关键词: 睡眠觉醒障碍, 焦虑, 抑郁, 共病表型, 精准干预, 聚类分析

Abstract:

Objective To explore the phenotypic characteristics of the “sleep-mood-somatic symptoms” comorbidity pattern in patients with sleep disorders complicated by anxiety and depression, and to evaluate the clinical effect of a precision intervention strategy developed according to phenotypic classification. Methods A total of 102 patients with sleep disorders complicated by anxiety and depression admitted between June 2024 and December 2025 were enrolled. The Pittsburgh sleep quality index (PSQI), self-rating anxiety scale (SAS), self-rating depression scale (SDS), and somatic symptom scale (SSS) were used for comprehensive assessment. Dimension-specific scores from each scale were collected, and K-means cluster analysis was applied to classify comorbidity phenotypes. Targeted precision intervention plans were formulated according to the core symptom characteristics of each phenotype. The intervention period was 8 weeks. Improvements in sleep quality, emotional status, and somatic symptoms were compared before and after intervention across the groups. Results Cluster analysis identified 3 comorbidity phenotypes among the 102 patients: phenotype 1 (sleep-dominant type), 42 cases, characterized by severe sleep disturbance, moderate anxiety and depression, and mild somatic symptoms; phenotype 2 (mood-dominant type), 36 cases, characterized by moderate sleep disturbance, severe anxiety and depression, and moderate somatic symptoms; and phenotype 3 (somatic-mood-sleep severe type), 26 cases, characterized by severe sleep disturbance, severe anxiety and depression, and severe somatic symptoms. Significant differences were observed among the phenotype groups in disease duration and the incidence of underlying diseases (P<0.05), whereas no significant differences were found in sex or age distribution (P>0.05). After precision intervention, PSQI, SAS, SDS, and SSS scores in all three groups were significantly lower than those before intervention (P<0.05). In terms of overall response rate, the rates were 92.86% in phenotype 1, 94.29% in phenotype 2, and 78.26% in phenotype 3; the differences in overall response rate among the three groups were statistically significant (P<0.05). Conclusion Patients with sleep disorders complicated by anxiety and depression exhibit distinct “sleep-mood-somatic symptoms” comorbidity phenotypes.

Key words: sleep wake disorders, anxiety, depression, comorbidity phenotypes, precision intervention, cluster analysis