Johns Hopkins University
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.
Idiopathic Subglottic Tracheal Stenosis
Voice Biomarker Screening Too
Study Type : | OBSERVATIONAL |
Estimated Enrollment : | 100 participants |
Official Title : | Voice Quality Analysis of Patients With Laryngotracheal Stenosis |
Actual Study Start Date : | 2025-07-01 |
Estimated Primary Completion Date : | 2027-07-01 |
Estimated Study Completion Date : | 2027-12-01 |
Information not available for Arms and Intervention/treatment
Ages Eligible for Study: | 18 Years to 80 Years |
Sexes Eligible for Study: | ALL |
Want to participate in this study, select a site at your convenience, send yourself email to get contact details and prescreening steps.
Not yet recruiting
Johns Hopkins Outpatient Center
Baltimore, Maryland, United States, 21287