Author + information
- Received September 19, 2006
- Revision received January 19, 2007
- Accepted February 5, 2007
- Published online May 22, 2007.
- Woldecherkos A. Shibeshi, MD⁎,†,
- Yinong Young-Xu, ScD, MS, MA⁎ and
- Charles M. Blatt, MD, FACC⁎,†,⁎ ()
- ↵⁎Reprint requests and correspondence:
Dr. Charles M. Blatt, Lown Cardiovascular Center, 21 Longwood Avenue, Brookline, Massachusetts 02446.
Objectives This study examined the effect of anxiety on mortality and nonfatal myocardial infarction (MI) in patients with coronary artery disease (CAD).
Background Inconsistent data exist regarding the impact of anxiety on the prognosis of patients with CAD.
Methods The authors conducted a prospective cohort study at an outpatient cardiology clinic of 516 patients with CAD (mean age 68 years at entry, 82% male) by administering the Kellner Symptom Questionnaire annually. The primary outcome was the composite of nonfatal MI or all-cause mortality.
Results During an average follow-up of 3.4 years, we documented 44 nonfatal MIs and 19 deaths. A high cumulative anxiety score was associated with an increased risk of nonfatal MI or death. Comparing the highest to lowest tertile of anxiety score, the age-adjusted hazard ratio was 1.97 (95% confidence interval 1.03 to 3.78, p = 0.04). In a multivariate Cox model after adjusting for age, gender, education, marital status, smoking, hypertension, diabetes mellitus, previous MI, body mass index, and total cholesterol, each unit increase in the cumulative mean anxiety score was associated with increased risk of nonfatal MI or total mortality; the hazard ratio was 1.06 (95% confidence interval 1.01 to 1.12, p = 0.02).
Conclusions A high level of anxiety maintained after CAD diagnosis constitutes a strong risk of MI or death among patients with CAD.
Prospective studies have implicated emotional distress as a risk factor for the development of coronary artery disease (CAD) (1–3). Mental stress has been linked to the progression of atherosclerosis, development of atherothrombosis, and increased risk of arrhythmias (4–6). Among the different aspects of emotional distress, depression has been extensively studied and is considered a major cardiac risk factor (1,7,8). The role of anxiety as a prognostic factor in the development of adverse cardiac events among patients with CAD is not well understood (1,8,9). Most of the previous studies included just a single baseline measurement of anxiety symptoms. Because a single baseline measurement does not reflect long-term anxiety, we hypothesized that a high or an increasing level of anxiety that is maintained over an extended period is associated with an increased risk of MI and death in patients with CAD.
Study sample and enrollment
We prospectively studied a sample of patients with CAD from an outpatient clinic affiliated with an academic medical center. Details of the scientific rationale and characteristics of the study population have been published previously (10,11).
Between December 1992 and April 2001, consecutive patients with CAD were recruited to the study, including men and women of all ages who met one or more of the following inclusion criteria: 1) a history of a documented MI; 2) angiographically proven CAD; 3) a history of typical angina with a positive exercise treadmill test with or without nuclear imagining; or 4) a history of atypical angina with a positive exercise treadmill test verified by abnormal nuclear or echocardiographic imaging. Patients were excluded from the study if they had previous coronary revascularization or had evidence of significant coexisting cardiac disease (valvular heart disease, cardiomyopathies, New York Heart Association functional class III or IV heart failure) or comorbid conditions that could significantly shorten life span and limit follow up (e.g., cancer).
After informed written consent was obtained from each patient on study enrollment, data on sociodemographic, psychosocial, and clinical characteristics were collected. Patients completed a questionnaire annually, either during their scheduled clinic visit or by mail. A cardiologist updated the clinical data, including any interim test results, after the scheduled visit.
Assessment of anxiety
We used Kellner’s Symptom Questionnaire (SQ) (12) to measure anxiety. In addition to anxiety, SQ measures depression, hostility, and somatization, thus enabling the testing of the independent prognostic value of anxiety. This self-administered questionnaire instructs subjects to answer each of the 92 yes/no questions about their feelings during the previous week (e.g., “feeling peaceful,” “feeling that something bad will happen,” “takes a long time to fall asleep,” “upset bowels or stomach,” and so on). The instrument has been validated for its ability to discriminate between psychiatric patients and normal patients, and for its test-retest and half-split reliabilities (12–14). Each subscale has scores ranging from 0 to 23 points. Anxiety scores ≥8 were considered to be abnormally high (12). Because categorical analysis has clinical relevance and can detect graded effect, we further divided anxiety scores into tertiles based on our sample size and event rate, fitting the intuitive classification of low, intermediate, and high level of anxiety.
Assessment of risk factors
At entry to the study, attending physicians collected data on variables that are known to be strongly associated with the outcomes of interest and are potential confounders, including age, gender, level of education (below or above 12th grade), history of hypertension (those who were using antihypertensive medication or with >140 mm Hg systolic or >90 mm Hg diastolic blood pressure), diabetes mellitus (those who were being treated for diabetes or whose fasting blood sugar was >126 mg/dl), smoking (history of smoking or current smokers), alcohol intake (history of drinking, frequency, and amount), physical exercise (regularity and intensity). Blood pressure and body mass index were recorded, and laboratory data including lipid profiles (total cholesterol, low-density lipoprotein, high-density lipoprotein, triglycerides) and blood sugar were obtained. These and other variables were measured annually during follow-up.
Ascertainment of nonfatal MI and mortality
The primary outcome of interest was the composite incidence of nonfatal MI or all-cause mortality. Secondary outcome measures included nonfatal MI, cardiac death, total mortality, and unstable angina. Information on these outcomes was periodically ascertained by the treating cardiologists according to standard criteria, with additional review of inpatient and outpatient records by a research assistant. Information about death was obtained from medical records, obituaries, and interviews with proxies.
Patients with baseline anxiety levels and at least 1 follow-up anxiety measure were included in the analyses. Among these patients, 7% of the follow-up anxiety measures were missing and they were replaced using the last observation carried forward method. Anxiety scores were then cumulatively averaged to assess long-term exposure, starting with the first follow-up measure. For example, if patient X had anxiety scores 5, 10, and 15 at her first, second, and third follow-up visits respectively, then the cumulative mean score at her third follow-up is 10 ([5 + 10 + 15]/3). Cumulative mean scores were calculated until an event (nonfatal MI or death) occurred, or until the last visit if no event occurred. Consequently, a patient could never be counted twice in each analysis.
Kellner’s anxiety scores, both baseline and cumulative mean, were dichotomized at a cutoff score of 8, and were categorized into tertiles with roughly one third of the observations in each tertile. We categorized this continuous outcome because the SQ scale, like any other scale, is only quasicontinuous and has an artificial lower and upper boundary. Moreover, the categorization reduces the influence of outliers. Finally, although the cutoff points alone cannot and should not be used to make a psychiatric diagnosis, we wanted to use the binary changes (normal vs. abnormal) to capture substantial and qualitative changes in addition to numerical changes. The tertile categorization has added benefits because it was based on the distribution of our study population and could show a graded effect. The slightly finer categorization (tertiles vs. binary) also helps to recover some of the statistical power that is lost by categorizing a continuous variable. Summary statistics of baseline characteristics in relation to tertiles of baseline anxiety scores on the SQ scale (Table 1)and crude incidence rates (Table 2)were provided. The association between an individual covariate measure and baseline anxiety scores was assessed using a chi-square test for categorical data and analysis of variance for continuous variables (Table 1).
Cox proportional hazard models were used to compute univariate, age-adjusted, and multivariate adjusted HRs for both primary and secondary outcome measures per unit increase in anxiety scores (Tables 3, 4, and 5).⇓⇓⇓Models were adjusted to the following baseline covariates: age, gender, hypertension, diabetes mellitus, previous MI, smoking, exercise (duration in min/day: <15, 15 to 30, 30 to 60, and >60), level of education (below or above 12th grade), total cholesterol, body mass index, alcohol use, and aspirin use.
Survival analyses (including Kaplan-Meier) were performed. Nonparametric survival analyses using the Mantel-Cox test, which estimates rate ratios, were performed to control for difference in duration of follow-up based on a proportional hazards model. We used this test to assess differences in effect estimates among the tertiles of anxiety scores on outcome measures, and to evaluate the overall trend (Tables 3 and 4). Bivariate and multivariate adjusted effect estimates were computed separately. After dichotomizing the data into high and low anxiety scores, similar unadjusted and multivariate adjusted analyses using a Cox regression model were performed.
Both the baseline and cumulative mean follow-up anxiety scores were evaluated to assess the effect of anxiety on the composite of nonfatal MI or total mortality based on a Cox regression for equality of survival, and to contrast the power of a single baseline measure against repeated measures. Statistical significance was determined using the Cox regression model with both baseline and mean follow-up scores in the model and adjusting for the above covariates.
The HRs and 95% CIs were used to assess measurement of effect, and statistical significance levels were determined by two-tailed p values of 0.05. The Stata Statistical Software for Professionals (version 8, Stata Corp., College Station, Texas) was used for these analyses.
Baseline characteristics and incidence rate
A total of 516 participants (82% men), with an average age of 68 (±9) years, completed a baseline anxiety measurement and completed at least one follow-up psychometric evaluation. Baseline anxiety scores were lower among men and increased with age. The prevalence of other traditional CAD risk factors (except for high-density lipoprotein cholesterol) was similar among the tertiles of anxiety scores at baseline (Table 1).
The mean duration of follow-up for patients in the study was 3.4 years (range 1 to 5 years). Over a 5-year period, we documented 44 new or recurrent cases of nonfatal MI and 19 all-cause deaths (12 cardiac-related deaths) with an annualized incidence rate of 3.1 in 100 person-years (95% CI 2.4 to 4.0) for the primary outcome (composite of nonfatal MI or total mortality). The crude incidence rate of nonfatal MI or total death was higher in those who were in a higher tertile of cumulative mean anxiety scores (25.2, 27.4, and 44.0 per 1,000 person-years for being in the lower, middle, and upper tertiles, respectively) (Table 2). Kaplan-Meier survival analysis showed a greater cumulative event-free survival for those patients who had lower cumulative mean anxiety scores (Fig. 1).
Univariate and multivariate analyses results for the primary outcome
We entered the cumulative mean anxiety score as a continuous variable in a Cox regression model, and computed the associated risk of nonfatal MI or total mortality with each unit increase in the scores. The mean cumulative anxiety score significantly predicted the primary outcome in a continuous model: age adjusted HR 1.06 (95% CI 1.01 to 1.12, p = 0.02). In the multivariate model, the effect size was similar: adjusted HR 1.07 (95% CI 1.02 to 1.13, p = 0.01) (Table 3).
A significantly higher rate of nonfatal MI and death was observed in the tertile of patients with the highest cumulative mean anxiety score as compared with the tertile with the lowest score. Age adjusted rate ratio was 1.97 (95% CI 1.03 to 3.78, p = 0.04). Comparing the same groups after adjusting for age, gender, smoking, hypertension, diabetes, previous MI, physical activity, education, and alcohol use, the cardiac event rate remained significantly elevated for the highest tertile: rate ratio = 11.03 (95% CI 1.61 to 75.36, p = 0.002) (Table 3). The Mantel-Cox model was used to test for trend of graded increase of risk from the lowest to the highest tertile, and it was significant (p = 0.01). After dichotomizing the cumulative mean anxiety score at the predetermined cutoff point of 8 according to Kellner (12), we observed an age-adjusted HR of 1.63 (95% CI 0.91 to 2.96, p = 0.1) and a multivariate adjusted HR of 1.71 (95% CI 0.92 to 3.21, p = 0.09). Although the effect measures still point to a higher risk associated with abnormally high anxiety score, both HRs are significant at the 90% level instead of the usual 95% level, a loss of power that was foreseen when we dichotomized this continuous variable.
Categorizing both baseline anxiety score and cumulative mean follow-up score into tertiles, we estimated the event rate of nonfatal MI or death for each tertile of anxiety at baseline and during follow-up. These categorical analyses, using Cox regression, showed that patients who started at the lowest levels of anxiety scores at baseline and whose mean cumulative anxiety scores were increased to the highest tertile during follow-up had the highest event rate of the primary outcome compared with all the other paired combination of categories such as those who started and remained within the lowest tertile of scores or started in the highest tertile and moved to the lowest tertile (p = 0.01) (Fig. 2).
In contrast, baseline anxiety score alone (per unit increase) was not significant in either age or multivariate adjusted models in predicting the risk of adverse outcome (age-adjusted HR 0.97 [95% CI 0.91 to 1.04, p = 0.40]; multivariate-adjusted HR 0.97 [95% CI 0.90 to 1.04, p = 0.36]) (Table 4). Trend analyses of baseline anxiety score tertiles provided no evidence that baseline anxiety score could independently predict risk of nonfatal MI or death (Table 4). Additional analysis was performed in which both baseline and cumulative mean of anxiety scores were included in the model, and we found that multiple measures of anxiety can significantly predict the risk of adverse outcome even after we adjusted for baseline anxiety (multivariate-adjusted HR 1.10 [95% CI 1.02 to 1.20, p = 0.02]). Indeed, as is shown in Figure 2, part of the reason that repeated measures of anxiety could better predict adverse outcome than a single baseline measure is that repeated measures could capture the changes in anxiety score (between baseline and follow-up measures) in addition to capturing long-term exposure to high level of anxiety. When we included directly a change in the anxiety score [follow-up anxiety score − baseline anxiety score] in the Cox survival model, we found a similar result (multivariate-adjusted HR 1.10 [95% CI 1.04 to 1.16, p < 0.001]).
In secondary analyses, we examined the association between cumulative mean anxiety score and separately nonfatal MI, cardiac death, total mortality, and unstable angina. The risk of cardiac death was significantly higher for each unit increase of cumulative mean anxiety score: age adjusted HR 1.12 (95% CI 1.01 to 1.25), p = 0.04, and multivariate adjusted HR 1.15 (95% CI 1.03 to 1.29), p = 0.01. Looking at individual components of the primary outcome, the risk (per unit increase in anxiety score) trended toward an increased event rate with statistical significance hovering around the 95% level: multivariate adjusted HR 1.07 (95% CI 1.00 to 1.14, p = 0.06) for nonfatal MI; 1.10 (95% CI 0.99 to 1.22, p = 0.07) for total mortality (Table 5).
There were 120 events of unstable angina during the follow-up period. Cumulative mean SQ score was associated with an increased rate of unstable angina: age adjusted HR 1.07 (95% CI 1.03 to 1.12, p < 0.001) and multivariate adjusted HR 1.08 (95% CI 1.04 to 1.13, p < 0.001) (Table 5).
This prospective cohort study is the first to include repeated measurements of anxiety in CAD patients during long-term follow-up. Multiple measures of anxiety were significantly associated in a dose-dependent manner with a higher risk of death or nonfatal MI. Patients whose anxiety score increased during follow-up had a significantly higher risk of developing a primary adverse outcome when compared with patients whose cumulative mean anxiety score did not differ significantly from baseline, including those patients whose anxiety scores remained elevated. Baseline anxiety scores predicted neither primary nor secondary outcomes.
Repeated measures of anxiety were better predictors of outcome than a single anxiety measure. This emphasizes the toll that an escalating anxiety state may impart to patients with CAD (15–23). A single measurement of anxiety may reveal little of this complex emotion that may be influenced by the interaction between patient and physician as CAD is managed. In our study, patients with escalating anxiety levels did not fare as well as patients with declining anxiety levels over the course of study. This supports the contention that a key element of the ill-defined benefit of a calming bedside or office manner is that of allaying the anxiety of patients with CAD. Unfortunately, our data do not provide insight into why a declining anxiety score over time imparts protection from MI or death, but they do provide a quantitative assessment of the risk associated with escalating anxiety levels. Although some studies also have shown an association between increased anxiety and a higher risk of death or MI (24–27) in patients with CAD, others failed to find such an association (20–23). Our prospective study differs from previous reports on anxiety in that it involved repeated measures of anxiety of patients with stable CAD with a median duration of 5 years after diagnosis, whereas most previous studies measured anxiety only once within a few days to a few weeks after the diagnosis of CAD.
Central neural mediators of anxiety and cardiac vulnerability to recurrent MI and death may be shared (28). Chronic stress can result in increased sympathetic outflow, reduced heart rate variability and baroreflex reactivity, as well as impaired vagal control, which have been linked to increased cardiac mortality from ventricular arrhythmia and sudden cardiac death (29–34). Chronically elevated catecholamine levels have been shown to increase lipoprotein lipase levels, induce hyperglycemia, elevate blood pressure (35–38), and increase platelet aggregation (39–41).
Other psychological factors
It is possible that other psychological factors, particularly depression, could have interacted with anxiety and thus could have influenced the relationship found between anxiety and heart disease by previous studies. Unfortunately, differentiating these complex interactions and determining the unique strength of each of these psychological factors is beyond what this study design permits. Nevertheless, it was important to learn whether anxiety was an independent prognostic factor among all the psychological factors that we measured (depression, hostility, and somatization). As a result, these factors and their interaction terms with anxiety were included in the multivariate models as covariates. In all 3 cases, we found that the interaction terms were not significant, and that anxiety continued to be a significant predictor of our primary outcome. Also, when all 3 factors were entered into the multivariate model together, anxiety was still a significant predictor with an HR of 1.11 (95% CI 1.03 to 1.09, p = 0.004, per unit increase in anxiety). The prognostic value of anxiety seems to be independent of other psychological factors. This finding is consistent with that of a study by Grace et al. (42). After correcting for depression measure, they found that anxiety was a significant predictor of recurrent ischemic and arrhythmic events in a cohort of patients with diagnosed MI or unstable angina during a 12-month follow-up.
The clinical implication of our study is that anxiety should now be considered a prognostic factor in patients with CAD. Severity of anxiety could be used in risk stratification, and periodic evaluation and treatment of the anxiety state should be considered as part of the comprehensive management of coronary patients. More studies are needed to determine what screening method and what cutoff point to use. Interventional studies involving randomized clinical trials will also be necessary to establish causality and to determine whether appropriate medical and stand-alone psychosocial interventions to reduce anxiety will result in better clinical outcomes.
It is possible that our findings occurred by chance, as a result of a confounding variable or bias, but several considerations argue against a chance occurrence. These include the prospective nature of the study and the relatively long duration of follow-up. The demonstration of a strong and dose-dependent relationship between anxiety and adverse cardiac events also argues against the likelihood of a chance finding. The risk estimates for primary outcomes have been relatively consistent, regardless of the models and the selected covariates, and all but a few are statistically significant. The cumulative mean anxiety score independently predicted event rates after controlling for potential confounders. Independent ascertainment of the outcomes in this study by a treating physician and a nurse without knowledge of the degree of exposure excludes differential ascertainment bias.
The data must be interpreted in the context of the study design and the possibility of some residual and uncontrolled confounders. Certain covariates may potentially be a part of the biological causal pathway attenuating effect size. However, we addressed this issue by limiting covariates entered into the multivariate models to their baseline values. The other caveat is that because of differences in demographic characteristics of the population under study—the majority of our patients were elderly men and of a higher socioeconomic status—these results may not be generalizable to some other populations. It is also unfortunate that we did not have measures for quality of life.
Repeated measures of anxiety predicted the composite outcome of nonfatal MI or death in patients with stable CAD. Baseline anxiety scores failed to predict these outcomes, suggesting that assessing anxiety regularly over the long term is necessary. Furthermore, the cumulative mean score separately predicted cardiac death or unstable angina. Interventional studies in the form of randomized clinical trials to assess the efficacy of anxiety reducing interventions on outcomes are needed.
Supported in part by the Lown Cardiovascular Research Foundation, Brookline, Massachusetts.
- Abbreviations and Acronyms
- coronary artery disease
- confidence interval
- hazard ratio
- myocardial infarction
- The Kellner Symptom Questionnaire
- Received September 19, 2006.
- Revision received January 19, 2007.
- Accepted February 5, 2007.
- American College of Cardiology Foundation
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