Psychosomatics 46:451-457, September-October 2005
doi: 10.1176/appi.psy.46.5.451
© 2005 Academy of Psychosomatic Medicine
Predictors of Quality of Life in Patients With Implantable Cardioverter Defibrillators
Samuel F. Sears, Ph.D.,
Tara Saia Lewis, Ph.D.,
Emily A. Kuhl, M.A., and
Jamie B. Conti, M.D.
Received Dec. 19, 2003; revision received June 4, 2004; accepted June 25, 2004. From the Department of Clinical and Health Psychology and the Division of Cardiovascular Medicine, University of Florida, Gainesville. Address correspondence and reprint requests to Dr. Sears, Department of Clinical and Health Psychology, University of Florida, Box 100165, UF Health Science Center, Gainesville, FL 32610; ssears{at}phhp.ufl.edu (e-mail).
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ABSTRACT
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Few studies have prospectively examined characteristics of implantable cardioverter defibrillator (ICD) patients as predictors of postimplant outcome. In this study the authors considered the association between preimplant psychological characteristics, ICD shocks, and postimplant quality of life at short- and long-term follow-ups, controlling for age and ejection fraction (N=88). Hierarchical regression analyses revealed that history of depression, trait anxiety, optimism, social support, and ICD shocks accounted for 41.8% to 64.5% of the variance in quality of life indices at 8- and 14-month follow-ups, depending on the outcome assessed. Further, psychological variables were as strong as, or stronger than, age, ejection fraction, and ICD shocks in predicting quality of life outcomes.
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INTRODUCTION
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The implantable cardioverter defibrillator (ICD) continues to demonstrate itself in clinical trials as the treatment of choice for potentially life-threatening ventricular arrhythmias.1 Research on quality of life indicates that ICD therapy is equal to, or better than, antiarrhythmic medications on patient-reported and objective indicators of quality of life.2–5 The experience of an ICD shock is the most commonly cited predictor of quality of life outcome.6–8 Evidence from large randomized, controlled trials suggested that the occurrence of one shock significantly reduces quality of life,5 while other studies have indicated that only five or more shocks result in significant declines.7 Psychological distress is a common comorbid response to ICD shock, since the shocks are generally aversive and unpredictable.8 It has also been suggested that distress, such as depression, may contribute to unstable arrhythmias and poor cardiac functioning, particularly following myocardial infarction.9,10 In survey research, health care providers estimated that 10% to 20% of their ICD patients experienced reductions in quality of life, emotional well-being, and family relationships.11 A recent meta-analysis suggested that the psychological burden in ICD patients may be attributable to the underlying arrhythmia conditions, as opposed to the ICD.12 However, the data from the randomized, controlled trials5,7 were not available when this meta-analysis was published. Many ICD patients experience a variety of psychological complications after implantation, including anxiety, depression, adjustment difficulties, excessive fear of ICD firings, and diminished quality of life.11,13 The reported incidence of each of these varies greatly across studies, primarily because of variances in research design, device technology, type of assessment measures utilized, and assessment intervals reported. However, a common theme has continually emerged—numerous ICD recipients feel psychological distress at some point following device implantation.
Research has indicated that the occurrence of ICD-specific fears and symptoms of anxiety (e.g., excessive worry, physiological arousal) are the most common psychological symptoms experienced by ICD recipients, with approximately 13%–38% of recipients experiencing diagnosable levels of anxiety. Depressive symptoms are reported at rates that are generally consistent with those for other cardiac populations (24%–33%).14 Specific risk factors for poor quality of life or psychosocial outcomes include young age (<50 years of age), frequent shocks, poor premorbid psychological functioning, poor understanding of the medical condition and the ICD, and additional medical comorbidities.
Since initial intervention research suggests that cognitive behavior treatments15 and multidisciplinary care models16 provide benefits for psychological and quality of life endpoints, prospective models that encompass biomedical, psychological, social, and demographic predictors would likely provide increased understanding about how and why quality of life changes over time. The purpose of this study was to examine the association between preimplant psychological patient characteristics, experience of ICD shocks, and postimplant quality of life ratings in ICD patients at both short- and long-term follow-ups (8 and 14 months postimplant, respectively). Regarding the proposed multiple regression analyses, the following hypotheses were made: 1) the associations between predictor variables of interest (history of depression, trait anxiety, dispositional optimism, social support, and ICD shocks) and the quality of life outcome variables will be statistically significant and 2) the percentage of variance in the outcome variables accounted for by the predictor variables of interest (as defined in hypothesis 1) will be equal to or greater than the variance accounted for by the control variables of patient age and left ventricular ejection fraction.
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METHOD
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Participants
The study group consisted of 88 patients who each received an ICD implant for the first time as the primary treatment for a diagnosis of life-threatening ventricular arrhythmia. All subjects were recruited from the following two locations: 1) the Electrophysiology Clinic at the Division of Cardiovascular Medicine, Shands Hospital, University of Florida, Gainesville, and 2) the Electrophysiology Clinic at the Division of Cardiovascular Medicine, Vanderbilt University Medical Center, Vanderbilt University, Nashville, Tenn. Individuals were excluded from participation in this study if they 1) were less than 18 years of age, 2) were unable to read and write in English, 3) were cognitively impaired, or 4) indicated they would not be available for follow-up assessment. Informed consent procedures as required and approved by the institutional review boards at both the University of Florida Health Science Center and the Vanderbilt University Medical Center were followed.
Procedure
All patients were recruited to participate during inpatient hospitalization for ICD implantation. A brief interview regarding history of depression and several self-report, paper-and-pencil questionnaires were administered. Follow-up assessments were conducted by telephone and targeted two time periods: 1) 6–9 months after ICD implantation and 2) 12–15 months postimplantation.
Measures
Patient assessment instruments were administered at each of three intervals: initial assessment, short-term follow-up, and long-term follow-up. At initial assessment, information regarding demographic characteristics and medical history, social support, optimism, history of depression, and trait anxiety was collected. At each follow-up, instruments measuring general quality of life, disease-specific quality of life, and experience of ICD shocks were administered.
Initial Assessment
Social support
The Interpersonal Support Evaluation List—Short-Form17 is a 16-item self-report questionnaire that provides a single, valid score of perceived availability of supportive social resources for coping.17–19 The Cronbach alpha for the total score on the Interpersonal Support Evaluation List was 0.79 in the current subject group.
Optimism
The Life Orientation Test20 is an eight-item self-report questionnaire (with four additional filler items) that assesses generalized expectancies for positive versus negative outcomes. It has a reported test-retest reliability of 0.79,20 and the Cronbach alpha for the Life Orientation Test was 0.74 in this group.
Depression
The Schedule for Affective Disorders and Schizophrenia21 is a structured interview developed to assess the presence of psychological disorders according to research diagnostic criteria. The depressive symptoms on this measure are consistent with those currently listed in DSM-IV.22
Trait anxiety
The State-Trait Anxiety Inventory23 is a 40-item self-report questionnaire designed to measure both state and trait anxiety.24 Test-retest stability coefficients for multiple samples of college students ranged from 0.73 to 0.86, with reported test-retest validity specifically for the trait anxiety scale of 0.73 (males) and 0.77 (females). The Cronbach alpha derived for the trait anxiety scale in the current group was 0.89.
Follow-Up Assessment
General quality of life
The Medical Outcomes Study 36-item Short-Form Health Survey (SF-36)25 is a self-report questionnaire that measures health-related quality of life. It includes eight health domain scales, including scales for general health perceptions and for mental health. The general health perceptions scale measures personal evaluation of health, health outlook, perceived resiliency to illness, and perceived changes in health from 1 year ago. The mental health scale measures general mental health functioning, including depression, anxiety, behavioral-emotional control, and positive affect. The internal reliabilities of the scales were found to range from 0.77 to 0.92 in a sample of 3,053 adults.26
Disease-specific quality of life
The Seattle Angina Questionnaire27 is a 19-item self-report questionnaire that was designed to measure cardiac functioning and health-related quality of life in patients diagnosed with coronary artery disease. It includes five clinically relevant scales, including the physical limitations scale, which measures how daily activities are limited by the patient’s cardiac disease. Test-retest reliability was 0.83 in a cardiac sample.27 The physical limitations scale examined in this study group had a Cronbach alpha of 0.93 at the short-term follow-up and 0.95 at the long-term follow-up.
Experience of ICD shocks
Patients were simply asked to recall from memory the number of shocks they experienced since last contact. To confirm the self-reported ICD firing experiences, the patients were asked to provide a brief description of each event and their response (e.g., medical appointment, phone call to physician, visit to emergency room).
Planned Statistical Outcome Analyses
In this study, three different dimensions of quality of life (mental health, general health, and physical limitations) were predicted through hierarchical multiple regression analyses for both the short-term and long-term follow-up assessments. In all, six separate hierarchical multiple regression analyses were conducted. Independent variables were selected from both the medical and psychological domains; these included 1) history of depression, 2) trait anxiety, 3) trait optimism, 4) social support, and 5) ICD shocks. All analyses controlled for the biological variables of patient age and left ventricular ejection fraction by entering these variables into the model first (step 1). Following step 1, the psychological variables were entered as a block into the analysis (step 2). Then, history of ICD shocks (positive or negative) was entered into the analysis as step 3. This blocked hierarchical technique was used to allow for the determination of the relative importance of each type of independent variable in the prediction of the dependent variables and to provide an overall measure of the variance predicted by the full model.
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RESULTS
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Characteristics of the Study Group
Of the 88 patients who participated in this study, the majority were male, with a mean age of 65.3 years (range: 22 to 89). The patients were almost exclusively Caucasian, and most were married with at least a high school education. The most frequently occurring medical diagnoses in this group were predominantly cardiovascular in nature. The vast majority of patients had primary diagnoses of ventricular arrhythmia (95.4%) and coronary artery disease (69.0%), and the group’s mean left ventricular ejection fraction was 30.6% (range: 5 to 70). The mean interval for the short-term follow-up assessment was 8.2 months (SD=1.8), while for the long-term follow-up assessment the mean interval was 14.3 months (SD=1.8). Overall, a total of 60 (68.2%) of the original 88 recruited patients participated in at least one follow-up, with 31 (35.2%) participating in both follow-ups. In contrast, 28 (31.8%) of the original patients could not be assessed at either follow-up, because of factors such as death, severe health impairment, relocation, and refusal.
Analyses to examine possible differences between follow-up participants and nonparticipants on gender, ethnicity, marital status, education level, patient age, left ventricular ejection fraction, history of depression, trait anxiety, dispositional optimism, and perceived social support revealed no significant differences or probabilities. While the number of patients who could not be assessed was sizable, the exceptionally low refusal rate and the lack of initial assessment differences between the subjects who did and did not participate in follow-up suggest that a systematic self-selection bias is unlikely to have occurred.
Initial Psychological Assessment Measures
For a summary of initial psychological assessment measures, see Table 1. Results from the Schedule for Affective Disorders and Schizophrenia have been omitted from the table because the structure of the measure as a clinical diagnostic tool is such that it does not yield quantitative data. Therefore, mean scores, standard deviations, and comparative norms are not applicable.
Follow-Up Quality of Life Assessment Measures
At both the short- and long-term follow-up assessments, patients completed the mental health and general health subscales of the SF-36 and the physical limitations subscale of the Seattle Angina Questionnaire. On the SF-36, the mean scores for the mental health subscale at the short- and long-term follow-ups were calculated at 76.48 (SD=21.11) and 75.92 (SD=20.84), respectively. For the general health subscale, the mean scores at short- and long-term follow-ups were calculated at 55.41 (SD=25.51) and 48.14 (SD=20.84), respectively. Paired-samples t test analyses for both the mental health and general health subscales indicated that the mean scores did not differ significantly over time. The mean scores obtained for the physical limitations subscale of the Seattle Angina Questionnaire at the short- and long-term follow-ups were 71.49 (SD=26.87) and 65.34 (SD=29.98), respectively. Paired-samples t test analyses indicated that the mean scores did not differ significantly over time.
Experience of ICD Shocks
At the short-term follow-up, nearly half of the subjects providing information indicated that they had received at least one ICD shock (45.8%, N=27). The mean number of ICD shocks was 4.6 per patient (range: 1–19); however, the vast majority of patients received far fewer, with 40.7% reporting 1 or 2 shocks. At the long-term follow-up assessment, the results were similar, with again approximately half of the patients reporting that they had received at least one shock (55.1%, N=27). The mean number of ICD shocks at this assessment was 5.6 per patient (range: 1–28), but most patients experienced far fewer, with 37% reporting 1 or 2 shocks. Of the total study group, approximately 17% at short-term follow-up and 18% at long-term follow-up had experienced at least one ICD storm (3 or more shocks within a 24-hour period). The median number of shocks at both the short- and long-term follow-ups was 3 per patient.
Predicting Short-Term Outcome Variables
Mental health quality of life
In this regression, the control variables of age and left ventricular ejection fraction significantly accounted for 21.1% of the variance of scores on the SF-36 mental health scale. As expected, the psychological variables of history of depression, trait anxiety, trait optimism, and social support were most important in predicting mental health quality of life—significantly accounting for 39.9% of the variance, almost twice that of the control variables. When ICD firing history was added to the model, it was a relatively small but significant contributor and accounted for 3.5% of the variance. In all, the total variance in short-term mental health quality of life accounted for by this significant model was 64.5% (p< 0.001).
General health quality of life
In the second regression, the control variables of age and left ventricular ejection fraction significantly accounted for 13.7% of the variance of scores on the SF-36 general health scale. As anticipated, the psychological variables of history of depression, trait anxiety, trait optimism, and social support were highly important in predicting general health quality of life and significantly accounted for 27.4% of the variance, exactly twice that of the control variables. When ICD firing history was added to the model, it was a relatively small contributor, although still significant, and accounted for 0.7% of the variance. In all, the total variance in short-term general health quality of life accounted for by this significant model was 41.8% (p=0.04).
Physical quality of life
In the third regression, as expected, the control variables of age and left ventricular ejection fraction were relevant, significantly accounting for 23.4% of the variance of scores on the Seattle Angina Questionnaire physical limitations subscale. However, the psychological variables of history of depression, trait anxiety, trait optimism, and social support were equal in importance in predicting the physical quality of life ratings and significantly accounted for 24.1% of the variance, slightly more than that of the control variables. When ICD firing history was added to the model, it represented a smaller, but still significant, contribution—7.3% of the variance. In all, the total variance in short-term physical quality of life accounted for by this significant model was 54.8% (p=0.02).
Predicting Long-Term Outcome Variables
Mental health quality of life
In this regression, the control variables of age and left ventricular ejection fraction significantly accounted for 27.1% of the variance of scores on the SF-36 mental health scale. As anticipated, the psychological variables of history of depression, trait anxiety, trait optimism, and social support were of relatively equal importance in predicting mental health quality of life, and they significantly accounted for 25.4% of the variance. When ICD firing history was added to the model, it was a relatively small contributor, although still significant—accounting for 1.3% of the variance. In all, the total variance in long-term mental health quality of life accounted for by this significant model was 53.8% (p<0.001).
General health quality of life
In the second regression, the control variables of age and ejection fraction significantly accounted for 27.3% of the variance of scores on the SF-36 general health scale. As anticipated, the psychological variables of history of depression, trait anxiety, trait optimism, and social support were important in predicting general health quality of life and significantly accounted for 17.6% of the variance, approximately two-thirds the variance accounted for by the control variables. When ICD firing history was added to the model, it was again a relatively small contributor, although still significant, accounting for 1.6% of the variance. In all, the total variance in long-term general health quality of life accounted for by this significant model was 46.5% (p=0.003).
Physical quality of life
In the third regression, as expected, the control variables of age and ejection fraction significantly accounted for some variance of scores on the Seattle Angina Questionnaire physical limitations subscale (14.6%). However, not surprisingly, the psychological variables of history of depression, trait anxiety, trait optimism, and social support were again more important in predicting the physical limitations score at this interval, and they significantly accounted for 26.4% of the variance, almost twice that accounted for by the control variables. When ICD firing history was added to the model, it was again a relatively small, although still significant, contributor and accounted for 2.4% of the variance. In all, the total variance in long-term physical quality of life accounted for by this significant model was 43.4% (p=0.02).
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DISCUSSION
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The current study results indicate that preimplant psychological variables (history of depression, trait anxiety, dispositional optimism, and social support) uniquely account for as much, if not more, of the variance in quality of life outcomes as do age and ejection fraction. Furthermore, the psychological characteristics were the most significant predictors of poor quality of life at both follow-up times, results that are consistent with the ample literature that suggests that psychological traits, such as anxiety, are robust, valid predictors of quality of life.13,28,29 These results suggest that identified risk factors for psychological difficulties do exist for ICD recipients; therefore, the provision of psychological interventions to all ICD recipients presenting with known risk factors, such as trait anxiety, low optimism, and history of depression, may be beneficial to optimize quality of life outcomes.14,30
Experience of ICD shocks was a significant predictor of quality of life, although to a lesser degree than the medical or psychological variables. We expected that the experience of ICD shocks would be a stronger predictor than the psychological variables, prompting "debriefing" sessions following ICD shocks. However, this study indicates that preimplant psychological variables may warrant intervention with or without the experience of shock. This is especially notable in the face of research that has implicated chronic and acute psychological factors in the development of ischemic disease and, subsequently, future ICD shocks,31 thereby making the psychological care of ICD patients even more critical. Nonetheless, it is premature to conclude that shock is not a good marker for psychological and psychiatric referral from cardiologists because a shock experience is an objective, easily detected event.8,32,33 Comparatively, a patient’s level of overall optimism, trait anxiety, or history of depression may be more difficult to ascertain in a clinical cardiology setting than whether a shock has occurred. However, select patients—such as those experiencing poor quality of life—may have problems recalling shock experiences. Nonetheless, referral based on the incidence of ICD shock continues to be a viable guidepost for referral by cardiologists at this point in time.8 Ideally, future research would extend psychological screening methods used in primary care to cardiology settings.
The major strengths of the current study involved prospective data collection and the inclusion of a variety of baseline patient characteristics prior to the experience of ICD shock. Inclusion of follow-up data at two separate endpoints—both short and long intervals after ICD implantation—is a unique feature of this study that addresses previously discrepant findings in the literature and provides descriptive information about changes over time in patient functioning and quality of life. Further, this study involved the collection of data from a study group that was very similar in demographic and medical characteristics to the patients described in large national ICD medical samples, thereby increasing the likelihood that these findings will generalize well to other ICD patient groups.
Despite this study’s multiple strengths, the results should be interpreted carefully in light of its limitations. First, consistent with the typical ICD patient, the subject group was demographically restricted to older, male, Caucasian patients. Second, both the short- and long-term follow-up intervals were marked by sizable attrition, which suggests that a self-selection bias took place such that participants with worse quality of life were less likely to participate in follow-up. However, analyses comparing participants and nonparticipants at follow-up did not indicate significant differences at the time of initial ICD implantation on medical or psychological variables. Third, although very few study patients had prescriptions for psychotropic medications and/or a psychiatric diagnosis at the time of initial ICD implantation, patient participation in psychological intervention by private providers, support groups, etc., after ICD implantation was not assessed. As differences in quality of life outcomes potentially exist between patients in treatment and those who are not, this issue represents a possible limitation in the interpretation of the results. Tracking of participants’ experience of ICD shocks relied solely on patient report, and the data were not acquired from physicians. Because of the likelihood that a greater number of shocks were actually experienced than reported, the significance of this variable as a predictor in the current study may be underestimated. Further, our study employed a conservative test of shock, since it was entered last in each of the hierarchical regression equations.
The impact of psychological maladjustment on quality of life is clear, and, despite methodological weaknesses, the influence of ICD shocks cannot be discounted.13,14,34 Given the wealth of data identifying factors associated with quality of life outcomes, future psychological research should focus on the impact of psychosocial interventions. Further research is also needed to more specifically address the independent value of each of the psychological predictor variables by determining the differential risk associated with each of these factors. The ICD represents a great innovation in decreasing mortality of sudden cardiac death. These data emphasize the importance of a biopsychosocial model in understanding the quality of life outcomes for ICD patients.
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ACKNOWLEDGMENTS
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The authors thank Nancy Connors, R.N., and John T. Lee, M.D., of Vanderbilt University for their assistance with recruitment for this study.
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REFERENCES
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- Schron EB, Exner DV, Yao Q, Jenkins LS, Steinberg JS, Cook JR, Kutalek SP, Friedman PL, Bubien RS, Page RL, Powell J: Quality of life in the Antiarrhythmics Versus Implantable Defibrillators trial: impact of therapy and influence of adverse symptoms and defibrillator shocks. Circulation 2002; 105:589–594[Abstract/Free Full Text]
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ABSTRACT
INTRODUCTION
