Assessment of swallowing performance in patients with neurodegenerative disease: A hierarchical cluster analysis.

BACKGROUND

Swallowing is a complex process that alters with age and neurological diseases; swallowing disorders can be a consequence of both of them. As an advanced multivariate statistical method, hierarchical cluster analysis (HCA) was utilized to make the dendrograms, which was used to find the relationship between the variables. The purpose of this study is to ascertain the type of clustering exhibited by the variables using HCA and to evaluate the approach to major neurodegenerative diseases (MND) with swallowing disorders based on the results obtained.

METHODS

Data were collected from a total of 173 patients from various neurological diagnoses, such as dementia, Parkinson's disease, stroke and polyneuropathy, aging between 42 and 104 (mean of age 72.85) by using the Montreal Cognitive Assessment, the Edinburgh Feeding Evaluation Scale (EdFED), the Eating Assessment Tool (EAT-10), and the Modified Mann Swallowing Ability test. From the collected data, dendrograms were formed by using HCA with Ward linkage method.

RESULTS

Based on cluster analysis results, clusters demonstrate statistical significance. They center around EdFED, EAT-10, and age in each MND. In healthy individuals, variables are not clustered as in the patient group. This study holds importance as it can give clinicians a different perspective on determining and managing the elderly population's swallowing problems.

CONCLUSIONS

The HCA method explicitly proposes which variables should be examined concurrently in the clinic for MND. This research is one of the pioneering studies conducted by using the HCA method.