To characterize the relationship between panic attack symptoms and atrial fibrillation episodes using a real-time assessment data capturing system that reduces recall biases of previous research.
Atrial fibrillation (AF) is a major health care problem) whose cardiac symptoms often overlap with panic attack (PA) symptoms. This pattern of comorbidity is important because it may delay accurate diagnosis, influence medical decision making, compromise physician-patient relationship, and reinforce illness behaviors. Clarifying the temporal relationship between panic and AF symptoms may create opportunities for more effective disease management programs. The purpose of this study is to characterize the temporal relationship between PA symptoms and AF episodes using a real-time assessment data capturing system that has methodological advantages over retrospective designs in previous research. Local cardiology practices will be screened for patients aged 21-75 years with paroxysmal AF for PA symptoms. Patients with AF indicating on the Patient Health Questionnaire (PHQ) a history of PA and experiencing at least one PA in the previous 4 weeks will be eligible. A formal diagnosis of panic disorder is not required. Thirty individuals will be enrolled for 4 weeks, during which they will wear an external cardiac event monitor for continuous rhythm monitoring. A mobile internet based application will allow participants to complete a panic episode report when they experience PA symptoms. They will record the time and duration of each episode, fear, and the PA symptoms. At end of day, participants will record their daily emotions, AF and PA symptoms, and health behaviors. Daily reminders for episode and daily reports with be sent via text message. Cardiac monitoring data, evening reports, and panic episode reports will be assessed by research staff daily. The primary aim is to examine the correspondence of PA and AF episodes. A time-lagged hierarchical model with repeated measures will examine whether panic episodes immediately precede or follow episodes of AF (i.e., within 4 hours). Power to detect an effect was estimated based on Monte Carlo studies run in MPlus. Based on findings that anxiety attacks are associated with a 4-time greater likelihood of episodes of AF, we estimated an effect size of ß=.25. For episodes as infrequent as 3 out of 14 days on average (150 total observations) statistical power exceeds .80. The hypothesis is that a percentage of individuals will show a temporal relationship between their PA symptoms and AF episodes and that this temporal relationship will differ among patients with disparate, but distinct, psychological/medical profiles. Findings may be informative for cardiologists treating AF patients who experience PA symptoms and may suggest effective disease management programs that help patients self-manage anxiety-related AF symptoms. The study will also provide pilot data on the utility of our assessment procedures for use in larger more comprehensive externally funded studies.
Study Type
OBSERVATIONAL
Enrollment
13
RHYTHMSTAR Mobile Cardiac Monitoring System
University at Buffalo
Buffalo, New York, United States
Ecological momentary assessments of atrial fibrillation symptoms
Self reporting of atrial fibrillation symptoms
Time frame: repeated measures throughout the 4 week protocol
Ecological momentary assessments of anxiety
Self reporting of anxiety symptoms
Time frame: repeated measures throughout the 4 week protocol
Mobile cardiac event recorder
EKG
Time frame: repeated measures throughout the 4 week protocol
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