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Epidemiology and prognostic implications of panic disorder and generalized anxiety disorder in patients with coronary artery disease: rationale and design for a longitudinal cohort study

Abstract

Background

Anxiety is associated with poorer prognosis in patients with coronary artery disease (CAD). Due to their severity and chronic course, anxiety disorders, particularly generalized anxiety disorder (GAD) and panic disorder (PD), are of considerable interest and clinical importance in this population. This study has two main objectives: (1) to estimate the prevalence and incidence of GAD and PD in patients with CAD over a 2-year period and (2) to prospectively assess the association between PD or GAD and adverse cardiac events, treatment adherence, CAD-related health behaviors, quality of life and psychological distress.

Design/Method

This is a longitudinal cohort study in which 3610 participants will be recruited following a CAD-related revascularization procedure. They will complete an interview and questionnaires at 5 time points over a 2-year period (baseline and follow-ups after 3, 6, 12 and 24 months). The presence of PD or GAD, adherence to recommended treatments, health behaviors, quality of life and psychological distress will be assessed at each time point. Data regarding mortality and adverse cardiac events will be collected with a combination of interviews and review of medical files.

Discussion

This study will provide essential information on the prevalence and incidence of anxiety disorders in patients with CAD and on the consequences of these comorbidities. Such data is necessary in order to develop clear clinical recommendations for the management of PD and GAD in patients with CAD. This will help improve the prognosis of patients suffering from both conditions.

Background

In Canada and in the United States, over 6% of adults aged 20 years or older live with coronary artery disease (CAD), the most common form of cardiovascular disease [1, 2]. Along with its elevated prevalence, CAD is also one of the costliest diseases in both countries, with annual direct and indirect costs reaching 219$ billions a year in the United States [2,3,4]. Although the incidence and mortality rates associated with CAD have decreased in the last decades, it remains one of the leading causes of mortality, hospitalization and disability-adjusted life years lost worldwide [1, 5, 6].

A variety of interventions may be used to manage the potential consequences of CAD and improve the prognosis of patients [7,8,9]. Given that up to 90% of the myocardial infarction risk is attributable to nine modifiable risk factors (e.g., cholesterol levels, hypertension, diabetes, smoking, obesity, physical inactivity, alcohol use, diet and psychosocial factors), comprehensive risk factor management programs and cardiac rehabilitation are essential to improve outcomes in patients with CAD [8, 10, 11]. The management of psychosocial risk factors represents a particular challenge: while decades of research have demonstrated their importance in patients with CAD, the nature and implications of the relationship between CAD and anxiety disorders is not as well understood as that of other CAD risk factors [12,13,14,15,16,17]. Although much of the research to date has focused on the role of depression, a growing number of studies suggest that anxiety may also lead to negative outcomes in this population [18,19,20,21,22].

Anxiety and coronary artery disease

Elevated anxiety has been independently associated with a 36–88% increase in the risk of adverse cardiac events in patients with CAD [22,23,24,25,26,27,28,29,30,31,32]. However, the relationship between anxiety, CAD and CAD-related mortality remains unclear [33]. This may be partly due to the fact that anxiety, particularly anxiety disorders, remains understudied in the context of CAD [33]. One important issue is that most of the studies on this topic assessed anxiety with self-reported questionnaires [33]. This approach alone cannot be used to diagnose anxiety disorders which, due to their severity and chronic course, are more likely to have a significant impact on CAD prognosis [21, 28].

Two anxiety disorders, generalized anxiety disorder (GAD) and panic disorder (PD), are of particular interest and importance in patients with CAD as their prevalence rates among this clinical population (24 and 53% respectively), are up to 15 times higher than those in the general population [21, 33,34,35,36,37,38,39]. In patients with CAD, the presence of these disorders is also associated with an increased risk of major cardiac events, greater disability, higher psychological distress and lowered quality of life [21, 39,40,41,42,43,44]. Both disorders are also characterized by an increased suicidal risk and multiple and often unproductive medical consultations [45,46,47,48,49,50] as well as incident CAD and cardiac events [22, 51, 52]. Without treatment, PD and GAD have a chronic course and worsen over time, which negatively influence their prognosis and treatment response [46, 53,54,55].

Diagnosing anxiety disorders such as GAD and PD in patients with CAD can be challenging as there is a significant overlap in the somatic symptoms of both conditions (e.g. chest pain, dizziness, dyspnea, palpitations and tiredness) [20, 21, 33, 35, 56]. This may explain why anxiety disorders have been found to be more prevalent in the few studies in which they were diagnosed using structured interviews (the gold standard for psychiatric diagnoses) conducted by trained mental health professionals [33]. Furthermore, a single assessment point, as was used in several reviewed studies, might not be reliable in order to adequately identify pathological anxiety in patients with CAD [20,21,22, 24, 25, 27, 31,32,33]. Indeed, some authors have expressed concerns that assessing anxiety disorders shortly after a cardiac or life-threatening event may lead to false positives [28, 35]. In addition, the onset of a chronic illness such as CAD and dealing with its consequences are risk factors for the development of GAD and PD [57] and could lead to an elevated incidence of these disorders in the following months and years. Thus, further prospective studies using validated structured interviews and a robust methodology to assess the prevalence and incidence of PD and GAD in patients with CAD are needed [33].

Possible mechanisms linking panic disorder and generalized anxiety disorder with CAD prognosis

Though still unclear, physiological and behavioral pathways have been proposed to explain how anxiety disorders and CAD influence each other and subsequently lead to poorer outcomes. Part of the association between CAD and anxiety disorders may be explained by physiological factors, such as increased inflammation [20, 21, 36, 39, 58]. Anxiety disorders are also associated with higher rates of hypertension, obesity, diabetes and dyslipidemia, which all increase the cardiovascular risk [21, 29, 59]. PD and GAD have also been linked to poorer health behaviors [20, 21, 36, 60,61,62,63,64]. For instance, the likelihood of alcohol use disorder, either dependence or abuse, is 79–83% higher in patients with GAD or PD than in patients without these disorders [65, 66]. These anxiety disorders are also associated with a 50–90% increased risk of daily smoking and nicotine dependence as well as low levels of physical activity [61, 63, 64, 67,68,69,70]. Furthermore, high levels of anxiety have been associated with non-attendance and non-completion of cardiac rehabilitation programs and non-adherence to cardiac medication [64, 70,71,72,73,74,75]. Consequently, another part of the association between anxiety disorders and CAD could be explained by the negative influence of these disorders on health behaviors and adherence to evidence-based risk-reducing recommendations and treatments for CAD [20, 21, 56, 64, 70, 75].

Summary

Despite the recommendations of the American Heart Association in 2014 [18], very few studies have prospectively investigated the independent role and differential impacts of anxiety disorders on cardiovascular outcomes in patients with established CAD [33, 76]. While some studies assessed the prevalence and prognostic implications of GAD in patients with CAD, to our knowledge, no prospective study has documented the potential consequences of PD on these same outcomes.

Anxiety disorders, and more specifically PD and GAD, are associated with a wide array of unhealthy behaviors, but the prevalence and persistence of such behaviors in patients with CAD remain unknown. Moreover, no study has investigated the role of PD and GAD on enrollment, participation and adherence to cardiac rehabilitation. Finally, only one study accounted for both medical and behavioral risk factors while assessing the effects of GAD on adverse cardiac outcomes in patients with CAD [31]. This low number of studies combined with concerns regarding diagnostic accuracy in most of them severely limit the interpretation of the data available on this issue, underscoring the importance of further research on the prognostic significance of PD and GAD in patients with CAD.

Objectives

In order to help bridge the knowledge gaps related to PD and GAD in patients with CAD, this study has two main objectives:

  1. 1.

    To establish the prevalence and incidence of PD and GAD in the 2 years following a CAD-related revascularization procedure.

  2. 2.

    To prospectively assess the association between the presence of PD or GAD and:

    1. a.

      Adverse cardiac events;

    2. b.

      Adherence to treatments (cardiac rehabilitation, pharmacotherapy);

    3. c.

      CAD-related health behaviors;

    4. d.

      Quality of life and psychological distress.

Methods

Design

This is a prospective cohort study in which participants will be evaluated at 5 time points: baseline, 3 months, 6 months, 1 year and 2 years. The study was registered with clinicaltrials.gov (NCT04433832).

Participants

All adults (≥ 18 years) who undergo a CAD revascularization procedure at the coronary/cardiac surgical care unit of the Quebec Heart and Lung Institute and are fluent in French will be eligible for study participation. These patients will be recruited either onsite or following their transfer to the Hôtel-Dieu de Lévis University-Affiliated Hospital. Patients will be excluded if they present a severe communication problem or suffer from a terminal illness, a diagnosed major cognitive deficit, or any other condition that could invalidate the interview (e.g. psychotic disorder), of if they are not legally competent.

Measures and outcomes definitions

Presence of PD and GAD (objective 1)

PD and GAD will be assessed at each time point using the Anxiety and Related Disorders Interview Schedule for DSM-5 (ADIS-5) [77]. This standardized interview protocol is one of the recommended measures for diagnosing anxiety disorders, including PD and GAD, in the research context [33, 78].

Adverse cardiac events (objective 2a)

Patients will be asked about all potential adverse events occurring during the study period with a structured medical interview developed by our team [79, 80]. All data will be confirmed by an independent review of medical records. With written consent from patients or next of kin (if deceased), records for admissions or consultations outside of the study hospital will be obtained from the hospital archives. Medical data will be extracted using a combination of a standardized medical data extraction form known for its excellent reliability (Cohen’s k = 0.72–0.91) and modules from the GRACE initial form [79,80,81].

Adverse events are defined as: either an acute myocardial infarction as defined by the Joint ESC/ACCF/AHA/WHF Task Force for the Universal Definition of Myocardial Infarction [82], a revascularization procedure (percutaneous coronary intervention or coronary bypass grafting), a cardiac arrest (including ventricular fibrillation) or death from a cardiovascular cause (primary cause).

The main outcome for objective 2a is the presence of any of the listed adverse events. The association between the presence of PD or GAD and each individual type of event will also be explored.

Adherence to treatments (objective 2b)

General measure: Adherence to treatments will be assessed with the Medical Outcomes Study Measures of Patient Adherence [83]. This brief structured interview, converted to a questionnaire for the purpose of this study, assesses the patients’ tendency to comply with medical recommendations and contains 2 sections (general and heart disease-specific) [83, 84]. This measure has good internal consistency (Cronbach’s α = 0.81) [83]. For the purpose of this study, the items were translated to French using Vallerand’s back-translation methodology [85].

Medication adherence: This parameter will be assessed using the Adherence Scale in Chronic Diseases which has good internal consistency (α = 0.74) [86,87,88]. This scale was translated to French using Vallerand’s back-translation methodology [85].

Cardiac rehabilitation participation: Patients will be asked if they participated in a formal cardiac rehabilitation program at each time point with two validated interview items [89]. Attendance will be assessed by reviewing records of the 12-week cardiac rehabilitation programs. With written consent from patients or next of kin, records of attendance to programs outside of the study hospital will be obtained from hospital archives. The overall level of adherence will be calculated with the percentage of the prescribed sessions attended during the program. Participation will be categorized as follows:

  • Non-attendance: patients who did not attend a cardiac rehabilitation program.

  • Completion: patients who attended at least 70% of the planned sessions [90].

  • Non-completion: patients who attended less than 70% of the planned sessions [90].

  • Discontinuation: patients who stopped attending cardiac rehabilitation at least 3 weeks before the end of the program.

Health behaviors (objective 2c)

Level of physical activity: This parameter will be assessed with the validated French version of the International Physical Activity Questionnaire—Short Form [91]. This data will be used to determine if patients are following the recommendations of the American Heart Association regarding exercise, which are: at least 30 min (minimum 5 days per week) of moderate intensity aerobic activity such as brisk walking [10].

Smoking status: This variable will be assessed using the validated self-report items developed by Statistics Canada to assess the current smoking status (non-smoking, occasional smoker, smoking every day) [92] in the 30 days preceding each time point.

Alcohol use: The patients’ compliance with recommendations regarding alcohol consumption (≤ 1 drink/day for women and ≤ 2 drinks/day for men) [7, 8, 10, 93, 94] will be assessed with the first 3 items of the validated French version of the Alcohol Use Disorders Identification Test [93, 94]. These items are well validated and are highly correlated with objective measures of alcohol consumption [95].

Fruit and vegetable intake: Patients usual consumption of fruit and vegetables will be assessed using the 6-item Fruits and Vegetables Questionnaire [96]. This brief measure is predictive of overall eating habits.

Quality of life and psychological distress (objective 2d)

Health-related quality of life: The validated French version of the 12-item Short-Form Health Survey Version 2 will be used to assess the health-related quality of life of patients [97, 98]. The physical summary score and mental summary score will be used in the current study.

Psychological distress: Anxiety and depressive symptoms will be measured with the validated French version of the Hospital Anxiety and Depression Scale [99, 100]. The internal consistency of the questionnaire and its 2 subscales (anxiety and depression) is well established (α = 0.68–0.93) [101]. The total score will be used as a measure of overall psychological distress in the current study. Heart-focused anxiety will be assessed with the French version of the Cardiac Anxiety Questionnaire [102, 103]. It has good internal consistency (α ≥ 0.83) and satisfactory convergent validity [102].

Other variables and measures

Sociodemographic data: Sociodemographic information, including employment status, educational level and family income (i.e. socio-economic status), will be obtained using a brief questionnaire.

Medical comorbidities and cardiovascular risk factors for CAD: This data will be obtained through a medical interview and review of medical records. Obesity will be assessed using body mass index (kg/m2), which will be computed from the reported height and weight of patients obtained during the medical interview. The Charlson Comorbidity Index will be used to summarize the patients’ medical comorbidities [104, 105].

Other psychosocial risk factors for CAD

  • Social support will be assessed with the validated French version of the Modified Medical Outcomes Study Social Support Survey. This brief measure assesses the patients’ perceived social support and has good internal consistency (α = 0.85–0.88).

  • Depression, agoraphobia, health anxiety and somatic symptom disorder will be assessed with the ADIS-5 which presents good to excellent inter-rater agreement for these psychiatric diagnoses [106].

  • Post-traumatic stress disorder (PTSD) will be assessed using the French version of the PTSD Checklist for DSM-5, a 20-item self-report measure that assesses symptoms of post-traumatic stress disorder [107, 108].

  • Sleep habits and sleeping problems will be assessed by using the French version of the Pittsburgh Sleep Quality Index [109, 110]. The brief self-reported questionnaire has good internal consistency (α = 0.70–0.83) and test–retest reliability [109].

Procedures

Recruitment and assessment of patients

Research assistants at the recruitment site will identify potentially eligible patients by consulting medical files. They will subsequently present them the consent form, explain the research project, answer questions and, upon acceptance, administer the medical interview, the fruits and vegetables intake measure and the physical activity measure. Face-to-face or phone assessments with a trained interviewer (doctoral student in psychology) to administer the selected modules of the ADIS-5 will be scheduled onsite with the consenting patients. Patients will fill out the questionnaires right after the face-to-face interview in an electronic format with assistance from a research assistant if needed. Patients who are unable to come in for a face-to-face interview (either due to their medical condition or to distance from the recruitment site) will be offered to complete the interview by phone and to fill out the questionnaires online through the REDCap secure web-based application [111], by phone or by regular mail. For regular mail and website completion, patients will receive a follow-up call to offer assistance a week after the questionnaires are sent. All measures will be administered at all time points. Patients will be contacted  two weeks before each time point in order to schedule the interview (onsite or by phone) and questionnaire completion (electronic format, paper or by phone). Patients who are unreachable after three weeks will be considered lost to follow-up. At each time point, research personnel, blinded to the patients’ results to the ADIS-5, will review the medical records of all patients. To improve retention, patients will have a chance to win an electronic tablet for the completion of each time point (interview and questionnaires) as a compensation for their time.

Quality control

Assessors (psychology doctoral students who completed ≥ 180 h of academic courses and practicums focusing on clinical assessment) will receive initial training (14 h) and subsequent weekly clinical supervision. The ADIS-5 interviews will be audio-recorded to facilitate supervision and to realize inter-rater agreements on the diagnoses. Inter-rater agreements on all ADIS-5 interviews and data will be established using a random sample of 25% of all files reviewed and all ADIS-5 interviews realized at each time point. All questionnaires and interviews will be reviewed after completion and patients will be contacted if missing data are present. Finally, most of the questionnaires will be filled out electronically, reducing the risk of incorrect or missing data.

Statistical analyses

All study data will be collected and managed using the REDCap data capture tools [111]. For objective 1, the prevalence and incidence of GAD and PD will be presented with their 95% confidence intervals for each time point. As a sensitivity analysis, the stability of baseline diagnoses of PD and GAD will be assessed at the 3-month follow-up. Diagnoses will be considered stable if less than 10% of patients experience remission (no longer meeting the diagnostic criteria for PD or GAD) between these time points. If this criterion is not fulfilled, all analyses for objective 2 will be repeated using the diagnoses established at the 3-month follow-up to identify patients with and without PD or GAD. Inter-rater agreements on ADIS-5 diagnoses will be assessed by computing Cohen’s Kappa and its 95% confidence interval.

In the context of objective 2, generalized linear mixed models (continuous outcomes) and generalized estimating equation models (dichotomous outcomes) with group X time interactions will be used to compare the evolution of both groups (with and without GAD or PD) in terms of adverse cardiac events, adherence to treatments (cardiac rehabilitation, pharmacotherapy), CAD-related health behaviors, quality of life and psychological distress All models will be adjusted for age, sex, cardiovascular risk factors, medications and medical comorbidity. Additional control variables will include, when relevant: diagnosis of depression, PTSD symptoms, previous cardiac events and interventions, health behaviors and social support. In the presence of significant effects of PD or GAD, analyses will be repeated in order to explore differences among men and women (group X sex X time).

As an exploratory measure, analyses will be repeated separately for GAD and PD. All analyses will be repeated using 3 groups (patients with PD or GAD at baseline, patients who developed PD or GAD afterwards, patients without PD or GAD at all time points) in order to explore the impact of developing GAD or PD over time.

Justification of sample size

The minimal sample sized required for each objective was calculated separately. The final sample size was established according to the objective requiring the highest number of participants (i.e. objective 2a, n = 2527 participants). That estimation was based on a previously reported rate of adverse cardiac events of 14.3% [22]. Considering an anticipated attrition rate of 30% after 2 years, a total of 3610 patients will have to be initially recruited. Based on the lower range of findings from studies of GAD in patients with CAD, the relative risk of adverse events in patients was conservatively estimated at 1.50 [33]. This data was used in the absence of similar studies in patients with PD.

Discussion

PD and GAD appear to be highly prevalent in patients with CAD and their negative impact on cardiovascular, physical and psychological outcomes in this population are increasingly recognized. However, the literature on this issue is still scarce, and the available studies present considerable methodological flaws. Furthermore, very few studies accounted for the effects of traditional risk factors, treatment adherence and health behaviors while examining the impacts of PD or GAD in patients with CAD. Consequently, the prevalence of anxiety disorders and their prognostic role in patients with CAD remain unclear, and the current available literature cannot support clear clinical recommendations for the management of PD and GAD in patients with CAD [112]. Prospective, comprehensive and robust studies documenting the prevalence and consequences of these anxiety disorders in patients with CAD are necessary to guide care for patients and orient clinical practice. This data will be very valuable to determine the usefulness of systematic screening for PD and GAD and provide guidance on which aspects of care should be specifically targeted in order to improve the prognosis of this subgroup of patients with CAD.

Study status

The recruitment began in February 2020. However, the study was on hold from March to July 2020 due to the COVID-19 pandemic confinement measures. Based on the patient volume at the recruitment site, it is estimated that the recruitment target for the present study will be reached in 28 months (30 patients/week). This estimate may be subject to change as the evolution of the COVID-19 pandemic and the associated public health measures may affect the recruitment and total number of eligible patients.

Availability of data and materials

Not applicable.

Abbreviations

CAD:

Coronary artery disease

GAD:

Generalized anxiety disorder

PD:

Panic disorder

ADIS-5:

Anxiety and Related Disorders Interview Schedule for DSM-5

PTSD:

Post-traumatic stress disorder

References

  1. 1.

    Agence de la santé publique du Canada. Les maladies du coeur au Canada: fait saillants du système canadien de surveillance des maladies chroniques. https://www.canada.ca/content/dam/phac-aspc/documents/services/publications/diseases-conditions/heart-disease-fact-sheet/heart-disease-factsheet-fra.pdf (2017).

  2. 2.

    Centers for Disease Control and Prevention. Heart Disease Facts. https://www.cdc.gov/heartdisease/facts.htm (2019).

  3. 3.

    Conference Board du Canada. La stratégie canadienne de santé cardiovasculaire: facteurs de risque et répercussions sur les coûts futurs. https://sencanada.ca/content/sen/committee/412/SOCI/Briefs/2015-05-07ReportCdnCardiovascularSociety-AddInfoConferenceBoardofCanada_f.pdf (2010).

  4. 4.

    American Heart Association. Cardiovascular disease: a costly burden for America, projections through 2035. https://healthmetrics.heart.org/wp-content/uploads/2017/10/Cardiovascular-Disease-A-Costly-Burden.pdf (2017).

  5. 5.

    Nowbar AN, Gitto M, Howard JP, et al. Mortality from ischemic heart disease: analysis of data from the World Health Organization and coronary artery disease risk factors from NCD risk factor collaboration. Circ Cardiovasc Qual Outcomes. 2019;12:e005375.

    PubMed  PubMed Central  Article  Google Scholar 

  6. 6.

    World Health Organization. The top 10 causes of death. https://www.who.int/news-room/fact-sheets/detail/the-top-10-causes-of-death (2018).

  7. 7.

    Fihn SD, Gardin JM, Abrams J, et al. 2012 ACCF/AHA/ACP/AATS/PCNA/SCAI/STS Guideline for the diagnosis and management of patients with stable ischemic heart disease: a report of the American College of Cardiology Foundation/American Heart Association Task Force on Practice Guidelines, and the American College of Physicians, American Association for Thoracic Surgery, Preventive Cardiovascular Nurses Association, Society for Cardiovascular Angiography and Interventions, and Society of Thoracic Surgeons. J Am Coll Cardiol. 2012;60(24):e44–164.

    PubMed  Article  Google Scholar 

  8. 8.

    Montalescot G, Sechtem U, Achenbach S, et al. 2013 ESC guidelines on the management of stable coronary artery disease: the Task Force on the management of stable coronary artery disease of the European Society of Cardiology. Eur Heart J. 2013;34(38):2949–3003.

    PubMed  Article  PubMed Central  Google Scholar 

  9. 9.

    Fihn SD, Blankenship JC, Alexander KP, et al. 2014 ACC/AHA/AATS/PCNA/SCAI/STS focused update of the guideline for the diagnosis and management of patients with stable ischemic heart disease: a report of the American College of Cardiology/American Heart Association Task Force on Practice Guidelines, and the American Association for Thoracic Surgery, Preventive Cardiovascular Nurses Association, Society for Cardiovascular Angiography and Interventions, and Society of Thoracic Surgeons. J Am Coll Cardiol. 2014;64(18):1929–49.

    PubMed  Article  PubMed Central  Google Scholar 

  10. 10.

    Smith SC Jr, Benjamin EJ, Bonow RO, et al. AHA/ACCF secondary prevention and risk reduction therapy for patients with coronary and other atherosclerotic vascular disease: 2011 update: a guideline from the American Heart Association and American College of Cardiology Foundation endorsed by the World Heart Federation and the Preventive Cardiovascular Nurses Association. J Am Coll Cardiol. 2011;58(23):2432–46.

    PubMed  Article  PubMed Central  Google Scholar 

  11. 11.

    Yusuf S, Hawken S, Ounpuu S, et al. Effect of potentially modifiable risk factors associated with myocardial infarction in 52 countries (the INTERHEART study): case-control study. Lancet. 2004;364(9438):937–52.

    PubMed  Article  PubMed Central  Google Scholar 

  12. 12.

    Pogosova N, Saner H, Pedersen SS, et al. Psychosocial aspects in cardiac rehabilitation: from theory to practice. A position paper from the Cardiac Rehabilitation Section of the European Association of Cardiovascular Prevention and Rehabilitation of the European Society of Cardiology. Eur J Prev Cardiol. 2015;22(10):1290–306.

    PubMed  Article  PubMed Central  Google Scholar 

  13. 13.

    Gallagher J, Parenti G, Doyle F. Psychological aspects of cardiac care and rehabilitation: time to wake up to sleep? Curr Cardiol Rep. 2015;17:111.

    PubMed  Article  PubMed Central  Google Scholar 

  14. 14.

    Neylon A, Canniffe C, Anand S, et al. A global perspective on psychosocial risk factors for cardiovascular disease. Prog Cardiovasc Dis. 2013;55:574–281.

    PubMed  Article  PubMed Central  Google Scholar 

  15. 15.

    Albus C, Jordan J, Hermann-Lingen C. Screening for psychosocial risk factors in patients with coronary heart disease—recommandations for clinical practice. Eur J Cardiovasc Prev Rehabil. 2004;11:75–9.

    PubMed  Article  PubMed Central  Google Scholar 

  16. 16.

    Thompson DR, Ski CF, Saner H. Psychosocial assessment and intervention—are we doing enough? Heart Lung. 2018;47:278–9.

    PubMed  Article  PubMed Central  Google Scholar 

  17. 17.

    Suls J, Bunde J. Anger, anxiety and depression as risk factors for cardiovascular disease: the problems and implications of overlapping affective dispositions. Psychol Bull. 2005;131(2):260–300.

    PubMed  Article  PubMed Central  Google Scholar 

  18. 18.

    Lichtman JH, Froelicher ES, Blumenthal JA, et al. Depression as a risk factor for poor prognosis among patients with acute coronary syndrome: systematic review and recommandations. A scientific statement from the American Heart Association. Circulation. 2014;129:1350–69.

    PubMed  Article  PubMed Central  Google Scholar 

  19. 19.

    Carney RM, Freedland KE. Depression and coronary heart disease. Nat Rev Cardiol. 2017;14:145–55.

    PubMed  Article  PubMed Central  Google Scholar 

  20. 20.

    Cohen BE, Edmondson D, Kronish IM. State of the art review: depression, stress, anxiety and cardiovascular disease. Am J Hypertens. 2015;28(11):1295–302.

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  21. 21.

    Celano CM, Daunis DJ, Hermioni NL, et al. Anxiety disorders and cardiovascular disease. Curr Psychiatry Rep. 2016;18(11):101.

    PubMed  PubMed Central  Article  Google Scholar 

  22. 22.

    Frasure-Smith N, Lesperance F. Depression and anxiety as predictors of 2-year cardiac events in patients with stable coronary artery disease. Arch Gen Psychiatry. 2008;65(1):62–71.

    CAS  PubMed  Article  Google Scholar 

  23. 23.

    Moser DK, McKinley S, Riegel B, et al. Relationship of persistent symptoms of anxiety to morbidity and mortality outcomes in patients with coronary heart disease. Psychosom Med. 2011;73(9):803–9.

    PubMed  Article  Google Scholar 

  24. 24.

    Tully PJ, Baker RA, Knight JL. Anxiety and depression as risk factors for mortality after coronary artery bypass surgery. J Psychosom Res. 2008;64(3):285–90.

    PubMed  Article  Google Scholar 

  25. 25.

    Strik JJ, Denollet J, Lousberg R, et al. Comparing symptoms of depression and anxiety as predictors of cardiac events and increased health care consumption after myocardial infarction. J Am Coll Cardiol. 2003;42(10):1801–7.

    PubMed  Article  Google Scholar 

  26. 26.

    Shibeshi WA, Young-Xu Y, Blatt CM. Anxiety worsens prognosis in patients with coronary artery disease. J Am Coll Cardiol. 2007;49(20):2021–7.

    PubMed  Article  Google Scholar 

  27. 27.

    Watkins LL, Koch GG, Sherwood A, et al. Association of anxiety and depression with all-cause mortality in individuals with coronary heart disease. J Am Heart Assoc. 2013;2(2):e000068.

    PubMed  PubMed Central  Article  Google Scholar 

  28. 28.

    Celano CM, Millstein RA, Bedoya CA, et al. Association between anxiety and mortality in patients with coronary artery disease: a meta-analysis. Am Heart J. 2015;170:1105–15.

    PubMed  PubMed Central  Article  Google Scholar 

  29. 29.

    Sowden GL, Huffman JC. The impact of mental illness on cardiac outcomes: a review for the cardiologist. Int J Cardiol. 2009;132:30–7.

    PubMed  Article  Google Scholar 

  30. 30.

    Roest AM, Martens EJ, Denollet J, et al. Prognostic association of anxiety post myocardial infarction with mortality and new cardiac events: a meta-analysis. Psychosom Med. 2010;72(6):563–9.

    PubMed  Article  Google Scholar 

  31. 31.

    Martens EJ, De Jonge P, Na B, et al. Scared to death? Generalized anxiety disorder and cardiovascular events in patients with stable coronary heart disease. Arch Gen Psychiatry. 2010;67(7):750–8.

    PubMed  Article  Google Scholar 

  32. 32.

    Roest AM, Zuidersma M, de Jonge P. Myocardial infarction and generalised anxiety disorder: 10-year follow-up. Br J Psychiatry. 2012;200(4):324–9.

    PubMed  Article  PubMed Central  Google Scholar 

  33. 33.

    Tully PJ, Cosh SM, Baumeister H. The anxious heart in whose mind? A systematic review and meta-regression of factors associated with anxiety disorder diagnosis, treatment and morbidity risk in coronary heart disease. J Psychosom Res. 2014;77(6):439–48.

    PubMed  Article  PubMed Central  Google Scholar 

  34. 34.

    Heart and Stroke Foundation. Anxiety. http://www.heartandstroke.ca/heart/recovery-and-support/emotions-and-feelings/anxiety (n.d.).

  35. 35.

    Tully PJ, Harrison NJ, Cheung P, Cosh S. Anxiety and cardiovascular disease risk: a review. Curr Cardiol Rep. 2016;18:120.

    PubMed  Article  PubMed Central  Google Scholar 

  36. 36.

    Abed MA, Kloub MI, Moser DK. Anxiety and adverse health outcomes among cardiac patients : a biobehavioral model. J Cardiovasc Nurs. 2014;29(4):354–63.

    PubMed  Article  PubMed Central  Google Scholar 

  37. 37.

    Bankier B, Januzzi JL, Littman AB. The high prevalence of multiple psychiatric disorders in stable outpatients with coronary heart disease. Psychosom Med. 2004;66:645–50.

    PubMed  Article  PubMed Central  Google Scholar 

  38. 38.

    Fleet RP, Lavoie KL, Beitman BD. Is panic disorder associated with coronary artery disease? A critical review of the literature. J Psychosom Res. 2000;48(4–5):347–56.

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  39. 39.

    Machado S, Sancassiani F, Paes F, et al. Panic disorder and cardiovascular diseases: an overview. Int Rev Psychiatry. 2017;29:436–44.

    PubMed  Article  PubMed Central  Google Scholar 

  40. 40.

    Jeejeebhoy FM, Dorian P, Newman DM. Panic disorder and the heart: a cardiology perspective. J Psychosom Res. 2000;48(4–5):393–403.

    CAS  PubMed  Article  Google Scholar 

  41. 41.

    Fleet RP, Dupuis G, Marchand A, et al. Panic disorder in coronary artery disease patients with noncardiac chest pain. J Psychosom Res. 1998;44(1):81–90.

    CAS  PubMed  Article  Google Scholar 

  42. 42.

    Srivastava S, Shekhar S, Bhatia MS, et al. Quality of life in patients with coronary artery disease and panic disorder: a comparative study. Oman Med J. 2017;32(1):20–6.

    PubMed  PubMed Central  Article  Google Scholar 

  43. 43.

    Alonso J, Petukhova M, Vilagut G, et al. Days out of role due to common physical and mental conditions: results from the WHO World Mental Health surveys. Mol Psychiatry. 2011;16(12):1234–46.

    CAS  PubMed  Article  Google Scholar 

  44. 44.

    Abrignani MG, Renda N, Abrignani V, et al. Panic disorder, anxiety and cardiovascular diseases. Clin Neuropsychiatry. 2014;11(5):130–44.

    Google Scholar 

  45. 45.

    Hoffman DL, Dukes EM, Wittchen H-U. Human and economic burden of generalized anxiety disorder. Depress Anxiety. 2008;25:72–90.

    PubMed  Article  Google Scholar 

  46. 46.

    National Institute for Health and Clinical Excellence. Generalised anxiety disorder in adults: management in primary, secondary and community care. London: The British Psychological Society, The Royal College of Psychiatrists; 2011.

    Google Scholar 

  47. 47.

    Newman MG, Llera SJ, Erickson TM, et al. Worry and generalized anxiety disorder: a review and theoretical synthesis of evidence on nature, etiology, mechanisms, and treatment. Annu Rev Clin Psychol. 2013;9:275–97.

    PubMed  PubMed Central  Article  Google Scholar 

  48. 48.

    Davidoff J, Christensen S, Khalili DN, et al. Quality of life in panic disorder: looking beyond symptom remission. Qual Life Res. 2012;21(6):945–59.

    PubMed  Article  Google Scholar 

  49. 49.

    Wittchen H-U. Generalized anxiety disorder: prevalence, burden and cost to society. Depress Anxiety. 2002;16:162–71.

    PubMed  Article  Google Scholar 

  50. 50.

    Roy-Byrne P, Stein MB, Russo J, et al. Panic disorder in the primary care setting: comorbidity, disability, service utilization, and treatment. J Clin Psychiatry. 1999;60(7):492–9.

    CAS  PubMed  Article  Google Scholar 

  51. 51.

    Gomez-Caminero A, Blumentals WA, Russo LJ, et al. Does panic disorder increase the risk of coronary heart disease? A cohort study of a national managed care database. Psychosom Med. 2005;67(5):688–91.

    PubMed  Article  Google Scholar 

  52. 52.

    Tully PJ, Beltrame J, Horowitz J, et al. Panic disorder and incident coronary heart disease: a systematic review and meta-regression in 1 131 612 persons and 58 111 cardiac events. Psychol Med. 2015;45:2909–20.

    CAS  PubMed  Article  Google Scholar 

  53. 53.

    American Psychiatric Association. DSM-5: Manuel diagnostique et statistique des troubles mentaux. 5e ed. Issy-les-Moulineaux: Elsevier Masson; 2015. p. 244–56.

    Google Scholar 

  54. 54.

    Fleet RP, Lavoie KL, Martel J-P, et al. Two-year follow-up status of emergency department patients with chest pain: was it panic disorder? CJEM. 2003;5(4):247–54.

    PubMed  Article  Google Scholar 

  55. 55.

    Kessler RC, Chiu WT, Jin R, et al. The epidemiology of panic attacks, panic disorder, and agoraphobia in the National Comorbidity Survey Replication. Arch Gen Psychiatry. 2006;63(4):415–24.

    PubMed  PubMed Central  Article  Google Scholar 

  56. 56.

    Moser DK. “The rust of life”: impact of anxiety on cardiac patients. Am J Crit Care. 2007;16(4):361–9.

    PubMed  PubMed Central  Article  Google Scholar 

  57. 57.

    Kariuki-Nyuthe C, Stein DJ. Anxiety and related disorders and physical illness. In: Sartorius N, Holt RIG, Maj M, editors. Comorbidity of mental and physical disorders. Berlin: Karger; 2015. p. 81–7.

    Google Scholar 

  58. 58.

    Huffman JC, Celano CM, Januzzi JL. The relationship between depression, anxiety, and cardiovascular outcomes in patients with acute coronary syndromes. Neuropsychiatr Dis Treat. 2010;6:123–36.

    PubMed  PubMed Central  Article  Google Scholar 

  59. 59.

    Kinley DJ, Lowry H, Katz C, et al. Depression and anxiety disorders and the link to physician diagnosed cardiac disease and metabolic risk factors. Gen Hosp Psychiatry. 2015;37:288–93.

    PubMed  Article  Google Scholar 

  60. 60.

    Bass C, Wade C, Hand D, et al. Patients with angina with normal and near normal coronary arteries: clinical and psychosocial state 12 months after angiography. Br Med J (Clin Res Ed). 1983;287(6404):1505–8.

    CAS  Article  Google Scholar 

  61. 61.

    Goncalves DC, Pachana NA, Byrne GJ. Prevalence and correlates of generalized anxiety disorder among older adults in the Australian National Survey of Mental Health and Well-Being. J Affect Disord. 2011;132(1–2):223–30.

    PubMed  Article  Google Scholar 

  62. 62.

    Olafiranye O, Jean-Louis G, Zizi F, et al. Anxiety and cardiovascular risk: review of epidemiological and clinical evidence. Mind Brain. 2011;2(1):32–7.

    CAS  PubMed  PubMed Central  Google Scholar 

  63. 63.

    da Silva CT, Schuch F, Costa M, et al. Somatic, but not cognitive, symptoms of anxiety predict lower levels of physical activity in panic disorder patients. J Affect Disord. 2014;164:63–8.

    Article  Google Scholar 

  64. 64.

    Martens EJ, de Jonge P, Na B, et al. Scared to death? Generalized anxiety disorder and cardiovascular events in patients with stable coronary heart disease: The Heart and Soul Study. Arch Gen Psychiatry. 2010;67(7):750–8.

    PubMed  Article  Google Scholar 

  65. 65.

    Kushner MG, Abrams K, Borchardt C. The relationship between anxiety disorders and alcohol use disorders: a review of major perspectives and findings. Clin Psychol Rev. 2000;20(2):149–71.

    CAS  PubMed  Article  Google Scholar 

  66. 66.

    Regier DA, Farmer ME, Rae DS, et al. Comorbidity of mental disorders with alcohol and other drug abuse. Results from the Epidemiologic Catchment Area (ECA) Study. JAMA. 1990;264(19):2511–8.

    CAS  PubMed  Article  Google Scholar 

  67. 67.

    Moylan S, Jacka FN, Pasco JA, et al. Cigarette smoking, nicotine dependence and anxiety disorders: a systematic review of population-based, epidemiological studies. BMC Med. 2012;10(123):1–14.

    Google Scholar 

  68. 68.

    Swendsen J, Conway KP, Degenhardt L, et al. Mental disorders as risk factors for substance use, abuse and dependence: results from the 10-year follow-up of the National Comorbidity Survey. Addiction. 2010;105(6):1117–28.

    PubMed  PubMed Central  Article  Google Scholar 

  69. 69.

    Goodwin RD. Association between physical activity and mental disorders among adults in the United States. Prev Med. 2003;36(6):698–703.

    PubMed  Article  Google Scholar 

  70. 70.

    Tully PJ, Cosh SM, Baune BT. A review of the affects of worry and generalized anxiety disorder upon cardiovascular health and coronary heart disease. Psychol Health Med. 2013;18(6):627–44.

    PubMed  Article  Google Scholar 

  71. 71.

    McGrady A, McGinnis R, Badenhop D, et al. Effects of depression and anxiety on adherence to cardiac rehabilitation. J Cardiopulm Rehabil Prev. 2009;29:358–64.

    PubMed  Article  Google Scholar 

  72. 72.

    Lane D, Carroll D, Ring C, et al. Predictors of attendance at cardiac rehabilitation after myocardial infarction. J Psychosom Res. 2001;51:497–501.

    CAS  PubMed  Article  Google Scholar 

  73. 73.

    Korhonen MJ, Pentti J, Hartikainen J, et al. Somatic symptoms of anxiety and nonadherence to statin therapy. Int J Cardiol. 2016;214:493–9.

    PubMed  Article  Google Scholar 

  74. 74.

    Kuhl EA, Fauerbach JA, Bush DE, et al. Relation of anxiety and adherence to risk-reducing recommendations following myocardial infarction. Am J Cardiol. 2009;103(12):1629–34.

    PubMed  Article  Google Scholar 

  75. 75.

    Sardinha A, Araújo CGS, Soares-Filho GLF, et al. Anxiety, panic disorder and coronary heart disease: issues concerning physical exercise and cognitive behavioral therapy. Exp Rev Cardiovasc Ther. 2011;9(2):165–75.

    CAS  Article  Google Scholar 

  76. 76.

    Alvarenga ME, Byrne D. Anxiety and cardiovascular disease: epidemiology and proposed mechanisms. In: Alvarenga ME, Byrne D, editors. Handbook of psychocardiology. Singapore: Springer; 2016. p. 247–63.

    Google Scholar 

  77. 77.

    Brown T, Barlow B. Anxiety and related disorders interview schedule for DSM-5® (ADIS-5)-adult and lifetime version: clinician manual (treatments that work). 1st ed. Oxford: Oxford University Press; 2015.

    Google Scholar 

  78. 78.

    Shear MK, Jack D, Maser D. Standardized assessment of panic disorder. Arch Gen Psychiatry. 1994;51:346–54.

    CAS  PubMed  Article  Google Scholar 

  79. 79.

    Foldes-Busque G, Marchand A, Chauny J-M, et al. Unexplained chest pain in the emergency department: could it be panic? Am J Emerg Med. 2011;29:743–51.

    PubMed  Article  Google Scholar 

  80. 80.

    Foldes-Busque G, Denis I, Poitras J, et al. The revised-panic screening score to improve identification of panic-like anxiety in emergency department patients with low-risk non-cardiac chest pain. Health Psychol. 2018;37:828–38 ((in press)).

    PubMed  Article  PubMed Central  Google Scholar 

  81. 81.

    Center for Outcomes Research. GRACE Initial Form-Version 3.5. https://www.outcomes-umassmed.org/grace/publicfiles/Main_GRACE_CRF.pdf (2002).

  82. 82.

    Thygesen K, Alpert JS, Jaffe AS, et al. Fourth universal definition of myocardial infarction. J Am Coll Cardiol. 2018;72(18):2231–64.

    PubMed  Article  PubMed Central  Google Scholar 

  83. 83.

    Hays RD. The Medical Outcomes Study (MOS) measures of patient adherence. https://www.rand.org/health-care/surveys_tools/mos/patient-adherence.html (1994).

  84. 84.

    Tarlov AR, Ware JE, Greenfield S, et al. The Medical Outcomes Study: an application of methods for monitoring the results of medical care. JAMA. 1989;262(7):925–30.

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  85. 85.

    Vallerand RJ. Toward a methodology for the transcultural validation of psychological questionnaires: implications for research in the French language. Can Psychol. 1989;30(4):662–80.

    Article  Google Scholar 

  86. 86.

    Buszko K, Obonska K, Michalski P, et al. The Adherence Scale in Chronic Diseases (ASCD). The power of knowledge: the key to successful patient-health care provider cooperation. Med Res J. 2016;1(1):37–42.

    Article  Google Scholar 

  87. 87.

    Kosobucka A, Michalski P, Pietrzykowski L, et al. Adherence to treatment assessed with the Adherence in Chronic Diseases Scale in patients after myocardial infarction. Patient Prefer Adherence. 2018;12:333–40.

    PubMed  PubMed Central  Article  Google Scholar 

  88. 88.

    Kubica A, Kosobucka A, Michalski P, et al. Self-reported questionnaires for assessment adherence to treatment in patients with cardiovascular diseases. Med Res J. 2017;2(4):115–22.

    Article  Google Scholar 

  89. 89.

    Kayaniyil S, Leung YW, Suskin N, et al. Concordance of self- and program-reported rates of cardiac rehabilitation referral, enrollment and participation. Can J Cardiol. 2009;25(4):e96–9.

    PubMed  PubMed Central  Article  Google Scholar 

  90. 90.

    Swardfager W, Herrmann N, Marzolini S, et al. Major depressive disorder predicts completion, adherence and outcomes in cardiac rehabilitation: a prospective cohort study of 195 patients with coronary artery disease. J Clin Psychiatry. 2011;72(9):1181–8.

    PubMed  Article  Google Scholar 

  91. 91.

    Craig CL, Marshall AL, Sjostrom M, et al. International physical activity questionnaire: 12-country reliability and validity. Med Sci Sports Exerc. 2003;35(8):1381–95.

    PubMed  PubMed Central  Article  Google Scholar 

  92. 92.

    Wong SL, Shields M, Leatherdale S, et al. Assessment of validity of self-reported smoking status. Health Rep. 2012;23(1):1–7.

    Google Scholar 

  93. 93.

    Saunders JB, Aasland OG, Babor TF, et al. Development of the alcohol use disorders identification test (AUDIT): WHO collaborative project on early detection of persons with harmful alcohol consumption—II. Addiction. 1993;88(6):791–804.

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  94. 94.

    Gache P, Michaud P, Landry U, et al. The alcohol use disorders identification test (AUDIT) as a screening tool for excessive drinking in primary care: reliability and validity of a French version. Alcohol Clin Exp Res. 2005;29(11):2001–7.

    PubMed  Article  PubMed Central  Google Scholar 

  95. 95.

    Higgins-Biddle JC, Babor TF. A review of the Alcohol Use Disorders Identification Test (AUDIT), AUDIT-C, and USAUDIT for screening in the United States: past issues and future directions. Am J Drug Alcohol Abuse. 2018;44:578–86.

    PubMed  PubMed Central  Article  Google Scholar 

  96. 96.

    Godin G, Bélanger-Gravel A, Paradis A, et al. A simple method to assess fruit and vegetable intake among obese and non-obese individuals. Can J Public Health. 2008;99(6):494–8.

    PubMed  PubMed Central  Article  Google Scholar 

  97. 97.

    Gandek B, Ware J, Aaronson N, et al. Cross-validation of item selection and scoring for the SF-12 Health Survey in nine countries: results from the IQOLA Project. International Quality of Life Assessment. J Clin Epidemiol. 1998;51:1171–8.

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  98. 98.

    Montazeri A, Vahdaninia M, Mousavi SJ, et al. The 12-item medical outcomes study short form health survey version 20 (SF-12v2): a population-based validation study from Tehran, Iran. Health Qual Life Outcomes. 2011;9:12.

    PubMed  PubMed Central  Article  Google Scholar 

  99. 99.

    Roberge P, Dore I, Menear M, et al. A psychometric evaluation of the French Canadian version of the Hospital Anxiety and Depression Scale in a large primary care population. J Affect Disord. 2013;147(1–3):171–9.

    PubMed  Article  PubMed Central  Google Scholar 

  100. 100.

    Zigmond AS, Snaith RP. The hospital anxiety and depression scale. Acta Psychiatr Scand. 1983;67(6):361–70.

    CAS  Article  PubMed  Google Scholar 

  101. 101.

    Bjelland I, Dahl AA, Haug TT, et al. The validity of the Hospital Anxiety and Depression Scale. An updated literature review. J Psychosom Res. 2002;52:69–77.

    PubMed  Article  PubMed Central  Google Scholar 

  102. 102.

    Bisson-Bernatchez E, Chiasson C, Turcotte S, et al. Validation of the French version of the Cardiac Anxiety Questionnaire (CAQ-FR). Can J Behav Sci. 2019;51(2):100.

    Article  Google Scholar 

  103. 103.

    Eifert G, Thompson R, Zvolensky M, et al. The cardiac anxiety questionnaire: development and preliminary validity. Behav Res Ther. 2000;38:1039–53.

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  104. 104.

    Quan H, Li B, Couris CM, et al. Updating and validating the Charlson comorbidity index and score for risk adjustment in hospital discharge abstracts using data from 6 countries. Am J Epidemiol. 2011;173(6):676–82.

    PubMed  Article  PubMed Central  Google Scholar 

  105. 105.

    Charlson ME, Pompei P, Ales KL, et al. A new method of classifying prognostic comorbidity in longitudinal studies: development and validation. J Chronic Dis. 1987;40(5):373–83.

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  106. 106.

    Brown TA, Di Nardo PA, Lehman CL, et al. Reliability of DSM-IV anxiety and mood disorders: implications for classification of emotional disorders. J Abnorm Psychol. 2001;110:49–58.

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  107. 107.

    Weathers FW, Litz BT, Keane T, et al. The PTSD Checklist for DSM-5 (PCL-5). https://www.ptsd.va.gov/professional/assessment/adult-sr/ptsd-checklist.asp (2013).

  108. 108.

    Ashbaugh A, Houle-Johnson S, Herbert C, et al. Psychometric validation of the English and French versions of the posttraumatic stress disorder checklist for DSM-5 (PCL-5). PLoS ONE. 2016;11(10):e0161645.

    PubMed  PubMed Central  Article  CAS  Google Scholar 

  109. 109.

    Ait-Aoudia M, Levy PP, Bui E, et al. Validation of the French version of the Pittsburgh Sleep Quality Index Addendum for posttraumatic stressdisorder. Eur J Psychotraumatol. 2013;4(1):192–8.

    Article  Google Scholar 

  110. 110.

    Buysse DJ, Reynolds CF, Monk TH, et al. The Pittsburgh Sleep Quality Index: a new instrument for psychiatric practice and research. Psychiatry Res. 1989;28(2):193–213.

    CAS  Article  Google Scholar 

  111. 111.

    Harris PA, Taylor R, Thielke R, et al. Research electronic data capture (REDCap): a metadata-driven methodology and workflow process for providing translational research informatics support. J Biomed Inform. 2009;42(2):377–81.

    PubMed  PubMed Central  Article  Google Scholar 

  112. 112.

    Blumenthal JA, Smith PJ. Anxiety and risk of cardiac events. Nat Rev Cardiol. 2010;7:606–8.

    PubMed  PubMed Central  Article  Google Scholar 

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Acknowledgements

We are grateful to the participants for their essential contribution to this study. We also wish to acknowledge the contribution of the medical staff of the Quebec Heart and Lung Institute for their ongoing collaboration.

Funding

This study is supported by a grant from the Canadian Institutes of Health Research (407654). GFB receives support from the Fonds de Recherche du Québec – Santé (GFB: 266918). The funding sources did not have any role in the design of the study and in the writing of this manuscript. They also have no role in the collection, analysis and interpretation of data.

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GFB, MAT, ID, CED, PT, ST and PP were involved in the design of the study. GFB, MAT and ID wrote the manuscript draft. CED, ST, PT and PP read and critically reviewed the manuscript. All authors read and approved the submitted manuscript.

Corresponding author

Correspondence to Guillaume Foldes-Busque.

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Ethical approval and consent to participate

The ethics committee of the Research center of the Quebec Heart and Lung Institute approved the research protocol (reference number MP-10-2020-3263 21818). Written informed consent is obtained from all participants prior to study participation.

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Not applicable.

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The authors declare that they have no competing interests.

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Foldes-Busque, G., Dionne, C.E., Turcotte, S. et al. Epidemiology and prognostic implications of panic disorder and generalized anxiety disorder in patients with coronary artery disease: rationale and design for a longitudinal cohort study. BMC Cardiovasc Disord 21, 26 (2021). https://doi.org/10.1186/s12872-021-01848-3

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Keywords

  • Anxiety disorders
  • Panic disorder
  • Generalized anxiety disorder
  • Coronary artery disease
  • Prognosis
  • Revascularization
  • Adverse cardiac events
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