Objective:

To examine associations between objective sleep structure and current suicidal ideation (SI) in depressed patients and to explore the utility of sleep-clinical clustering for SI stratification.

Approach:

• Participants: 287 patients with depressive disorder underwent clinical assessment and overnight polysomnography (PSG).
• Assessment of SI: Current SI was assessed using item 3 of the HAMD-17.
• Statistical Analysis: Binary logistic regression evaluated factors associated with SI; K-Means clustering identified sleep-clinical subgroups.

Key Findings:

• 50.52% of patients exhibited current SI.
• Only the HAMD total score was independently associated with current SI (OR = 1.683, p < 0.001).
• Cluster analysis revealed three subgroups with distinct SI rates: Cluster 1 (37.04%), Cluster 2 (70.37%), Cluster 3 (60.80%).
• Membership in Clusters 2 + 3 was associated with current SI (OR = 3.152, p < 0.001).

Interpretation:

Depression severity was the primary factor associated with current SI, while PSG-derived sleep-clinical clusters may help characterize presentations of SI.

Limitations:

• The study's exploratory nature requires validation in larger longitudinal samples.
• The primary cluster association was attenuated when adjusting for HAMD total score.

Conclusion:

PSG-derived sleep-clinical clusters may provide insights into the heterogeneity of current SI in depressed patients.