Voice Quality Analysis of Patients With Laryngotracheal Stenosis

ConditionIdiopathic Subglottic Tracheal Stenosis

Trial statusNot yet recruiting

Trial phaseNot listed

Trial typeObservational

Biological sexAll

Age18-80

SponsorJohns Hopkins University

About this trial

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.

Eligibility criteria

This trial does not accept healthy volunteers

Qualifiers

Current diagnosis of laryngotracheal stenosis

Patient age 18 - 80 years old

Eastern Cooperative Oncology Group (ECOG) performance status of 0 - 1

The patient must be able to comprehend and have signed the informed consent.

Disqualifiers

Inability to use the app associated with the study.

Comorbid laryngeal or glottic disease

Concurrent neurological disease which may impact voice use (such as tremor, parkinsonism, laryngeal dystonia)

Trial population

Individuals with idiopathic subglottic stenosis

Trial design

Design model

Cohort

Time perspective

Prospective

Treatments tested in this trial

Voice Biomarker Screening Too
Diagnostic test
The investigators will develop a screening tool using voice that can predict disease severity in idiopathic subglottic stenosis

Treatment groups

No treatment groups listed

Trial outcomes

Primary outcomes

Voice Quality in patients with idiopathic subglottic stenosis

To remotely assess voice quality of patients with idiopathic subglottic stenosis with VoiceLab automated voice analysis software both before and at regular intervals following dilation procedures

Time frame