Unable to enroll the required number of subjects to achieve statistically significant results. There were no adverse events to report.

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.

Inclusion Criteria:

• Patients (male and female) between 21 - 75 years of age
• Patients of both sexes, of varying races and ethnicities, with a range of educational levels and ages
• ICD-10 diagnosis code of PAF in the electronic medical record or ECG demonstrating PAF in the chart.
• History of PA symptoms as identified on screening with the PHQ-PD
• Read and speak English
• Access to a smartphone and internet/data coverage.
• Ability to read and type within a smartphone-based application.
• Capacity to understand and provide informed consent, and comply with protocol requirements that includes completion of a limited number of questionnaires.

Exclusion Criteria:

• Uncontrolled hypertension (defined as documented BP readings consistently above 140/90)
• Patients younger than 21 years old or older than 75 years old
• Reversible causes of AF, which include but are not limited to untreated thyroid disease, recent major surgical procedure or trauma, etc
• History of persistent or chronic AF
• History of clinically significant valvular heart disease (bio prosthetic or mechanical valve, severe aortic stenosis, moderate to severe mitral stenosis, rheumatic heart disease, or severe mitral regurgitation)
• History of congestive heart failure (CHF) and an ejection fraction (EF) of less than 40%
• History of new onset coronary artery disease (CAD) in the last 90 days
• History of myocardial infarction (MI) in the last 90 days
• History of percutaneous coronary intervention in the last 90 days
• History of coronary artery bypass grafting in the last 90 days.
• History of untreated obstructive sleep apnea (OSA)
• History of severe pulmonary hypertension
• Patients on rhythm control medications and expected to have changing dose during the study (not excluded if patient anticipated to be on stable dose throughout duration of the study: 30 days).
• History of cerebrovascular injury (stroke, transient ischemic attack, traumatic brain injury) in the last 90 days
• Morbid obesity, Body Mass Index (BMI) >40 kg/m2
• Dementia or any form of cognitive impairment that precludes the patient from providing consent
• Pregnant women
• Patients with a major psychiatric disorder which, in the opinion of the investigator, may impede his/her participation in the study. These disorders include, but are not limited to, major depression with high likelihood of suicidal behavior (i.e., intent or plan), alcohol or substance abuse/dependence within the past year, lifetime history of schizophrenia or schizoaffective disorder, psychoses, mania.
• Patients who do not have a smartphone device
• Uncompensated hearing or visual defects
• Patients unable to communicate verbally in English
• Patients who are unable to fully comprehend the consent forms
• Medically unstable patients or patients who have a life expectancy less than the anticipated duration of the study

Academic Cardiology Practice