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Depressive, anxiety, and sleep disturbance symptoms in patients with obstructive sleep apnea: a network analysis
Xue Luo1,2, Shuangyan Li1,2, Qianyun Wu1,2
1Department of Psychiatry Sleep Medical Center, Nanfang Hospital Southern Medical University, No. 1838 North Guangzhou Avenue, Guangzhou, 510515, China.
Background:
Patients with obstructive sleep apnea (OSA) frequently experience sleep disturbance and psychological distress, such as depression and anxiety, which may have a negative impact on their health status and functional abilities. To gain a more comprehensive understanding of the symptoms of depression, anxiety, and sleep disturbance in patients with OSA, the current study utilized network analysis to examine the interconnections among these symptoms.
Methods:
Depressive and anxiety symptoms were evaluated using the Hospital Anxiety and Depression Scale (HADS), and sleep disturbance symptoms were evaluated using the Pittsburgh Sleep Quality Index (PSQI). A total of 621 patients with OSA completed the questionnaires. The indices 'Expected influence' and 'Bridge expected influence' were used as centrality measures in the symptom network. The Least Absolute Shrinkage and Selection Operator (LASSO) technique and the Extended Bayesian Information Criterion (EBIC) were utilized to estimate the network structure of depressive, anxiety, and sleep disturbance symptoms. A Network Comparison Test (NCT) was performed to evaluate the differences between the mild to moderate OSA and severe OSA networks.
Results:
Network analysis revealed that A6 ("Getting sudden feelings of panic") had the highest expected influence value and D6 ("Feeling being slowed down") had the highest bridge expected influence values in the networks. The NCT results revealed that the edge weights significantly differed between patients with mild to moderate OSA and those with severe OSA (M = 0.263, p = 0.008). There was no significant difference in global strength variation between the two networks (S = 0.185, p = 0.773).
Conclusions:
Our results suggest that the highest expected influence value and bridge symptoms (e.g., A6 and D6) can be prioritized as potential targets for intervention and treatment in patients with OSA.
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