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Consensus-Based Attributes for Identifying Patients With Spasmodic Dysphonia and Other Voice Disorders
Christy L Ludlow1, Rickie Domangue2, Dinesh Sharma2
1Department of Communication Sciences and Disorders, James Madison University, Harrisonburg, Virgina.
Importance:
A roadblock for research on adductor spasmodic dysphonia (ADSD), abductor SD (ABSD), voice tremor (VT), and muscular tension dysphonia (MTD) is the lack of criteria for selecting patients with these disorders.
Objective:
To determine the agreement among experts not using standard guidelines to classify patients with ABSD, ADSD, VT, and MTD, and develop expert consensus attributes for classifying patients for research.
Design, Setting And Participants:
From 2011 to 2016, a multicenter observational study examined agreement among blinded experts when classifying patients with ADSD, ABSD, VT or MTD (first study). Subsequently, a 4-stage Delphi method study used reiterative stages of review by an expert panel and 46 community experts to develop consensus on attributes to be used for classifying patients with the 4 disorders (second study). The study used a convenience sample of 178 patients clinically diagnosed with ADSD, ABSD, VT MTD, vocal fold paresis/paralysis, psychogenic voice disorders, or hypophonia secondary to Parkinson disease. Participants were aged 18 years or older, without laryngeal structural disease or surgery for ADSD and underwent speech and nasolaryngoscopy video recordings following a standard protocol.
Exposures:
Speech and nasolaryngoscopy video recordings following a standard protocol.
Main Outcomes And Measures:
Specialists at 4 sites classified 178 patients into 11 categories. Four international experts independently classified 75 patients using the same categories without guidelines after viewing speech and nasolaryngoscopy video recordings. Each member from the 4 sites also classified 50 patients from other sites after viewing video clips of voice/laryngeal tasks. Interrater κ less than 0.40 indicated poor classification agreement among rater pairs and across recruiting sites. Consequently, a Delphi panel of 13 experts identified and ranked speech and laryngeal movement attributes for classifying ADSD, ABSD, VT, and MTD, which were reviewed by 46 community specialists. Based on the median attribute rankings, a final attribute list was created for each disorder.
Results:
When classifying patients without guidelines, raters differed in their classification distributions (likelihood ratio, χ2 = 107.66), had poor interrater agreement, and poor agreement with site categories. For 11 categories, the highest agreement was 34%, with no κ values greater than 0.26. In external rater pairs, the highest κ was 0.23 and the highest agreement was 38.5%. Using 6 categories, the highest percent agreement was 73.3% and the highest κ was 0.40. The Delphi method yielded 18 attributes for classifying disorders from speech and nasolaryngoscopic examinations.
Conclusions And Relevance:
Specialists without guidelines had poor agreement when classifying patients for research, leading to a Delphi-based development of the Spasmodic Dysphonia Attributes Inventory for classifying patients with ADSD, ABSD, VT, and MTD for research.
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