NCT07394335

Brief Summary

Urodynamic investigations, including cystometry, pressure-flow studies, and electromyography, are considered the gold standard for the objective diagnosis of lower urinary tract dysfunction according to current international guidelines. However, accurate interpretation requires simultaneous analysis of multiple pressure signals, identification of artifacts, and application of complex nomograms, making urodynamics one of the most challenging diagnostic skills to master during urology residency training. Traditional training largely depends on apprenticeship-based exposure, which is highly variable across training centers. The primary aim of this prospective educational study is to evaluate the effectiveness of a large language model (LLM), as an interactive tutor in improving urology residents' urodynamic interpretation skills and learning curve. By providing structured theoretical instruction, case-based guidance, and real-time feedback through a standardized case pool, this study investigates whether AI-assisted mentorship can accelerate skill acquisition, enhance diagnostic accuracy, and offer a standardized, accessible educational model for urodynamic training.

Trial Health

43
At Risk

Trial Health Score

Automated assessment based on enrollment pace, timeline, and geographic reach

Trial has exceeded expected completion date
Enrollment
13

participants targeted

Target at below P25 for not_applicable

Timeline
Completed

Started Mar 2026

Shorter than P25 for not_applicable

Geographic Reach
1 country

1 active site

Status
not yet recruiting

Health score is calculated from publicly available data and should be used for screening purposes only.

Trial Relationships

Click on a node to explore related trials.

Study Timeline

Key milestones and dates

First Submitted

Initial submission to the registry

January 30, 2026

Completed
7 days until next milestone

First Posted

Study publicly available on registry

February 6, 2026

Completed
1 month until next milestone

Study Start

First participant enrolled

March 15, 2026

Completed
1 month until next milestone

Primary Completion

Last participant's last visit for primary outcome

April 15, 2026

Completed
1 month until next milestone

Study Completion

Last participant's last visit for all outcomes

May 15, 2026

Completed
Last Updated

February 6, 2026

Status Verified

January 1, 2026

Enrollment Period

1 month

First QC Date

January 30, 2026

Last Update Submit

January 30, 2026

Conditions

Urodynamic Interpretation Skills

Keywords

Urodynamic Education, Learning Curve, Urology Residency, Large Language Models Training, LLM

Outcome Measures

Primary Outcomes (1)

  • Improvement in Urodynamic Interpretation Accuracy

    Change in urodynamic interpretation performance measured using a predefined 16-item objective scoring system assessing technical validity, numerical parameter interpretation, and diagnostic synthesis. Scores are compared across pre-test, mid-test, and post-test assessments to evaluate learning curve progression.

    From baseline (pre-test) to post-test (approximately 4 weeks)

Study Arms (1)

LLM-Based Urodynamic Education

EXPERIMENTAL

Participants receive a structured urodynamic education program supported by a large language model acting as an interactive tutor.

Other: LLM-Based Urodynamic Tutoring

Interventions

LLM-Based Urodynamic TutoringOTHER

Participants receive a structured urodynamic education program supported by a large language model acting as an interactive tutor.

Also known as: LLM-Based Urodynamic Education
LLM-Based Urodynamic Education

Eligibility Criteria

Age18 Years+
Sexall
Healthy VolunteersYes
Age GroupsAdult (18-64), Older Adult (65+)

You may qualify if:

  • Urology residents currently enrolled in an accredited urology training program
  • No prior formal certification in urodynamic training

You may not qualify if:

  • Prior completion of a formal urodynamic training course
  • Declining to provide informed consent

Contact the study team to confirm eligibility.

Sponsors & Collaborators

Study Sites (1)

University of Health Sciences, Erzurum City Hospital, Department of Urology

Erzurum, Turkey (Türkiye)

Location

Related Publications (1)

  • Frigerio M, Barba M, Cola A, Volontè S, Marino G, Regusci L, Sorice P, Ruggeri G, Castronovo F, Serati M, Torella M, Braga A. The Learning Curve of Urodynamics for the Evaluation of Lower Urinary Tract Symptoms. Medicina (Kaunas). 2022 Feb 23;58(3):341. doi: 10.3390/medicina58030341. PMID: 35334517; PMCID: PMC8955767.

    BACKGROUND

Study Officials

  • Hüseyin Koçakgöl, MD

    University of Health Sciences, Erzurum City Hospital

    PRINCIPAL INVESTIGATOR

Central Study Contacts

Hüseyin Koçakgöl, MD

CONTACT

+905062846185hsynkocakgl@gmail.com

Study Design

Study Type
interventional
Phase
not applicable
Allocation
NA
Masking
NONE
Purpose
OTHER
Intervention Model
SINGLE GROUP
Model Details: Participants undergo a single-arm, prospective educational intervention with repeated assessments (pre-test, mid-test, and post-test) to evaluate changes in urodynamic interpretation performance over time.
Sponsor Type
OTHER
Responsible Party
SPONSOR INVESTIGATOR
PI Title
MD, Urology

Study Record Dates

First Submitted

January 30, 2026

First Posted

February 6, 2026

Study Start

March 15, 2026

Primary Completion

April 15, 2026

Study Completion

May 15, 2026

Last Updated

February 6, 2026

Record last verified: 2026-01

Data Sharing

IPD Sharing
Will not share

Individual participant data will not be shared because the study involves a small sample size and focuses on educational performance outcomes. All analyses will be reported in aggregate form without identifiable individual-level data.

Locations

TU(1)