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MP47-15 POINT OF CARE ULTRASOUND IN UROLOGY: BUILDING A FEASIBLE INTRODUCTORY TRAINING PROGRAM

2020· article· en· W3021579387 on OpenAlexaboutno aff
Michael Uy, Catherine Anne Lovatt, Jennifer Hoogenes, Carol Bernacci, Edward D. Matsumoto

Bibliographic record

VenueThe Journal of Urology · 2020
Typearticle
Languageen
FieldMedicine
TopicPelvic and Acetabular Injuries
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineUrologyCompetence (human resources)Acute scrotumPoint of care ultrasoundUltrasoundMedical educationScrotumMedical physicsRadiologySurgeryPsychology

Abstract

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You have accessJournal of UrologySurgical Technology & Simulation: Training & Skills Assessment II (MP47)1 Apr 2020MP47-15 POINT OF CARE ULTRASOUND IN UROLOGY: BUILDING A FEASIBLE INTRODUCTORY TRAINING PROGRAM Michael Uy*, Catherine Anne Lovatt, Jennifer Hoogenes, Carol Bernacci, and Edward D. Matsumoto Michael Uy*Michael Uy* More articles by this author , Catherine Anne LovattCatherine Anne Lovatt More articles by this author , Jennifer HoogenesJennifer Hoogenes More articles by this author , Carol BernacciCarol Bernacci More articles by this author , and Edward D. MatsumotoEdward D. Matsumoto More articles by this author View All Author Informationhttps://doi.org/10.1097/JU.0000000000000902.015AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookLinked InTwitterEmail Abstract INTRODUCTION AND OBJECTIVE: Point of care ultrasound (PoCUS) is a widely used bedside tool in urology. Applications include the assessment of an undifferentiated acute scrotum, renal colic, and the guidance of suprapubic catheter placement. However, the user-dependent nature of this modality necessitates appropriate use and competence. The objective of this study was to develop a feasible introductory PoCUS course for urology residents. METHODS: Urology residents of all years completed a 3-hour online course, followed by a 3-hour hands-on seminar involving kidney, bladder, and testicular sonographic scanning. Low cost simulated testicular phantoms were constructed and utilized (Figure 1). Course material was developed by licensed ultrasound technologists, based on the Sonography Canada National Competency Profiles. Pre- and post-course surveys focused on residents’ user-confidence, while pre- and post-course multiple-choice questionnaires (MCQ) assessed theoretical knowledge. RESULTS: Fourteen urology residents (n = 14) participated in the course. Theoretical knowledge in PoCUS improved significantly (p < 0.001) (Table 1). Self-rated confidence in manipulation of ultrasound controls, doppler imaging, and PoCUS of the kidney, bladder, and testicles also improved (all p < 0.001). All participants indicated that the course increased their likelihood of PoCUS use in clinical practice, and that POCUS training should be integrated into a urology training curriculum. CONCLUSIONS: We successfully developed and executed a feasible foundational PoCUS course for urology residents based on national ultrasound training guidelines. Following the course, residents significantly improved in user confidence and theoretical knowledge. This easily modifiable and reproducible course can be utilized as an introductory tool for urology residents to begin developing competency in ultrasound, and may act as a stepping stone for further competency-based training programs. Source of Funding: None © 2020 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 203Issue Supplement 4April 2020Page: e690-e690 Advertisement Copyright & Permissions© 2020 by American Urological Association Education and Research, Inc.MetricsAuthor Information Michael Uy* More articles by this author Catherine Anne Lovatt More articles by this author Jennifer Hoogenes More articles by this author Carol Bernacci More articles by this author Edward D. Matsumoto More articles by this author Expand All Advertisement PDF downloadLoading ...

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.536
Threshold uncertainty score0.301

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.026
GPT teacher head0.300
Teacher spread0.274 · 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 designBench or experimental
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
Published2020
Admission routes1
Has abstractyes

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