Clinical heterogeneity and cluster analysis of multiple system atrophy / 中华老年医学杂志

ABSTRACT

Objective:To examine the clinical subtypes of patients with multisystem atrophy(MSA)that may indicate the prognosis of patients.Additionally, we aim to compare the ability to perform daily activities among patients of each subtype using cluster analysis.Methods:The retrospective analysis included demographic data, clinical symptoms and signs, scale scores, and ancillary examinations of 94 patients diagnosed with multisystem atrophy at Xuanwu Hospital of Capital Medical University.The study aimed to analyze the clinical characteristics of each subtype obtained through clustering.Additionally, a comparison was made between patients with traditional motor subtypes and those with new subtypes in terms of activities of daily living.The study consisted of 94 MSA patients, with an average age of 61 years and a female representation of 51.1%.Using the data collected on the continuum, a full linkage hierarchical cluster analysis was performed to classify MSA patients into four clinical subtypes: gait disorder(17 cases, 18.1%), malignant tonic hyperkinetic with premature haircut(25 cases, 26.6%), intermediate(43 cases, 45.7%), and autonomic benign type(9 cases, 9.6%).Each subtype exhibited various clinical motor and non-motor symptoms, including UPDRS-Ⅲ( χ2=27.90, P<0.001), gait disturbance( χ2=33.23, P<0.001), MoCA( χ2=10.98, P=0.012), HAMA( χ2=12.14, P=0.007), HAMD( χ2=13.62, P=0.003), smell score( χ2=10.16, P=0.017), postural hypotension( χ2=14.59, P=0.028), and a statistically significant difference in the ability to perform daily living score( χ2=25.35, P<0.001).No statistically significant differences in non-motor symptoms and activities of daily living abilities were observed between the cerebellar and Parkinsonian types of traditional motor typing( P>0.05). Conclusions:The hierarchical clustering analysis conducted in this study reveals that the clinical phenotype of MSA provides a more accurate reflection of patients' clinical characteristics and their impact on quality of life compared to the traditional motor phenotype.Additionally, it may help predict variations in the underlying pathological impairment and the rate of disease progression.These findings offer a foundation for precise diagnostic interventions in patients with MSA.