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Psychosomatics 49:199-207, May-June 2008
doi: 10.1176/appi.psy.49.3.199
© 2008 Academy of Psychosomatic Medicine
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A Prospective Examination of Antidepressant Use and Its Correlates in Patients With Acute Coronary Syndrome

Sherry L. Grace, Ph.D., Yvonne W. Leung, M.A., and Donna E. Stewart, M.D., FRCPC

Received September 20, 2006; revised December 19, 2006; accepted January 4, 2007. From York University and University Health Network Women’s Health Program, York University; University Health Network, Women’s Health Program, and University of Toronto. Send correspondence and reprint requests to Sherry L. Grace, Ph.D., Kinesiology and Health Science, 368 Bethune College, 4700 Keele St., Toronto, Ontario M3J1P3 Canada. e-mail: sgrace{at}yorku.ca
© 2008 The Academy of Psychosomatic Medicine


  ABSTRACT

 
TOP
 ABSTRACT
INTRODUCTION
 METHOD
 RESULTS
 DISCUSSION
 REFERENCES
 
BACKGROUND: Depression has been implicated in the occurrence of recurrent coronary events and cardiac or all-cause mortality in acute coronary syndrome (ACS) patients. OBJECTIVE: The authors describe the frequency and type of antidepressant use and its correlates 18 months after ACS hospital discharge. METHOD: A sample of 661 ACS inpatients, recruited from three hospitals, completed a sociodemographic survey and the Hospital Anxiety and Depression Scale (HADS), and clinical data were extracted from charts. A mailed survey 9 months and 18 months post-discharge assessed self-reported antidepressant use, and the HADS was re-administered. RESULTS: Approximately 9% of participants reported antidepressant use both 9 and 18 months post-hospitalization, with 77% concordance in usage over time. Participants most frequently reported using selective serotonin reuptake inhibitors and least often tricyclics. Logistic regression revealed that antidepressant users were more likely to be anxious and have more comorbidity, and were less likely to work full-time, whereas number of medications, age, and marital status were not related. CONCLUSION: Patients with comorbid physical and mental conditions who are unemployed may be more likely to receive an antidepressant because of greater depression symptoms or greater exposure to healthcare providers, which increases the potential for symptom recognition and treatment.

Key Words: Heart Disease • Antidepressants

  INTRODUCTION

 
TOP
 ABSTRACT
 INTRODUCTION
METHOD
 RESULTS
 DISCUSSION
 REFERENCES
 
Depression is common among acute coronary syndrome (ACS) patients.1,2 The prevalence of major depression ranges around 15%–20%,3 which is approximately three times higher than found in age-matched, community-based prevalence studies,4,5 and the prevalence of elevated depression symptoms has been reported to be as high as 50%.6 In addition to this emotional burden, depression has been implicated in the occurrence of recurrent coronary events and cardiac or all-cause mortality in ACS patients.7,8 Not only is this the case for depressive disorder, but for depressive symptomatology itself, which confers a relative risk between 1.5 and 2.5 for future cardiac morbidity and mortality,3 and a dose–response relationship has been supported.6 In fact, it has been suggested that the magnitude of this depression effect is similar to that of traditional cardiac risk factors such as hypertension and dyslipidemia.9

Unfortunately, however, such depressive symptoms are grossly underscreened and undertreated.2 Evidence-based therapies for depression established in non-comorbid populations include psychotherapy and antidepressant medications.10 Indeed, selective serotonin reuptake inhibitors (SSRIs) represent safe and effective means of reducing depression in cardiac patients, as well.11–13 Although evidence of cardiac risk reduction brought about by such pharmacotherapy (or psychotherapy) is lacking to-date, reducing this emotional burden is also a worthy goal. The objective of this study was to examine the self-reported prevalence of antidepressant use, the class of medications reported, the consistency of this use over time, and the sociodemographic and clinical correlates of such use.


  METHOD

 
TOP
 ABSTRACT
 INTRODUCTION
 METHOD
RESULTS
 DISCUSSION
 REFERENCES
 
Procedure and Design
This study uses a prospective observational design and is a secondary analysis of data collected within the context of a larger study on access to cardiac rehabilitation (CR). Ethics approval was obtained from participating sites. Participants were followed for 18 months from admission for their index acute coronary syndrome (ACS) hospitalization. Consecutive ACS patients were recruited on relevant cardiovascular units by a research assistant when they were medically stable. ACS diagnosis was confirmed on the basis of indication in patient chart of detailed history, focused physical examination, diagnostic ECG changes (i.e., Q waves, and/or ST–T segment changes), and/or troponin levels above the 99th percentile of normal. Patients who had undergone concurrent percutaneous coronary interventions (PCIs), or acute coronary bypass (ACB) were also eligible. Exclusion criteria included being medically unstable, too confused to participate, having previous participation in CR, or being ineligible for CR on the basis of Canadian Association of Cardiac Rehabilitation14 guidelines because of musculoskeletal, visual, non-dysphoric psychiatric, or other comorbidities, or being unable to read or speak English. Those who met study criteria and agreed to participate signed a consent form and were provided with a self-report questionnaire. Consent was also obtained to extract cardiac clinical data from their medical charts. At 9 and 18 months later, participants were mailed a survey assessing several variables, including self-reported antidepressant use.

Participants
A total of 1,362 consecutive ACS patients at Trillium Health Centre or University Health Network Toronto General or Toronto Western Hospitals in Ontario, Canada were approached to solicit informed consent between September 2003 and August 2004. Of these patients, 661 consented to participate, and 483 were ineligible for the study (response rate: 661/879; 75%). Reasons for ineligibility were the following: previous attendance at CR (N=123; 25.5%), lack of English language proficiency (N=119; 24.6%), too ill to participate (N=98, 20.3%), condition not indicated for referral to CR (N=70; 14.5%), patient too confused or experiencing cognitive impairment (N=42; 8.7%), comorbid musculoskeletal condition precluding ambulation (N=19; 3.9%), or patient already participating in two studies (N=5; 1.0%). Other reasons (N=7; 1.4%) included isolation for infection control and moving to another province.

Characteristics of participants and non-participants are shown in Table 1. There were no significant differences in participation on the basis of marital status. Of the patients approached, participants were significantly younger than those who declined or were ineligible to participate (F[2]=33.59; p <0.001; post-hoc ps <0.001). Significantly more men agreed to participate than women ({chi}2[2]=31.44; p <0.001). Participants’ ages ranged from 33 to 91. The majority of participants self-reported their ethnocultural background as white (N=509; 81.4%), and the most frequent non-white ethnocultural backgrounds were South Asian (N=49; 7.8%), Black (e.g., Afro-Canadian, African, or West Indian; N=16; 2.6%), and Filipino (N=12; 1.9%).


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TABLE 1. Self-Reported Characteristics of Participating, Refusing, and Ineligible Patients at Baseline Recruitment



Measures
In-Hospital Assessments
Sociodemographic data assessed in the baseline self-report survey included age, sex, ethnocultural background, marital status, work status, level of education, and gross annual family income. Postal codes were used to classify participants as urban or rural, with a zero in the second digit representing rural areas, as defined by the Canadian postal service.

Body Mass Index (BMI) was based on self-reported height and weight (kg/m2). Participants were asked whether they were current, past, or non-smokers. They were also asked to check comorbidities from a list of 13 conditions, including musculoskeletal, gastrointestinal, and respiratory conditions. The number of conditions was counted, and a total score was generated. Data were extracted from clinical charts; these included confirmation of reason for index hospitalization, cardiac medications, and disease severity (NYHA Class15).

The Hospital Anxiety and Depression Scale (HADS16), a reliable and well-validated scale,17 was used to assess anxiety and depressive symptoms. The HADS is a 14-item self-report questionnaire: anxiety and depressive symptomatology were each measured through 7 items, rated on a 4-point Likert-type scale. Total scores range from 0 to 21, where a score below 8 indicates the "normal" range of subthreshold symptoms; a score of 9–10 represents moderate affective symptomatology; and a score of ≥11 represents severe affective symptomatology.16

The Duke Activity Status Index (DASI18) is a brief, 12-item, self-administered survey to determine functional capacity. Participants were asked about their ability to perform common activities of daily living, such as personal care, ambulation, household tasks, sexual functioning, and recreational activities, which are each associated with specific metabolic equivalents (METs). This valid and common tool correlates highly with peak oxygen uptake.19

Mailed Assessments: 9 and 18 Months
These self-report surveys requested participants to gather their medication bottles and list all their current medications, cardiac and otherwise. The total number of medications was recorded, and antidepressant and anxiolytic medications were coded by class. The HADS was also re-administered in the final survey (i.e., in-hospital and 18-month post-discharge assessments).

Statistical Analysis
We used SPSS 14.0 for the following analyses. After data cleaning and screening, differences between participating, ineligible, and declining patients were tested by Pearson’s r, chi-square, and analysis of variance, as appropriate. A descriptive examination was then performed, and open-ended medication responses were coded. Sex differences in baseline anxiety and depression symptoms were evaluated by t-tests. Cohen’s kappa was used to compute concordance between antidepressant use at 9 and 18 months post-hospitalization. Differences in 18-month anxiety and depression symptoms by 9-month antidepressant use were compared by t-tests, then data were split by antidepressant use, and paired t-tests were computed to examine change in affective symptoms from hospitalization to 18 months post-discharge. In-hospital sociodemographic and clinical correlates of 9-month antidepressant use were explored by chi-square analysis and t-tests, as appropriate. Finally, we performed a hierarchical logistic-regression analysis predicting antidepressant use 9 months post-hospitalization. Significant correlates from the bivariate screening were entered into the model.


  RESULTS

 
TOP
 ABSTRACT
 INTRODUCTION
 METHOD
 RESULTS
DISCUSSION
 REFERENCES
 
Respondent Characteristics
Of the 661 consenting participants, 61 were ineligible and 506 were retained at the 9-month assessment (retention rate: 506/600; 84.3%). Reasons for ineligibility were the following: unable to reach/incorrect contact information (N=34; 5.1%), too ill to participate (N=10; 1.5%), deceased (N=8; 1.2%), and other reasons (N=9; 1.4%).

At 18 months post-discharge, 465 participants were retained in the study (81.4% retention rate). Characteristics of participants and those who declined or were ineligible at 18 months post-hospitalization are summarized in Table 2. Reasons for ineligibility were the following: cannot reach/incorrect contact information (N=55; 61.1%), too ill to take part (N=13; 14.4%), deceased (N=10; 11.1%), previous participation in CR (N=3; 3.3%), and other reasons (N=9; 10.0%); these included the onset of conditions that precluded eligibility for CR. Retained participants tended to be older, white, married/common-law, non-smokers, less likely to be diabetic or have undergone a PCI procedure, and have a higher family income.


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TABLE 2. Characteristics of Participating, Refusing, and Ineligible Patients at 18-Month Follow-Up Assessment (N=661)



Anxiety and Depression Symptoms in the Hospital and 18 Months Later
Table 3 shows mean anxiety and depression symptoms by sex at both time-points. In the hospital, 46 participants (7.1%) reported depression symptoms in the moderate range, with 50 (7.7%) severe, for a total of 14.7% reporting elevated depression symptoms. At 18 months, 21 participants (4.7%) reported depression symptoms in the moderate range, with 26 (5.8%) severe, for a total of 10.5% reporting elevated depression symptoms. Fourteen participants (3.2%) reported elevated depression symptoms at both time-points. In the hospital, 80 participants (12.3%) reported anxiety symptoms in the moderate range, with 137 (21.0%) severe, for a total of 33.2% reporting elevated anxiety symptoms. At 18 months, 38 participants (8.5%) reported anxiety symptoms in the moderate range, with 56 (12.6%) severe, for a total of 21.1% reporting elevated anxiety symptoms.


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TABLE 3. Anxiety and Depression Symptoms (HADS Scores) in the Hospital and 18 Months Post-Discharge, by Sex



In the hospital, depression and anxiety scores were highly correlated (r=0.60; p<0.001), and 74 participants (11.3%) had both elevated depression and anxiety symptoms ({kappa}=0.34); 18 months post-discharge, depression and anxiety scores were again highly correlated (r=0.67; p<0.001), and 30 participants (6.7%) had both elevated depression and anxiety symptoms ({kappa}=0.33). As shown, although there were no significant sex differences in depression symptoms, there was a trend toward greater symptoms among women in the hospital (t = –1.77; p=0.078). Female participants reported significantly more anxiety in the hospital and 18 months later than male participants.

Antidepressant Use
Nine months post-discharge, 48 participants (9.5%) self-reported taking an antidepressant medication. Classes of antidepressants reported were: SSRIs (N=27; 56.3%), serotonin and norepinephrine reuptake inhibitors (SNRIs; N=8; 16.7%), atypical antidepressants (N=7; 14.6%), and tricyclic antidepressants (TCAs; N=6; 12.5%). The most frequently reported drugs in the SSRI category were citalopram (Celexa®; N=14; 29.2%), sertraline (Zoloft®; N=6; 12.5%), and paroxetine (Paxil®; N=5; 10.4%). The only drug reported in the SNRI category was venlafaxine (Effexor®; N=8; 16.7%). The drugs reported in the atypical category were mirtazapine (Remeron®; N=5; 10.4%) and bupropion (Wellbutrin®; N=2; 4.2%). The most frequently reported drug in the TCA class was amitriptyline (N=4; 8.3%). Three participants (6.3%) reported taking two types of antidepressants.

Eighteen months post-discharge, 40 participants (8.6%) self-reported taking an antidepressant medication. Of the 48 participants reporting antidepressant use 9 months post-ACS discharge, 31 (61.4%) were still taking one at 18 months. The concordance of antidepressant usage at both time-points was 77% (Cohen’s {kappa}). Escitalopram (Cipralex®) was the only new antidepressant reported at the 18-month assessment. Although the class of anti-depressants was generally consistent from 9 to 18 months, 4 antidepressant users (8.3%) reported a different medication at 18 months, and, for 2 (4.2%), this represented a change in antidepressant type.

Thirty-nine participants (7.7%) reported using an anxiolytic at 9 months, and 35 (7.5%) reported their use at 18 months post-hospitalization. All were benzodiazepines, and concordance in usage at both time-points was 72% (Cohen’s {kappa}). Fourteen participants (2.8%) reported using both antidepressants and anxiolytics at 9 months, and 11 (2.4%) reported using both at 18 months post-hospitalization.

Relationship Between Antidepressant Use and Anxiety and Depression Symptoms
There were 61 participants (12.3%) with elevated depression symptoms in the hospital who were retained in the study 9 months post-discharge and, at 9 months, 14 (23.0%) reported taking an antidepressant. There were 152 participants (30.6%) with elevated anxiety symptoms in the hospital who were retained in the study 9 months post-discharge and, at 9 months, 18 (11.8%) reported taking an anxiolytic.

Participants taking an antidepressant 9 months post-discharge reported significantly greater depression (mean: 5.66; standard deviation [SD]: 4.68 versus 3.60; SD: 3.38; p=0.001) and anxiety symptoms (mean: 8.46; SD: 5.07 versus 5.11; SD: 3.74; p<0.001) 18 months post-discharge than patients not on antidepressants at 9 months. The data-set was split by antidepressant usage. For participants who were not taking an antidepressant at 9 months, both depression (t=2.72; p=0.007) and anxiety symptoms (t=5.90; p<0.001) decreased significantly by 18 months. However, for participants who reported taking an anti-depressant at 9 months, anxiety symptoms improved significantly from hospitalization to 18 months later (t=2.89; p=0.006), but depression symptoms did not (t=1.34; p>0.05).

Eighteen months post-discharge, 4 of the participants (9.5%) who reported elevated depression symptoms were taking an antidepressant. At the same point, 14 participants (15.9%) who reported elevated anxiety symptoms self-reported taking an anxiolytic.

In-Hospital Correlates of Antidepressant Use 9 Months Post-ACS Discharge
As shown in Table 4, participants self-reporting antidepressant use were significantly more likely to be female, have lower family income, be less likely to be working full-time, have a greater number of medical comorbidities, and have lower functional status. Participants taking an antidepressant 9 months post-discharge also reported significantly greater anxiety and depression symptoms while in the hospital.


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TABLE 4. In-Hospital Correlates of Antidepressant Use 9 Months Post-ACS Discharge



These significant correlates were entered into a hierarchical logistic-regression analysis predicting antidepressant use after 9 months. In-hospital anxiety and depression symptoms were entered at Step 1, sociodemographic characteristics at Step 2, and clinical characteristics at Step 3. As shown in Table 5, income was excluded from the model. This is because of the interrelationship between work status and income, which may cause collinearity, and the latter variable was chosen to be excluded because it is perceived to be less reflective of personal socioeconomic status in this age-group. The overall model was significant ({chi}2=52.86; p<0.001), as were Step 1 ({chi}2=35.40; p<0.001) and Step 2 ({chi}2=12.26; p=0.002), with only a trend toward significance for Step 3, the clinical characteristics block ({chi}2=5.20; p=0.07). According to the Wald criterion, participants taking antidepressants were significantly more likely to report anxiety but not depression, had more comorbidities, and were less likely to be working full-time.


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TABLE 5. Hierarchical Logistic Regression of In-Hospital Correlates of Antidepressant Use 9 Months Post-ACS Discharge




  DISCUSSION

 
TOP
 ABSTRACT
 INTRODUCTION
 METHOD
 RESULTS
 DISCUSSION
REFERENCES
 
Depression symptoms negatively affect quality of life, adherence to evidence-based therapies, and health outcomes in cardiac patients.20 This study prospectively examined antidepressant use in a sample of ACS patients. Rates of antidepressant use were just below 10% across the 11/2 years of ACS recovery. This is fairly consistent with a 2002 population-based study in Ontario, which reported 15.7% rate of antidepressant use among post-myocardial infarction patients.21 The frequency of anxiolytic use (7.7%) was slightly lower than antidepressant use. Because there were no diagnostic interviews or assessment of psychotherapy rates, the current study is unable to determine whether the frequency of antidepressant use is appropriate to the rates of elevated depression symptoms (over 10%).

These patients generally stayed on the medication consistently, with 77% concordance in antidepressant use from 9 months to 18 months post-discharge. Only four patients changed antidepressant medications over the 9 months of assessment. Participants on antidepressants experienced significant decreases in their anxiety symptoms, but not their depression symptoms (although mean depression scores were within the "normal" range for all participants by 18 months post-hospitalization). This poor antidepressant response and the few changes in medications suggest that physician follow-up was less than optimal. Previous studies have reported that follow-up by physicians regarding dosing and patient response to antidepressants is low.22,23 However, given that there were no diagnostic clinical interviews incorporated into the study, our lack of assessment of other forms of therapy, and our non-randomized design, we cannot comment on the degree of symptom-control afforded by the antidepressant utilization observed in the current study. It is promising, however, that over 60% of the patients on antidepressants remained on the medications for at least 9 months, which should enable the drug to achieve effect.

The previous investigation of Ontario administrative data showed that 62% of the antidepressant use was from the SSRI class, and 36% were TCAs.21 Similarly, the most frequent class of antidepressant used in the current study was the SSRI (56.3%), but TCA use was much lower, at 12.5%. SSRIs have been shown to be safer among cardiac patients,24,25 and, indeed, they were the most frequently-used medications. TCA use is not recommended, given the evidence of cardiovascular toxicity,26 including increases in heart rate, orthostatic hypotension, and conduction delays.24 Fortunately, our findings suggest that TCA use has declined among ACS patients.

In a recent United States survey of cardiovascular physicians,27 55.7% reported treating comorbid depression with antidepressant medication, with the most frequent medications being sertraline (28%), paroxetine (16.1%), and fluoxetine (10.8%). Bupropion was prescribed at 4.4% and TCAs at 3.8% of the time. The rates of sertraline use are not surprising, given that the largest trial of anti-depressant safety used sertraline.20 However, in our study, use of citalopram was more frequent than use of sertraline. Similar to sertraline, citalopram is not likely to inhibit cytochrome P450 enzymes, thus minimizing interactions with cardiac medications.28 Rates of bupropion use in our study were similar, at 4.2%, and may have been prescribed to patients who smoked, although this antidepressant may cause minor increases in blood pressure.29

Although depression and anxiety are highly comorbid disorders,30,31 and medications indicated for combating depression also have anxiolytic effects,32 it is noteworthy that anxiety symptoms were more strongly related to anti-depressant usage than were depression symptoms in the model. This finding warrants further study. A recent study showed that medical residents were more likely to correctly identify anxiety than depression symptoms in their post-myocardial infarction patients.33 It could be that the somatic symptoms of anxiety are more easily recognized than affective ones. Indeed, a recent national survey of cardiovascular physicians showed that 79% reported no use of a standard depression screening method or tool.27 This suggests that more systematic screening of depression symptoms through a standardized tool such as the PRIME–MD34 is needed to correctly and consistently identify elevated depression symptoms. This screening could then lead to referral for clinical diagnosis, as appropriate, and treatment with psychotherapy and antidepressant medication. An alternative explanation for the relationship between anxiety and antidepressant use could relate to patient requests for medication or greater number of healthcare visits to quell their feelings of anxiety.

Work status was also related to antidepressant use; those who were not employed full-time were more likely to be taking antidepressants. Generally, people who are unemployed have poorer mental and cardiovascular health.35 Indeed, participants in our sample who were not working full-time reported a greater number of comorbid conditions (2.33 versus 1.65; p<0.001).

This greater number of comorbidities was also related to antidepressant use. This could, again, be explained in several ways. Most importantly, depression may be accompanied by numerous somatic symptoms, such as anorexia, fatigue, and painful physical symptoms. Second, the cognitive bias seen in depression may focus patients on their symptoms and poor health. Third, patients who have more comorbidities would have a greater number of healthcare visits, and, therefore, exposure to more providers who could screen for or recognize their depression symptoms. Fourth, many side effects have been related to antidepressant use, for example, headaches, muscle pain, and digestive problems.36 However, these side effects usually remit after the first few weeks of treatment36 and would likely not lead to the development of comorbidities. Finally, patients with many chronic health conditions, including cancer, for example,37 have a higher incidence of depression. Therefore, coping with these chronic conditions may lead to depression, and, ultimately, antidepressant use. Interestingly, antidepressant usage was not related to number of medications used, but to number of comorbid conditions.

Caution is warranted when examining these results, most notably in relation to measurement issues. The use of self-report measures is open to social-desirability bias and other errors in reporting. We could have more confidence in these results with physician-reported or administrative data on clinical depression diagnoses and antidepressant prescriptions, although our self-report antidepressant data likely reflect accurately the antidepressant prescriptions that patients have filled. The lack of diagnostic interviews precludes any conclusions on appropriateness of the antidepressant prescribing or the degree of remission afforded by treatment. Other measurement limitations relate to lack of data on unfilled prescriptions, antidepressant dosage, titration of dosages, side effects leading to discontinuation, and psychotherapy or other treatment referrals. Given the non-random study design, causal conclusions regarding the effectiveness of antidepressants cannot be drawn. Finally, generalizability is limited by the selection biases both in initial recruitment and in the characteristics of our retained sample of participants.

Overall, 15% of ACS patients reported moderate-to-severe depression symptoms in the hospital. Approximately 9% of participants reported using antidepressants at both 9 months and 18 months post-hospitalization, with most patients using SSRIs. Antidepressant users were more likely to be anxious, retired, or unemployed, and report more comorbidities. Gender was not significantly related to antidepressant use after controlling for confounding variables.

Findings suggest that physicians may more easily identify patients’ anxiety symptoms and use this information in the determination for the need for an antidepressant prescription. Moreover, ACS patients reporting a greater number of comorbid conditions likely visit a greater number of healthcare providers, and therefore have a greater chance of having their depression symptoms recognized and treated. Clearly, we must continue to promote depression screening for all cardiac patients, to promote treatment through behavioral, psychotherapeutic, and psychopharmacological means, and to continue the study of the mechanisms and effects of depression treatment on cardiac outcomes.


  ACKNOWLEDGMENTS

 
We gratefully acknowledge the efforts of Laura Ewart and Suzan Krepostman for participant recruitment and the nurses on the wards who facilitated this process.

This study was funded by the Canadian Health Services Research Foundation and the Ontario Ministry of Health and Long-Term Care and was administered by the Canadian Institutes of Health Research. Dr. Grace is supported through a Career Scientist Award by the Ontario Ministry of Health and Long-Term Care.


  REFERENCES

 
TOP
 ABSTRACT
 INTRODUCTION
 METHOD
 RESULTS
 DISCUSSION
 REFERENCES
 

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