Voice Quality Analysis of Patients With Laryngotracheal Stenosis

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Conditions studied: Idiopathic Subglottic Tracheal Stenosis

In brief

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.

Key facts

Study ID
NCT06161077
Run by
Johns Hopkins University
People needed
100
Starts
2027-01-01
Expected to finish
2030-12-01
Last updated by the study team
2026-07-13

Who can join

Age: 18 and older, up to 80. Sex: any. Healthy volunteers: not accepted.

You may qualify if…

You may not qualify if…

Where it is running

Full record on ClinicalTrials.gov

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