A Multi-factor Model for the Assessment of Depression Associated with Obstructive Sleep Apnea: A Fuzzy Logic Approach

Many patients with obstructive sleep apnea (OSA) also exhibit depressive symptoms such as fatigue, anhedonia, weight changes, and depressed or sad mood. Some of these patients are misdiagnosed with clinical depression and treated with antidepressants, which may actually impede OSA treatment. Thus, the assessment of depression is of crucial importance in sleep clinics, and is often used both before and after treatment. As there are no objective ways to measure depression, the most common form of assessment is using subjective, usually self-reporting, questionnaires. These questionnaires were created for assessing and diagnosing clinical depression and not for multiple assessments of depressive symptoms as a secondary medical condition. They are also subject to reporting inaccuracies. In this paper, we introduce STEM-D, a fuzzy logic model for assessing depression in OSA patients that incorporates the multifactorial nature of depression. We studied nine existing questionnaires and created four categories of questions. We modeled the categories using fuzzy variables, with the output variable being the severity of a patient's depression. STEM-D will be used multiple times throughout treatment to monitor a patient's change in depressive symptoms as a result of OSA treatment. This model will be applied in a clinical setting as part of a larger project, CPAP-T*MONITOR.