BACKGROUND: 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.
| Identifer | oai:union.ndltd.org:bu.edu/oai:open.bu.edu:2144/45547 |
| Date | 31 January 2023 |
| Creators | Dasari, Laya |
| Contributors | McKnight, C. James, Pedrelli, Paola |
| Source Sets | Boston University |
| Language | en_US |
| Detected Language | English |
| Type | Thesis/Dissertation |
| Rights | Attribution 4.0 International, http://creativecommons.org/licenses/by/4.0/ |
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