McKnight, C. JamesPedrelli, PaolaDasari, Laya2023-02-032023-02-032022https://hdl.handle.net/2144/45547BACKGROUND: Major depression is a pervasive condition that affects every aspect of a patient’s life, and many patients are unable to find symptom alleviation with the current available medications. Ketamine has recently shown promise as a rapid-acting antidepressant, yet its mechanisms are not yet well-understood. OBJECTIVE: We sought to understand the change in depression symptom interrelationships, with particular interest in sleep, in the context of ketamine treatment in depression by completing a network analysis. METHODS: 97 patients with treatment-resistant depression were given ketamine over six treatments, and symptoms were examined via the Quick Inventory of Depressive Symptomology (QIDS-SR-16). Two networks were constructed: one prior to the first treatment, and one prior to the sixth treatment. Each symptom of the inventory formed a node, and partial correlations were used to construct the edges of the network. Centrality indices and network structure was then evaluated and compared. RESULTS: Centrality indices measured were unstable, limiting assertions to node strength, but global network structure was revealed to be changed between the networks. CONCLUSION: The data suggests that ketamine may affect the interrelationships between depressive symptoms, by impacting some symptoms more than others.en-USAttribution 4.0 Internationalhttp://creativecommons.org/licenses/by/4.0/PsychobiologyAntidepressantDepressionKetamineNetwork analysisSleepTreatment-resistantThesis/Dissertation2023-01-310000-0002-0250-2106