 patients (1.2%) underwent a single open reconstruction for treatment of their urethral stricture, while n=253 (0.2%) had ≥2 open procedures during the study period. CONCLUSIONS: USD is not rare, carries a significant burden on the health care system in Ontario with few receiving definitive treatment with urethroplasty. Source of Funding: N/A © 2021 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 206Issue Supplement 3September 2021Page: e21-e21 Advertisement Copyright & Permissions© 2021 by American Urological Association Education and Research, Inc.MetricsAuthor Information R. Christopher Doiron More articles by this author Marlo Whitehead More articles by this author Christopher M. Booth More articles by this author D. Robert Siemens More articles by this author Expand All Advertisement Loading ...

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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)0.000
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.021
Threshold uncertainty score0.153

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.004
Science and technology studies0.0020.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0140.001

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 head0.015
GPT teacher head0.257
Teacher spread0.242 · 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 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".

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Citations0
Published2021
Admission routes1
Has abstractyes

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