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Voice Quality Analysis of Patients With Laryngotracheal Stenosis

NCT06161077 · Status: NOT_YET_RECRUITING · Type: OBSERVATIONAL · Enrollment: 100

Last updated 2025-08-06

No results posted yet for this study

Summary

The investigators previously demonstrated that voice changes are common in patients with Laryngotracheal Stenosis (LTS), and patients typically report an improvement in voice outcomes following endoscopic dilation. Recently, NIH based programs such as a Bridge to Artificial Intelligence (Bridge2AI) have highlighted the use of artificial intelligence to identify acoustic biomarkers of disease. Therefore, the investigators hypothesize that progression of LTS scar can be quantified using acoustic measurements and machine learning. The goal of this clinical trial is to remotely monitor patient voice quality in an effort to determine if regularly performed voice recordings can be used as a diagnostic tool in order to predict the need for dilation procedures. The investigators feel that successful use of remote voice recording technology with algorithmic analysis will improve patient quality of life.

Conditions

  • Idiopathic Subglottic Tracheal Stenosis

Interventions

DIAGNOSTIC_TEST

Voice Biomarker Screening Too

The investigators will develop a screening tool using voice that can predict disease severity in idiopathic subglottic stenosis

Sponsors & Collaborators

Principal Investigators

  • Alexander Hillel, MD · Johns Hopkins School of Medicine

Eligibility

Min Age
18 Years
Max Age
80 Years
Sex
ALL
Healthy Volunteers
No

Timeline & Regulatory

Start
2026-07-01
Primary Completion
2028-07-01
Completion
2028-12-01

Countries

  • United States

Study Locations

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Entities

Companies

Read the full study record

This page highlights key information. For complete eligibility criteria, study locations, investigator contacts, and the full protocol, visit the original record on ClinicalTrials.gov.

View NCT06161077 on ClinicalTrials.gov