- Email: [email protected]
The accuracy of symptom reporting by patients complaining of palpitations
The Accuracy of Symptom Reporting by Patients Complaining of Palpitations Arthur J. Barsky, MD, Paul D. Cleary, PhD, Maria C. Barnett, MPH, Cindy L. Christiansen, PhD, Jeremy N. Ruskin, MD, Boston, Massachusetts
To examine the relationship between patients’ reports of palpitations and documented arrhythmias. PATIENTS
AND
METHODS:
COIlSf.XUtiVf?
PatietltS
complaining of palpitations and referred for 24hour ambulatory electrocardiographic monitoring were studied using self-report questionnaires and a structured diagnostic interview. Electrocardiographic results were subsequently analyzed in conjunction with symptom diaries. Positive predictive value was used to estimate the likelihood that a reported symptom coincided with a documented arrhythmia. Sensitivity was calculated as a measure of the likelihood that an arrhythmia would be detected and repotted as a symptom. RESULTS: Positive predictive value was inversely related to somatization, hypochondriacal attitudes, and psychiatric symptoms. It was not related to chronic&y of palpitations, previously diagnosed heart disease, more extensive medical care utilization, or clinically significant arrhythmias. Patients were generally insensitive to their arrhythmias, failing to note the vast majority. CONCLUSIONS: Somatizing and hypochondriacal patients are not more sensitive to or accurately aware of subtle changes in cardiac activity, but rather may be expressing a response bias toward reporting somatic and psychologic distress in general. Apparently, patients do not learn to discriminate and detect cardiac activity more accurately as a result of having more medical care or suffering longer with their symptoms.
From the Department of Psychiatry (AJB), Harvard Medical School, Diwsion of Psychiatry, Brigham and Women’s Hospital; Department of Health Care Pokey (PDC, CLC), Harvard Medical School; Psychiatry Service (MCB), Massachusetts General Hospital; Department of Medicine (JNR), Harvard Medical School, Medical Service, (Cardiac Unit), Massachusetts General Hospital, Boston, Massachusetts. Requests for reprints should be addressed to Arthur J. Barsky, MD, Brigham and Women’s Hospital, Division of Psychiatry, 75 Francis Street, Boston, Massachusetts 02115. Supported by Research Grants #HL43216 from the National Heart, Lung, and Blood Institute, and #HS-07118 from the Agency for Health Care Policy and Research. Manuscript submitted May 5, 1993, and accepted In revised form January 24, 1994.
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ymptoms are unreliable indicators of underlying tissue pathology. The radiographic size of peptic ulcers, for instance, is only weakly correlated with symptom reports k2., arthritic pain cannot be predicted from bone roentgenograms alone3 and is more closely associated with attitudes toward the disease than with the extent of joint pathology$ asthmatic patients’ dyspnea corresponds poorly with measures of airway obstruction5; and the symptoms of diabetes correlate better with depression than with glycosylated hemoglobin levels.6 In cardiac disease as well, symptoms and demonstrable pathology do not have a fixed, one-to-one correspondence. Many patients with palpitations are without arrhythmias and a large proportion of arrhythmias are asymptomatic. When patients complaining of palpitations undergo 24-hour ambulatory electrocardiographic monitoring, 39% to 85% manifest some rhythm disturbance.7-14 (The vast majority of these arrhythmias are benign, clinically insignificant, and do not merit treatment.) Although as many as 75% of these patients with arrhythmias report their presenting symptom during monitoring,7-QJ3-‘6 for only about 15% of them do their symptom reports coincide with their arrhythmia.s.7-10J4-17Thus, accurate symptom reports occur in less than 10% of all patients being monitored. There also appears to be little correspondence between the specific nature of the patient’s symptoms and the type of arrhythmia that generated it.7J1 This literature, however, has significant limitations: The term palpitations is not explicitly defined, standardized methods of assessment are lacking; precise temporal relationships between symptoms and arrhythmias are not established; and comparison or control groups are omitted. Palpitations are defined as a sudden and disquieting awareness of one’s heartbeat. They may refer to a change in rate, rhythm, or force of contraction. Palpitations may be described as pounding, racing, skipping, stopping, thumping, fluttering, or as a sensation that one’s heart is beating irregularly. Often, neither patients nor physicians make explicit the precise sense in which they use the term, and considerable confusion may result. The aim of this study was to explore the relationship between symptom reporting and cardiac activity in patients undergoing ambulatory electrocardiogra-
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phy for palpitations. We also sought to characterize the differences between accurate and inaccurate symptom reporters.
METHODS Subjects and Setting Eligible subjects consisted of consecutive outpatients referred to the Holter Laboratory of the Massachusetts General Hospital over an 1l-month period for the evaluation of palpitations or dizziness, or both. The inclusion criteria were English fluency and availability for a follow-up interview 6 months later. Patients with major sensory or communication deficits or with significant organic brain disease were excluded. Asymptomatic nonpatient volunteers served as a comparison group.
Design and Procedure Patients were contacted immediately after referral to the Holter Laboratory. Those agreeing to be studied came to the hospital before their electrocardiogram appointments to complete the research battery, which took approximately 1%hours. Patients then received specially designed diaries for recording symptoms during monitoring, and were instructed in completing an entry for each palpitation they noted. Due to scheduling constraints, some patients completed the battery immediately after, rather than immediately before, receiving the Holter monitor. Patients received $50 for participating in the study. A continuous, 24-hour electrocardiogram was recorded in the standard fashion with a dual channel recorder (Del Mar Avionics Electrocardiocorder, Model 453A, Irvine, California), with five leads placed in a modified CM lead convention. Patients were given a clock to determine the exact time of all symptoms, and were taught to mark the electrocardiogram recording at the onset of each symptom. Recordings were scanned and analyzed with a Holter analysis unit (Del Mar Avionics, Model 750), and then interpreted by a cardiologist.
Variables and Their Measurement Cardiac symptoms and status. Palpitations were recorded in the diary by choosing among nine different descriptive terms (for example, thumping, skipping, racing). A history of known cardiac disease and treatment was obtained from the patient during the research interview. Psychiatric indices. Somatization was measured with the self-report Somatic Symptom Inventory (SSI). It consists of 26 somatic symptoms that are common to the somatization subscale of the Hopkins Symptom Checklist-90 and the hypochondriasis subscale of the MMPI.lhlg Responses are scored on a 5point ordinal scale. This questionnaire has excellent September
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intrascale consistency and test-retest reliability.“0-22 Hypochondriacal symptoms were assessed with the 14-item, self-report Whiteley Index. This scale assesses attitudes and concerns about health and disease rather than somatic symptoms. On principal components analysis, it yields three factors: disease conviction (the unfounded belief one has a serious disease), disease fear, and bodily preoccupation. It has excellent test-retest and intrascale reliability, as well as discriminant and convergent validity.2”2i Psychiatric diagnoses were assessed with the Diagnostic Interview Schedule (DIS), version 3-R.28 This is a widely used, highly structured interview that generates most of the major axis I diagnoses, both current and lifetime, and is scored by computer using operationalized DSM-III-R criteria. We employed only the modules for anxiety disorders, depressive disorders, and somatization disorder. Simple and social phobias were omitted from these analyses because they are very prevalent and are less clinically significant. State anxiety was measured using the Spielberger State-Trait Anxiety Inventory (STAI), a 20-item selfreport questionnaire that has excellent internal consistency as well as construct, concurrent, and convergent validity. 2g The State Anxiety subscale measures the severity of anxiety symptoms at the time of administration (in contrast to anxiety disorder, which was diagnosed with the DIS interview, described above). It has been used extensively in studies of cardiac disease and of transient anxiety induced by experimental procedures and surgery.30-32 Medical utilization. Patients were asked about all scheduled physician visits, walk-in and emergency visits, days hospitalized, and all outpatient visits to a mental health professional in the preceding 12 months, at both the study hospital and other sites.
Statistical Analyses The Holter electrocardiogram was analyzed in conjunction with the symptom diary to determine cardiac activity during the 30 seconds preceding each symptom report. A symptom was considered accurate when it followed an extrasystole; the onset or termination of tachycardia, flutter, or fibrillation; a pause exceeding 2 seconds; or a change in sinus rate of 50% or greater. To assess the degree of association between symptom reports and cardiac activity, we calculated a statistic we refer to as average positive predictive value. This value is equal to the number of reported symptoms that were preceded by an arrhythmia divided by the total number of symptoms reported (true positives/[&tie positives + false positives]). The positive predictive value of a test usually is calculated for a single test administered once to each patient. Our sta1994
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TABLE I Types of Symptoms Reported* Palpitation Patients (n q 145) Number of Symptom Reports Symptom 20 Stopping Fluttering 111 Irregular heartbeat 156 Jumping 79 Pounding/vigorous heartbeat 125 Racing 105 Faintness 38 49 Chest pain Shortness of breath 73
Average Positive Predictive Value+ ,950 ,811 ,782 ,620 ,392 ,210 ,158 ,143 .137
‘Frequency and average positive predictive value by type of symptom reported. +Number of symptoms accompanied by arrhythmia divided by total number symptoms reported.
tistic summarizes the association between symptoms and cardiac events for all symptoms reported by each patient. Thus, it is based on only one symptom for some patients and multiple symptoms for others. In statistical terms, these are repeated measures or clustered observations within individuals. When analyzing repeated measures within individuals, it is important to take into account that observations within individuals are likely to be correlated. Positive predictive value is clinically meaningful because it indicates the likelihood that any given symptom report will be related to an arrhythmia. However, for any indicator (namely, test or symptom) with given performance characteristics, positive predictive value will be positively associated with the relative frequency of the phenomena being detected, in this case cardiac events. That means that among persons for whom the likelihood of detecting a given event is the same, positive predictive value will be higher for those with more cardiac events. Therefore, to estimate the association between patient characteristics and positive predictive value, taking into account the varying number of symptoms per patient, we employed beta-binomial regression models.3336 After estimating the association between each characteristic and average positive predictive value, we estimated another model that included all the patient characteristics that had statistically significant bivariate associations with average positive predictive value. Because of the association between positive predictive value and the incidence of arrhythmias, we also estimated a model that included these variables and the number of arrhythmias experienced by the patient. To simplify the interpretation of coefficients from these models, we converted them into odds ratios. An odds ratio describes the relative likelihood that symptoms are related to arrhythmias for one category of patient as compared with another (for example, male versus 216
female). In the case of a continuous variable (such as age), the odds ratio represents the increase in relative odds for each integer increment in the independent variable (for example, 1 year). The likelihood that any given event will result in a symptom is termed the sensitivity of the symptom. As with positive predictive value, we calculate this for all events experienced by the individual. To emphasize that this is different from the conventional method of calculating the sensitivity of one test per individual, we refer to this statistic as average sensitivity. Comparisons between pairs of patient groups on continuous variables were made using Student’s t-test for equality of means. Comparisons of categorical variables were made using the chi-square test. For cases in which any expected cell frequency was less than five, Fisher’s exact test was used. To assess the association between continuous masures, we calculated Pearson product moment correlations.
RESULTS During the period of study, 238 patients underwent Holter monitoring for palpitations or dizziness, or both. Of these, 35 patients (15%) were ineligible, 8 others (3.4%) could not be contacter,, and 50 patients (21%) refused to participate. Thus, a total of 145 patients (71% of those eligible) were 1b:amined. Two of these patients complained only of xizziness, and the rest had palpitations. The mean age of the palpitation patients was 47.4 2 17.1 years; 57% were women; 49% .vere married; 88% were white, 9.7% were black, and 2.8% were Asian; 47% had graduated from high school and 44% had graduated from college.
Average Positive Predictive Value Ninety-nine palpitation patients (68%) reported at least one palpitation during monitoring. Among patients who were symptomatic, the mean number of diary symptoms was 3.7. The mean average positive predictive value for all symptom reports was 0.399. In Table I it can be seen that the palpitation descriptors most likely to be accompanied by electrocardiographic abnormalities are “heart stopping,” “fluttering,” and “irregular heartbeat.” The least predictive palpitation terms were “racing” and “pounding.” The relationships between average positive predictive value and several clinical characteristics are shown in Table II. Patients whose symptoms were more likely to coincide with electrocardiographic abnormalities were significantly older, somatized less, and were less hypochondriacal. Although no less anxious at the time of monitoring (as indicated by STAI scores), accurate reporters had fewer psychopathological symptoms and fewer psychiatric diagnoses. The likelihood that a diary symptrj’: coincided with
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TABLE II Clinical Characteristics
and Positive Predictive Adjusted Odds Ratio
Sociodemographic Characteristics Age (years) Gender (female) Socioeconomic position (l-5) Marital status (married) Psychiatric Characteristics State anxiety (l-4) Somatization (l-5) Hypochondriacal symptoms (l-5) Number of psychopathological symptoms in past year Number of psychiatric diagnoses More than 1 lifetime psychiatric diagnosis+
Value* 95% Confidence Interval
1.04 11.00 1.08 .96
(1.01 (0.48 (0.78 (0.47
1.06) 2.09) 1.49) 1.96)
1.00 0.31 0.51 0.84 0.71 0.66
(0.96 (0.17 (0.31 (0.74 (0.50 (0.32
1.04) 0.58) 0.83) 0.97) 1.03)
1.351
‘Adjusted odds ratios, estimated usrng beta-binomial regression. These ratios represent the relative likelihood that palpitations are more accurate tie, have a higher positive predictive value) in patients with and without each clinical characteristrc or in patients with a one integer increment in the characteristic. (See Statistical Analyses section for futher explanation.) rExcluding simple and social phobias.
TABLE Ill Medical
Characteristics
and Positive Predictive Adjusted Odds Ratio
Clinical Characteristics Duration of palpitations (months) Percent of patients with known cardiac history Medical Care Utilization Previous Holter monitor Previous stress test Number of physician visits, preceding 12 months Number of emergency & walk-in visits, preceding 12 months Days hospitalized, preceding 12 months Number of mental health visits, preceding 12 months
Value* 95% Confidence Interval
1.00 0.94
(0.996 1.003) (0.44 2.02)
1.51 1.53
(0.68 3.34) (0.73 3.18)
1.01
(0.98
1.05)
0.82
(0.66
1.02)
0.80
(0.51
1.26)
0.21
(0.07
0.61)
‘Adjusted odds ratios, estimated usrng beta-binomial regression. These ratios represent the relative likelihood that palpitations are more accurate (ie, have a higher positive predictive value) in patients with and without each clinical characteristic or in patients with a one integer increment in the characteristic. (See Statistical Analyses section for f&her explanation.)
an arrhythmia was not related to the chronicity of the chief complaint or to whether the patient gave a history of previously diagnosed heart disease (Table III). Nor was average positive predictive value related to the clinical significance of the arrhythmia: Patients with ventricular or supraventricular tachycardia, atrial flutter or fibrillation, or bradycardia (n = 28) did not differ significantly from patients with benign arrhythmias in average positive predictive value or in the number of diary symptoms. Accurate awareness of arrhythmias might be expected to be related to medical care use, since more contact with doctors and more diagnostic testing could cause patients to scrutinize themselves more and become hypervigilant about bodily sensations. As shown in Table III, however, average positive predictive value was significantly related only to the number of mental health visits. When we included all the significant predictors of
average positive predictive value in a multiple betabinomial regression model, the only statistically significant predictor of average positive predictive value was the patients’ somatization score (odds ratio = 0.41; 95% confidence interval (CI) 0.19 to 0.90). When the number of cardiac events was added to the model, the somatization score was still significant (odds ratio = 0.41; 95% CI 0.18 to 0.96).
Correspondence Between and Type of Arrhythmia
Type of Symptom
Does the descriptive term chosen by the patient to characterize the palpitation correspond to the type of arrhythmia that occasioned it? As shown in Table IV, when associated with an arrhythmia, the sensation of the heart stopping always followed a ventricular premature contraction (although there were only 19 such reports). Eighty-five percent of the accurate reports of “jumping” and “pounding” followed ventricular pre-
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mature contractions. In contrast, the complaints of “irregular heartbeat” and “fluttering” were less predictive: Approximately half of these reports, when accurate, resulted from ventricular premature contractions, and approximately half of them followed atrial premature contractions. The descriptor used did not correspond in a literal fashion to the type of arrhythmia that caused it. Thus, “stopping” never coincided with bradycardia or a prolonged pause, and “racing” was never associated with tachycardia.
tom characterizations vary in the likelihood that they reflect an underlying arrhythmia: “stopping,” “fluttering,” and “irregular heartbeat” have higher average positive predictive values than do “racing” or “pounding.” Thus, for example, 19 of 20 patient reports of “heart stopping” followed an electrocardiographic irregularity, whereas only 22 of the 105 reports of Yacing” heart were accompanied by an abnormality. The likelihood that a symptom report was preceded by an arrhythmia was inversely related to self-reported measures of somatization and hypochondriaAverage Sensitivity sis (disease fear, unwarranted disease conviction, and Palpitations are extremely insensitive indicators of bodily preoccupation). Somatizing and hypochondriarrhythmias; there is a very low likelihood that any acal patients might be expected to be more sensitive given arrhythmia will be noticed and reported as a and more astute interoceptors who notice benign symptom. Of the 145 patients, 7 had no cardiac events bodily dysfunctions, mild self-limited infirmities, and during the monitoring period and data were missing normal physiologic functions to which other people on this variable for 1 subject. Of the remaining 137 are insensitive or fail to discern. That would imply patients, 87 (64%) detected none of their arrhythmias that somatizers could make finer visceral discriminaat all. Only 8 detected more than 10% of the events tions and could detect more subtle cardiac irregularthat occurred, and only 26 detected more than 1%. ities. Our findings suggest, however, that this is not Even the patients with the highest average positive the case and instead imply that somatizing and predictive values were very insensitive and failed to hypochondriacal concerns are better understood as note the vast majority of their arrhythmias. Only 6 of a general response bias toward the expression of bodthe 30 patients with at least one accurate symptom ily distress, a global proclivity to feel uncomfortable. report had average sensitivities greater than or equal To use a signal detection paradigm, somatizers may to 0.25. In all, 82% of patients with ventricular pre- not be particularly sensitive detectors of weak and inmature contractions and 87% of patients with atrial frequent bodily signals, but rather may be unable to premature contractions had no accurate diary symp- discriminate signals from background noise. tom reports. Among the less common arrhythmias, The inverse relationship between positive predicthere were no accurate symptom reports of atrial fib- tive value and psychiatric disorder is not surprising. rillation, bradycardia, or pauses. An extensive body of research indicates that patients with high levels of psychologic distress and psychiRelationships Among Arrhythmias, Accuracy, atric symptoms report high levels of somatic symptoms as we11.3g-43As Watson and Pennebaker@ have and Sensitivity Average positive predictive value is positively as- observed, physical symptoms and negative moods tosociated with the incidence of arrhythmias, because gether often reflect a pervasive underlying disposition as the number of cardiac events increases the statis- toward experiencing distress and discomfort in gentical probability that any random symptom will coineral. Thus, medical outpatients who are more psycide with an event also increases. As predicted, the chiatrically disturbed would be expected to report total number of arrhythmias in 24 hours was signifimore somatic symptoms in general and more cardiac cantly associated with average positive predictive symptoms (such as palpitations) in particular. In value (r = 0.41; P = 0.0001). Average sensitivity, howmany instances then, Holter diary reporting may be ever, was not significantly related to the number of viewed as one particular manifestation of more genarrhythmias (r = -0.12; P = 0.18). eralized somatic distress and concern. Patients with higher average positive predictive COMMENTS values are also significantly older and have much Although a number of earlier reports suggested lit- more arrhythmic activity. This relationship is partly tle correspondence between arrhythmias and palpia statistical one, as discussed above. But in addition, tations during Holter monitoring,7-gJ2J5J6,37,38this dis- the data suggest the possibility that as a group, accrepancy was not probed or elucidated. In this study, curate reporters have more serious cardiac morbidseveral significant differences emerge between pa- ity. They may be referred for Holter monitoring betients whose symptoms tend to coincide with ar- cause they are sicker and older, and because their rhythmias and patients whose symptoms tend not to. physicians have a higher index of suspicion for carThe former somatize less, are less hypochondriacal, diac disease. The patients with lower positive preand have less psychiatric morbidity. Specific sympdictive values, on the other hand, are younger and 218
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TABLE IV Symptoms and Arrhythmias* % of Symptom Reports Resulting from Premature Ventricular Contractions Accurate reports of racing heart (n = 22) 72.7% Accurate reports of irregular heartbeat In = 125) 48.0% Accurate reports of heart pounding (n = 50) 84.0% Accurate reports of heart fluttering (n = 90) 57.8% Accurate reports of heart jumping (n = 40) 85.7% Accurate reports of heart stopping (n = 19) 100.0% ‘Relationshipof type of symptomto type of arrhythmia.
have less arrhythmic activity. They may represent a different group of patients who are being Holter monitored with a different rationale. In these eases, the electrocardiogram may have been obtained to reassure an unusually worried patient that nothing serious is wrong, or because the patient insisted on it, rather than because significant electrocardiographic findings were anticipated. Does the type of palpitation reported convey any descriptive or diagnostic information about the type of arrhythmia causing it? Reporting that the heart stopped, when indicative of an arrhythmia, always resulted from a premature ventricular contraction. The sensation of the heart “jumping” indicated a premature ventricular contraction 85% of the time that it followed any arrhythmia. But symptoms do not appear to be literal descriptors of the type of arrhythmia that produced them: “Stopping” never reflected a pause or bradycardia, and “racingt) was never accompanied by taehycardia. No term was used significantly more of-. ten to refer to a clinically significant, as opposed to a benign, arrhythmia. From a clinician’s perspective, the likelihood that a symptom coincides with a documented arrhythmia is the most salient aspect of symptom accuracy. But the converse phenomenon, the likelihood that an arrhythmia will become manifest by generating a symptom report, is also of interest. Patients were generally insensitive to arrhythmias, and only a very small fraction of arrhythmias generated symptom reports. It was particularly striking that none of the patients with atria1 fibrillation, who were most subject to arrhythmic activity, reported any palpitations at all. Even patients with high average positive predictive values did not notice the vast majority of their arrhythmias. This study has several limitations. First, some parameters were defined arbitrarily. Thus, to constitute an accurate symptom report, an arrhythmia had to occur within 30 seconds before the symptom; we used 50% as the cutoff for a perceivable change in heart rate, and at least 2 seconds as the duration of
% of Symptom Reports Resulting from Premature Atrial Contractions 18.2% 44.8% 12.0% 38.9% 14.3% 0
% of Symptom Reports Resulting from Atrial Tachycardias 0 4.8% 2.0% 1.1% 0 0
a perceivable pause. Second, caution is necessary in generalizing from this restricted and biased sample to medical outpatient populations in general. Patients referred for Holter monitoring may not be representative of all ambulatory medical patients complaining of palpitations. Indeed, as discussed earlier, the Holter laboratory population is likely to be enriched with patients who are unduly worried about their symptoms and with patients who have more serious arrhythmias. Third, there are conceptual difficulties in this study. A single premature beat is hardly comparable to a prolonged tachycardia, yet we did not take the duration of each arrhythmia into account. Another limitation of our data is more technical, in that it was sometimes impossible to decipher the electrocardiogram preceding a given symptom: Patients failed to activate the event button, it did not work properly, or the tracing was illegible. Finally, our psychiatric evaluation did not include a screen for alcohol and substance abuse, and these are prevalent and important disorders in ambulatory medical populations. More knowledge of the relationship between palpitations and arrhythmias could improve differential diagnosis and symptom palliation. At present, the evaluation and management of the patient complaining of palpitations is often problematical and unsatisfactory. Frequently, the medical evaluation is inconclusive, Holter monitoring is uninformative, and no etiology is established. At that point, nonspecific reassurance is often ineffective, and many palpitation patients remain symptomatic, distressed, and impaired over long periods.44 Even for patients with clinically significant arrhythmias, antiarrhythmic pharmaeotherapy may fail to produce symptom relief since the patients’ symptoms rarely result from their arrhythmias. What clinical implications emerge from this work? First, the practitioner needs to remember that the complaint of palpitations is more likely to reflect an arrhythmia (although not necessarily a clinically serious arrhythmia) in patients who somatize less and
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have fewer hypochondriacal concerns about their health, and in patients who are less psychiatrically disturbed. Somatizing patients-namely, those who report more somatic symptoms without a medical basis-are apparently less able to accurately detect changes in cardiac rhythm and discriminate them from the background sensations of normal cardiac activity. Their palpitations are best viewed in this broader context as only one manifestation of the multiple somatic symptoms they report in many bodily locations. Likewise, the palpitations of patients with more psychiatric disorders may also be thought of as merely one instance of a more general phenomenon, a more global state of physical distress. Focusing on their palpitations to the exclusion of their other functional, somatic symptoms risks missing the forest for the trees; Holter-monitoring such patients may sometimes be like taking roentgenograms of only the interphalangeal joints of a patient with widespread arthritis. That does not necessarily mean, however, that these patients do not need monitoring-somatizing and psychiatric patients have their share of significant heart disease. But this work does suggest monitoring might be delayed until the physician has searched carefully for a psychiatric disorder or a more general pattern of somatization. Treatment of a psychiatric disorder, such as panic disorder or major depression, could then be initiated and Holter monitoring only carried out if psychiatric treatment fails to eliminate the palpitations. Thus our findings do not dictate whether or not monitoring should be performed, but rather suggest a temporal sequencing of diagnostic and therapeutic efforts. In addition, the study implies that more precision is necessary in the task of history-taking. The simple term “palpitations,” as used both by patients and doctors, is too imprecise, ambiguous, and vague. Although our data do not confii a literal correspondence between the patient’s description and the nature of the arrhythmia, we did find that some descriptive terms have higher predictive values than others. Finally, there are implications for the use of physician services and of ambulatory monitoring. Rising concerns about the cost of medical care force us to improve the diagnostic yield of history-taking itself and to develop better criteria for the use of expensive laboratory tests. This problem is particularly accute for somatizing patients, since they are among the greatest users of medical care.45l46The ability to recognize such patients earlier and to diagnose and treat their underlying psychiatric disorders instead of pursuing extensive and fruitless medical evaluation will only become more crucial with the growing need to contain medical costs.
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REFERENCES 1. Peterson WL, Sturdevant RAL, Frank1 HD, et al. Healing of duodenal ulcer with an antacid regimen. NEJM. 1977;297:341-345. 2. Bodemar G, Walan A. Maintenance treatment of recurrent peptic ulcer by cimetidine. Lancet. 1978;1:403-407. 3. Hussar AE, Guller EJ. Correlation of pain and the roentgenographic findings of spondylosis of the cervical and lumbar spine. Am J Med SC;. 1956; 232:518-527. 4. Lichtenberg PA, Swensen CH, Skehan MW. Further investigation of the role of personality, lifestyle and arthritic severity in predicting pain. J Psychosom Res. 1986;30:327-337. 5. Burdon JGW, Juniper EF, Killan KJ, et al. The perception of breathlessness in asthma. Am Rev Resp Dis. 1982;162:825-828. 6. Lustman PJ, Clause RE, Carney RM. Depression and the reporting of diabetes symptoms. Int JPsychiatry Med. 1988;18:295-303. 7. Zeldis SM, Levine BJ, Michelson EL, Morganroth J. Cardiovascular complaints; correlation with cardiac arrhythmias on 24hour ECG monitoring. Chest. 1980;78:456-462. 8. Burckhardt D, Luetold BE, Jost MV, Hoffman A. Holter monitoring in the evaluation of palpitations, dizziness and syncope. In: Roelandt J, Hugenholtz PG, eds. Long-Term Ambulatory Electrocardiography. The Hague: Martinus Nijhoff; 1982;29-39. 9. Clark PI, Glasser SP, Spoto E. Arrhythmias detected by ambulatory monitoring. Chest. 1980;77:722-725. 10. Kennedy HL, Chandra V, Sayther KL, Caralis DG. Effectiveness of increasrng hours of continuous ambulatory electrocardiography in detecting maximal ventricular ectopy. Am J Cardiol. 1978;42:925-930. 11. Lipski J, Cohen L, Espinoza J, et al. Value of Holter monitoring in assessing cardiac arrhythmias in symptomatic patients. Am J Cardiol. 1976;37:102-107. 12. Goldberg AD, Raftery EB, Cashman PMM. Ambulatory ECG records in patients with transient cerebral attacks or palpitations. BMJ. 1975;4:569-571. 13. Hasin Y, David D, Rogel S. Diagnostic and therapeutic assessment by telephone ECG monitoring of ambulatory patients. BJM. 1976;11:609-612. 14. Grodman RS, Capone RJ, Most AS. Arrhythmia surveillance by transtelephonic monitoring. Am Heart J. 1979;98:459-464. 15. Morahan JP, Denes P, Rosen KM. Portable ECG monitoring. Arch fntern Med. 1975;135:1188-1194. 16. Kunz G, Raeder E, Burckhardt D. What does the symptom “palpitation” mean? ZKardiol. 1977;66:138-141. 17. Winkle RA, Derrington DC, Schroeder JS. Characteristics of ventricular tachycardia in ambulatory patients. Am J Cardiol. 1977;39:487-492. 18. Derogatis LR, Lipman RS, Covi L, et al. The Hopkins Symptom Checklist (HSCL): a self-report symptom inventory. Behav Sci. 1974;19:1-15. 19. Lipman RS, Covi L, Shapiro AK. The Hopkins Symptom Checklist (HSCL): factors derived from the HSCL-90. Psychopharmacol Bull. 1977;13:43-45. 20. Weinstein MC, Berwick DM, Goldman PA, et al. A comparison of three psychiatric screening tests using Receiver Operating Characteristic (ROC) analysis. Med Care. 1989;27:593-607. 21. Barsky Al, Wyshak G, Klerman GL. Hypochondriasis: an evaluation of the DSM-III criteria in medical outpatients. Arch Gen Psychiatry. 1986;43:493-500, 22. Barsky AJ, Wyshak G, Klerman GL. Transient hypochondriasis. Arch Gen Psychiatry. 1990;47:746-752. 23. Pilowsky I. Dimensions of hypochondriasis. Br J Psychiatry. 1967;113:89-93. 24. Pilowsky I. A general classification of abnormal illness behaviors. Br J Med Psychol. 1978;51:131-137. 25. Pilowsky I, Murrell TGC, Gordon A. The development of a screening method for abnormal illness behavior. J Psychosom Res. 1979;23:203-207. 26. Beaber RJ, Rodney WM. Underdiagnosis of hypochondriasis in family practice. Psychosomatics. 1984;24:39-45. 27. Barsky AJ, Wyshak G. Hypochondriasis and related health attitudes. Psychosomatics. 1989;30:412-420. 28. Robins LN, Helzer JE, Croughan J, Ratcliff KS. National Institute of Mental Health Diagnostic Interview Schedule. Its history, characteristics, and validity. Arch Gen Psychiatry. 1981;38:381-389. 29. Spielberger CD, Gorsuch RL, Lushere RE, et al. Manual for the State-Trait 97
ACCURACY OF REPORTS OF PALPITATIONS/BARSKY Anxiety Inventory. Palo Alto, California: Consulting Psychologist’s Press; 1983. 30. Thompson DR, Webster RA, Cordle CJ, Sutton DW. Specific sources and patterns of anxiety in male patients with first myocardial infarction. Br J Med Psychol. 1987;60:343-348. 31. Schocken DD, Greene AF, Worden TJ, et al. Effects of age and gender on the relationship between anxiety and coronary artery disease. Psychosom Med. 1987;49:118-126. 32. Shipley RH, Butt JH, Horwitz B, Farbry JE. Preparation for a stressful medical procedure: effect of amount of stimulus preexposure and coping style. J Consult Clin Psychol. 1978;46:499-507. 33. McCullagh P, Nelder JA. Generalized Linear Regression Models, 2nd ed. New York: Chapman Hall; 1989. 34. Prentice RL. Binary regression using an extended beta-binomial distribution, with discussion of correlation induced by covariate measurement errors. JAm Stat Assoc. 1986;81:321-327. 35. Rosner B. Significance testing for correlated binary outcome data. Biometrrcs. 1988;44:505-512. 36. Rosner B. Multivariate methods for clustered binary data with more than one level of clustering. J Am Stat Assoc. 1984;84:373-380, 37. Shenasa M, Curry B, Sowton E. The relationship between symptoms and arrhythmias during 24hour ECG recording. In: Stott F, Raftery E, Goulding L, eds. Proceedings of the Thrrd International Symposium on Ambulatory Monitoring. London: Academic Press; 1980. 38. Krasnow AZ, Bloomfield DK. The relationship between subjective
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symptomatology and objective frndings from ECG monitoring studies In a large unselected populatron. In: Stern S, ed. Ambulatory ECG Monitoring. Chicago: Year Book Medical Publishers; 1978;149-169. 39. Pennebaker JW. The Psychology of Physical Symptoms. New York: Springer-Verlag; 1982. 40. Pennebaker JW. Beyond laboratory-based cardiac perception: ecological rnteroception. In: Schandry R, Vaitl D, eds. Advances in Cardiac Perception. New York: Springer-Verlag; 1991. 41. Costa PT, McCrae RR. Hypochondriasis, neuroticism, and aging. Am Psychol. 1985;40:19-28. 42. Costa PT, McCrae RR. Somatic complaints in males as a function of age and neuroticism: a longitudinal analysis. J Behav Med. 1980;3:245-255. 43. Watson D, Pennebaker JW. Health complaints, stress, and distress: exploring the central role of negative affectivity. Psycho1 Rev. 1989; 96:234-254. 44. Kroenke K, Arrington ME, Mangelsdorff. The prevalence of symptoms in medical outpatients and the adequacy of therapy. Arch Intern Med. 1990;150:1685-1689. 45. Smith GR, Monson RA. Patients with multiple unexplarned symptoms; therr characteristics, functional health, and health care utrlization. Arch Intern Med. 1986;146:69-72, 46. Katon W, Lin E, Von Korff M, et al. Somatization: a spectrum of severity. Am J Psychiatry. 1991;148:34-40.
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To examine the relationship between patients’ reports of palpitations and documented arrhythmias. PATIENTS
AND
METHODS:
COIlSf.XUtiVf?
PatietltS
complaining of palpitations and referred for 24hour ambulatory electrocardiographic monitoring were studied using self-report questionnaires and a structured diagnostic interview. Electrocardiographic results were subsequently analyzed in conjunction with symptom diaries. Positive predictive value was used to estimate the likelihood that a reported symptom coincided with a documented arrhythmia. Sensitivity was calculated as a measure of the likelihood that an arrhythmia would be detected and repotted as a symptom. RESULTS: Positive predictive value was inversely related to somatization, hypochondriacal attitudes, and psychiatric symptoms. It was not related to chronic&y of palpitations, previously diagnosed heart disease, more extensive medical care utilization, or clinically significant arrhythmias. Patients were generally insensitive to their arrhythmias, failing to note the vast majority. CONCLUSIONS: Somatizing and hypochondriacal patients are not more sensitive to or accurately aware of subtle changes in cardiac activity, but rather may be expressing a response bias toward reporting somatic and psychologic distress in general. Apparently, patients do not learn to discriminate and detect cardiac activity more accurately as a result of having more medical care or suffering longer with their symptoms.
From the Department of Psychiatry (AJB), Harvard Medical School, Diwsion of Psychiatry, Brigham and Women’s Hospital; Department of Health Care Pokey (PDC, CLC), Harvard Medical School; Psychiatry Service (MCB), Massachusetts General Hospital; Department of Medicine (JNR), Harvard Medical School, Medical Service, (Cardiac Unit), Massachusetts General Hospital, Boston, Massachusetts. Requests for reprints should be addressed to Arthur J. Barsky, MD, Brigham and Women’s Hospital, Division of Psychiatry, 75 Francis Street, Boston, Massachusetts 02115. Supported by Research Grants #HL43216 from the National Heart, Lung, and Blood Institute, and #HS-07118 from the Agency for Health Care Policy and Research. Manuscript submitted May 5, 1993, and accepted In revised form January 24, 1994.
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ymptoms are unreliable indicators of underlying tissue pathology. The radiographic size of peptic ulcers, for instance, is only weakly correlated with symptom reports k2., arthritic pain cannot be predicted from bone roentgenograms alone3 and is more closely associated with attitudes toward the disease than with the extent of joint pathology$ asthmatic patients’ dyspnea corresponds poorly with measures of airway obstruction5; and the symptoms of diabetes correlate better with depression than with glycosylated hemoglobin levels.6 In cardiac disease as well, symptoms and demonstrable pathology do not have a fixed, one-to-one correspondence. Many patients with palpitations are without arrhythmias and a large proportion of arrhythmias are asymptomatic. When patients complaining of palpitations undergo 24-hour ambulatory electrocardiographic monitoring, 39% to 85% manifest some rhythm disturbance.7-14 (The vast majority of these arrhythmias are benign, clinically insignificant, and do not merit treatment.) Although as many as 75% of these patients with arrhythmias report their presenting symptom during monitoring,7-QJ3-‘6 for only about 15% of them do their symptom reports coincide with their arrhythmia.s.7-10J4-17Thus, accurate symptom reports occur in less than 10% of all patients being monitored. There also appears to be little correspondence between the specific nature of the patient’s symptoms and the type of arrhythmia that generated it.7J1 This literature, however, has significant limitations: The term palpitations is not explicitly defined, standardized methods of assessment are lacking; precise temporal relationships between symptoms and arrhythmias are not established; and comparison or control groups are omitted. Palpitations are defined as a sudden and disquieting awareness of one’s heartbeat. They may refer to a change in rate, rhythm, or force of contraction. Palpitations may be described as pounding, racing, skipping, stopping, thumping, fluttering, or as a sensation that one’s heart is beating irregularly. Often, neither patients nor physicians make explicit the precise sense in which they use the term, and considerable confusion may result. The aim of this study was to explore the relationship between symptom reporting and cardiac activity in patients undergoing ambulatory electrocardiogra-
S
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phy for palpitations. We also sought to characterize the differences between accurate and inaccurate symptom reporters.
METHODS Subjects and Setting Eligible subjects consisted of consecutive outpatients referred to the Holter Laboratory of the Massachusetts General Hospital over an 1l-month period for the evaluation of palpitations or dizziness, or both. The inclusion criteria were English fluency and availability for a follow-up interview 6 months later. Patients with major sensory or communication deficits or with significant organic brain disease were excluded. Asymptomatic nonpatient volunteers served as a comparison group.
Design and Procedure Patients were contacted immediately after referral to the Holter Laboratory. Those agreeing to be studied came to the hospital before their electrocardiogram appointments to complete the research battery, which took approximately 1%hours. Patients then received specially designed diaries for recording symptoms during monitoring, and were instructed in completing an entry for each palpitation they noted. Due to scheduling constraints, some patients completed the battery immediately after, rather than immediately before, receiving the Holter monitor. Patients received $50 for participating in the study. A continuous, 24-hour electrocardiogram was recorded in the standard fashion with a dual channel recorder (Del Mar Avionics Electrocardiocorder, Model 453A, Irvine, California), with five leads placed in a modified CM lead convention. Patients were given a clock to determine the exact time of all symptoms, and were taught to mark the electrocardiogram recording at the onset of each symptom. Recordings were scanned and analyzed with a Holter analysis unit (Del Mar Avionics, Model 750), and then interpreted by a cardiologist.
Variables and Their Measurement Cardiac symptoms and status. Palpitations were recorded in the diary by choosing among nine different descriptive terms (for example, thumping, skipping, racing). A history of known cardiac disease and treatment was obtained from the patient during the research interview. Psychiatric indices. Somatization was measured with the self-report Somatic Symptom Inventory (SSI). It consists of 26 somatic symptoms that are common to the somatization subscale of the Hopkins Symptom Checklist-90 and the hypochondriasis subscale of the MMPI.lhlg Responses are scored on a 5point ordinal scale. This questionnaire has excellent September
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intrascale consistency and test-retest reliability.“0-22 Hypochondriacal symptoms were assessed with the 14-item, self-report Whiteley Index. This scale assesses attitudes and concerns about health and disease rather than somatic symptoms. On principal components analysis, it yields three factors: disease conviction (the unfounded belief one has a serious disease), disease fear, and bodily preoccupation. It has excellent test-retest and intrascale reliability, as well as discriminant and convergent validity.2”2i Psychiatric diagnoses were assessed with the Diagnostic Interview Schedule (DIS), version 3-R.28 This is a widely used, highly structured interview that generates most of the major axis I diagnoses, both current and lifetime, and is scored by computer using operationalized DSM-III-R criteria. We employed only the modules for anxiety disorders, depressive disorders, and somatization disorder. Simple and social phobias were omitted from these analyses because they are very prevalent and are less clinically significant. State anxiety was measured using the Spielberger State-Trait Anxiety Inventory (STAI), a 20-item selfreport questionnaire that has excellent internal consistency as well as construct, concurrent, and convergent validity. 2g The State Anxiety subscale measures the severity of anxiety symptoms at the time of administration (in contrast to anxiety disorder, which was diagnosed with the DIS interview, described above). It has been used extensively in studies of cardiac disease and of transient anxiety induced by experimental procedures and surgery.30-32 Medical utilization. Patients were asked about all scheduled physician visits, walk-in and emergency visits, days hospitalized, and all outpatient visits to a mental health professional in the preceding 12 months, at both the study hospital and other sites.
Statistical Analyses The Holter electrocardiogram was analyzed in conjunction with the symptom diary to determine cardiac activity during the 30 seconds preceding each symptom report. A symptom was considered accurate when it followed an extrasystole; the onset or termination of tachycardia, flutter, or fibrillation; a pause exceeding 2 seconds; or a change in sinus rate of 50% or greater. To assess the degree of association between symptom reports and cardiac activity, we calculated a statistic we refer to as average positive predictive value. This value is equal to the number of reported symptoms that were preceded by an arrhythmia divided by the total number of symptoms reported (true positives/[&tie positives + false positives]). The positive predictive value of a test usually is calculated for a single test administered once to each patient. Our sta1994
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TABLE I Types of Symptoms Reported* Palpitation Patients (n q 145) Number of Symptom Reports Symptom 20 Stopping Fluttering 111 Irregular heartbeat 156 Jumping 79 Pounding/vigorous heartbeat 125 Racing 105 Faintness 38 49 Chest pain Shortness of breath 73
Average Positive Predictive Value+ ,950 ,811 ,782 ,620 ,392 ,210 ,158 ,143 .137
‘Frequency and average positive predictive value by type of symptom reported. +Number of symptoms accompanied by arrhythmia divided by total number symptoms reported.
tistic summarizes the association between symptoms and cardiac events for all symptoms reported by each patient. Thus, it is based on only one symptom for some patients and multiple symptoms for others. In statistical terms, these are repeated measures or clustered observations within individuals. When analyzing repeated measures within individuals, it is important to take into account that observations within individuals are likely to be correlated. Positive predictive value is clinically meaningful because it indicates the likelihood that any given symptom report will be related to an arrhythmia. However, for any indicator (namely, test or symptom) with given performance characteristics, positive predictive value will be positively associated with the relative frequency of the phenomena being detected, in this case cardiac events. That means that among persons for whom the likelihood of detecting a given event is the same, positive predictive value will be higher for those with more cardiac events. Therefore, to estimate the association between patient characteristics and positive predictive value, taking into account the varying number of symptoms per patient, we employed beta-binomial regression models.3336 After estimating the association between each characteristic and average positive predictive value, we estimated another model that included all the patient characteristics that had statistically significant bivariate associations with average positive predictive value. Because of the association between positive predictive value and the incidence of arrhythmias, we also estimated a model that included these variables and the number of arrhythmias experienced by the patient. To simplify the interpretation of coefficients from these models, we converted them into odds ratios. An odds ratio describes the relative likelihood that symptoms are related to arrhythmias for one category of patient as compared with another (for example, male versus 216
female). In the case of a continuous variable (such as age), the odds ratio represents the increase in relative odds for each integer increment in the independent variable (for example, 1 year). The likelihood that any given event will result in a symptom is termed the sensitivity of the symptom. As with positive predictive value, we calculate this for all events experienced by the individual. To emphasize that this is different from the conventional method of calculating the sensitivity of one test per individual, we refer to this statistic as average sensitivity. Comparisons between pairs of patient groups on continuous variables were made using Student’s t-test for equality of means. Comparisons of categorical variables were made using the chi-square test. For cases in which any expected cell frequency was less than five, Fisher’s exact test was used. To assess the association between continuous masures, we calculated Pearson product moment correlations.
RESULTS During the period of study, 238 patients underwent Holter monitoring for palpitations or dizziness, or both. Of these, 35 patients (15%) were ineligible, 8 others (3.4%) could not be contacter,, and 50 patients (21%) refused to participate. Thus, a total of 145 patients (71% of those eligible) were 1b:amined. Two of these patients complained only of xizziness, and the rest had palpitations. The mean age of the palpitation patients was 47.4 2 17.1 years; 57% were women; 49% .vere married; 88% were white, 9.7% were black, and 2.8% were Asian; 47% had graduated from high school and 44% had graduated from college.
Average Positive Predictive Value Ninety-nine palpitation patients (68%) reported at least one palpitation during monitoring. Among patients who were symptomatic, the mean number of diary symptoms was 3.7. The mean average positive predictive value for all symptom reports was 0.399. In Table I it can be seen that the palpitation descriptors most likely to be accompanied by electrocardiographic abnormalities are “heart stopping,” “fluttering,” and “irregular heartbeat.” The least predictive palpitation terms were “racing” and “pounding.” The relationships between average positive predictive value and several clinical characteristics are shown in Table II. Patients whose symptoms were more likely to coincide with electrocardiographic abnormalities were significantly older, somatized less, and were less hypochondriacal. Although no less anxious at the time of monitoring (as indicated by STAI scores), accurate reporters had fewer psychopathological symptoms and fewer psychiatric diagnoses. The likelihood that a diary symptrj’: coincided with
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TABLE II Clinical Characteristics
and Positive Predictive Adjusted Odds Ratio
Sociodemographic Characteristics Age (years) Gender (female) Socioeconomic position (l-5) Marital status (married) Psychiatric Characteristics State anxiety (l-4) Somatization (l-5) Hypochondriacal symptoms (l-5) Number of psychopathological symptoms in past year Number of psychiatric diagnoses More than 1 lifetime psychiatric diagnosis+
Value* 95% Confidence Interval
1.04 11.00 1.08 .96
(1.01 (0.48 (0.78 (0.47
1.06) 2.09) 1.49) 1.96)
1.00 0.31 0.51 0.84 0.71 0.66
(0.96 (0.17 (0.31 (0.74 (0.50 (0.32
1.04) 0.58) 0.83) 0.97) 1.03)
1.351
‘Adjusted odds ratios, estimated usrng beta-binomial regression. These ratios represent the relative likelihood that palpitations are more accurate tie, have a higher positive predictive value) in patients with and without each clinical characteristrc or in patients with a one integer increment in the characteristic. (See Statistical Analyses section for futher explanation.) rExcluding simple and social phobias.
TABLE Ill Medical
Characteristics
and Positive Predictive Adjusted Odds Ratio
Clinical Characteristics Duration of palpitations (months) Percent of patients with known cardiac history Medical Care Utilization Previous Holter monitor Previous stress test Number of physician visits, preceding 12 months Number of emergency & walk-in visits, preceding 12 months Days hospitalized, preceding 12 months Number of mental health visits, preceding 12 months
Value* 95% Confidence Interval
1.00 0.94
(0.996 1.003) (0.44 2.02)
1.51 1.53
(0.68 3.34) (0.73 3.18)
1.01
(0.98
1.05)
0.82
(0.66
1.02)
0.80
(0.51
1.26)
0.21
(0.07
0.61)
‘Adjusted odds ratios, estimated usrng beta-binomial regression. These ratios represent the relative likelihood that palpitations are more accurate (ie, have a higher positive predictive value) in patients with and without each clinical characteristic or in patients with a one integer increment in the characteristic. (See Statistical Analyses section for f&her explanation.)
an arrhythmia was not related to the chronicity of the chief complaint or to whether the patient gave a history of previously diagnosed heart disease (Table III). Nor was average positive predictive value related to the clinical significance of the arrhythmia: Patients with ventricular or supraventricular tachycardia, atrial flutter or fibrillation, or bradycardia (n = 28) did not differ significantly from patients with benign arrhythmias in average positive predictive value or in the number of diary symptoms. Accurate awareness of arrhythmias might be expected to be related to medical care use, since more contact with doctors and more diagnostic testing could cause patients to scrutinize themselves more and become hypervigilant about bodily sensations. As shown in Table III, however, average positive predictive value was significantly related only to the number of mental health visits. When we included all the significant predictors of
average positive predictive value in a multiple betabinomial regression model, the only statistically significant predictor of average positive predictive value was the patients’ somatization score (odds ratio = 0.41; 95% confidence interval (CI) 0.19 to 0.90). When the number of cardiac events was added to the model, the somatization score was still significant (odds ratio = 0.41; 95% CI 0.18 to 0.96).
Correspondence Between and Type of Arrhythmia
Type of Symptom
Does the descriptive term chosen by the patient to characterize the palpitation correspond to the type of arrhythmia that occasioned it? As shown in Table IV, when associated with an arrhythmia, the sensation of the heart stopping always followed a ventricular premature contraction (although there were only 19 such reports). Eighty-five percent of the accurate reports of “jumping” and “pounding” followed ventricular pre-
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mature contractions. In contrast, the complaints of “irregular heartbeat” and “fluttering” were less predictive: Approximately half of these reports, when accurate, resulted from ventricular premature contractions, and approximately half of them followed atrial premature contractions. The descriptor used did not correspond in a literal fashion to the type of arrhythmia that caused it. Thus, “stopping” never coincided with bradycardia or a prolonged pause, and “racing” was never associated with tachycardia.
tom characterizations vary in the likelihood that they reflect an underlying arrhythmia: “stopping,” “fluttering,” and “irregular heartbeat” have higher average positive predictive values than do “racing” or “pounding.” Thus, for example, 19 of 20 patient reports of “heart stopping” followed an electrocardiographic irregularity, whereas only 22 of the 105 reports of Yacing” heart were accompanied by an abnormality. The likelihood that a symptom report was preceded by an arrhythmia was inversely related to self-reported measures of somatization and hypochondriaAverage Sensitivity sis (disease fear, unwarranted disease conviction, and Palpitations are extremely insensitive indicators of bodily preoccupation). Somatizing and hypochondriarrhythmias; there is a very low likelihood that any acal patients might be expected to be more sensitive given arrhythmia will be noticed and reported as a and more astute interoceptors who notice benign symptom. Of the 145 patients, 7 had no cardiac events bodily dysfunctions, mild self-limited infirmities, and during the monitoring period and data were missing normal physiologic functions to which other people on this variable for 1 subject. Of the remaining 137 are insensitive or fail to discern. That would imply patients, 87 (64%) detected none of their arrhythmias that somatizers could make finer visceral discriminaat all. Only 8 detected more than 10% of the events tions and could detect more subtle cardiac irregularthat occurred, and only 26 detected more than 1%. ities. Our findings suggest, however, that this is not Even the patients with the highest average positive the case and instead imply that somatizing and predictive values were very insensitive and failed to hypochondriacal concerns are better understood as note the vast majority of their arrhythmias. Only 6 of a general response bias toward the expression of bodthe 30 patients with at least one accurate symptom ily distress, a global proclivity to feel uncomfortable. report had average sensitivities greater than or equal To use a signal detection paradigm, somatizers may to 0.25. In all, 82% of patients with ventricular pre- not be particularly sensitive detectors of weak and inmature contractions and 87% of patients with atrial frequent bodily signals, but rather may be unable to premature contractions had no accurate diary symp- discriminate signals from background noise. tom reports. Among the less common arrhythmias, The inverse relationship between positive predicthere were no accurate symptom reports of atrial fib- tive value and psychiatric disorder is not surprising. rillation, bradycardia, or pauses. An extensive body of research indicates that patients with high levels of psychologic distress and psychiRelationships Among Arrhythmias, Accuracy, atric symptoms report high levels of somatic symptoms as we11.3g-43As Watson and Pennebaker@ have and Sensitivity Average positive predictive value is positively as- observed, physical symptoms and negative moods tosociated with the incidence of arrhythmias, because gether often reflect a pervasive underlying disposition as the number of cardiac events increases the statis- toward experiencing distress and discomfort in gentical probability that any random symptom will coineral. Thus, medical outpatients who are more psycide with an event also increases. As predicted, the chiatrically disturbed would be expected to report total number of arrhythmias in 24 hours was signifimore somatic symptoms in general and more cardiac cantly associated with average positive predictive symptoms (such as palpitations) in particular. In value (r = 0.41; P = 0.0001). Average sensitivity, howmany instances then, Holter diary reporting may be ever, was not significantly related to the number of viewed as one particular manifestation of more genarrhythmias (r = -0.12; P = 0.18). eralized somatic distress and concern. Patients with higher average positive predictive COMMENTS values are also significantly older and have much Although a number of earlier reports suggested lit- more arrhythmic activity. This relationship is partly tle correspondence between arrhythmias and palpia statistical one, as discussed above. But in addition, tations during Holter monitoring,7-gJ2J5J6,37,38this dis- the data suggest the possibility that as a group, accrepancy was not probed or elucidated. In this study, curate reporters have more serious cardiac morbidseveral significant differences emerge between pa- ity. They may be referred for Holter monitoring betients whose symptoms tend to coincide with ar- cause they are sicker and older, and because their rhythmias and patients whose symptoms tend not to. physicians have a higher index of suspicion for carThe former somatize less, are less hypochondriacal, diac disease. The patients with lower positive preand have less psychiatric morbidity. Specific sympdictive values, on the other hand, are younger and 218
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TABLE IV Symptoms and Arrhythmias* % of Symptom Reports Resulting from Premature Ventricular Contractions Accurate reports of racing heart (n = 22) 72.7% Accurate reports of irregular heartbeat In = 125) 48.0% Accurate reports of heart pounding (n = 50) 84.0% Accurate reports of heart fluttering (n = 90) 57.8% Accurate reports of heart jumping (n = 40) 85.7% Accurate reports of heart stopping (n = 19) 100.0% ‘Relationshipof type of symptomto type of arrhythmia.
have less arrhythmic activity. They may represent a different group of patients who are being Holter monitored with a different rationale. In these eases, the electrocardiogram may have been obtained to reassure an unusually worried patient that nothing serious is wrong, or because the patient insisted on it, rather than because significant electrocardiographic findings were anticipated. Does the type of palpitation reported convey any descriptive or diagnostic information about the type of arrhythmia causing it? Reporting that the heart stopped, when indicative of an arrhythmia, always resulted from a premature ventricular contraction. The sensation of the heart “jumping” indicated a premature ventricular contraction 85% of the time that it followed any arrhythmia. But symptoms do not appear to be literal descriptors of the type of arrhythmia that produced them: “Stopping” never reflected a pause or bradycardia, and “racingt) was never accompanied by taehycardia. No term was used significantly more of-. ten to refer to a clinically significant, as opposed to a benign, arrhythmia. From a clinician’s perspective, the likelihood that a symptom coincides with a documented arrhythmia is the most salient aspect of symptom accuracy. But the converse phenomenon, the likelihood that an arrhythmia will become manifest by generating a symptom report, is also of interest. Patients were generally insensitive to arrhythmias, and only a very small fraction of arrhythmias generated symptom reports. It was particularly striking that none of the patients with atria1 fibrillation, who were most subject to arrhythmic activity, reported any palpitations at all. Even patients with high average positive predictive values did not notice the vast majority of their arrhythmias. This study has several limitations. First, some parameters were defined arbitrarily. Thus, to constitute an accurate symptom report, an arrhythmia had to occur within 30 seconds before the symptom; we used 50% as the cutoff for a perceivable change in heart rate, and at least 2 seconds as the duration of
% of Symptom Reports Resulting from Premature Atrial Contractions 18.2% 44.8% 12.0% 38.9% 14.3% 0
% of Symptom Reports Resulting from Atrial Tachycardias 0 4.8% 2.0% 1.1% 0 0
a perceivable pause. Second, caution is necessary in generalizing from this restricted and biased sample to medical outpatient populations in general. Patients referred for Holter monitoring may not be representative of all ambulatory medical patients complaining of palpitations. Indeed, as discussed earlier, the Holter laboratory population is likely to be enriched with patients who are unduly worried about their symptoms and with patients who have more serious arrhythmias. Third, there are conceptual difficulties in this study. A single premature beat is hardly comparable to a prolonged tachycardia, yet we did not take the duration of each arrhythmia into account. Another limitation of our data is more technical, in that it was sometimes impossible to decipher the electrocardiogram preceding a given symptom: Patients failed to activate the event button, it did not work properly, or the tracing was illegible. Finally, our psychiatric evaluation did not include a screen for alcohol and substance abuse, and these are prevalent and important disorders in ambulatory medical populations. More knowledge of the relationship between palpitations and arrhythmias could improve differential diagnosis and symptom palliation. At present, the evaluation and management of the patient complaining of palpitations is often problematical and unsatisfactory. Frequently, the medical evaluation is inconclusive, Holter monitoring is uninformative, and no etiology is established. At that point, nonspecific reassurance is often ineffective, and many palpitation patients remain symptomatic, distressed, and impaired over long periods.44 Even for patients with clinically significant arrhythmias, antiarrhythmic pharmaeotherapy may fail to produce symptom relief since the patients’ symptoms rarely result from their arrhythmias. What clinical implications emerge from this work? First, the practitioner needs to remember that the complaint of palpitations is more likely to reflect an arrhythmia (although not necessarily a clinically serious arrhythmia) in patients who somatize less and
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have fewer hypochondriacal concerns about their health, and in patients who are less psychiatrically disturbed. Somatizing patients-namely, those who report more somatic symptoms without a medical basis-are apparently less able to accurately detect changes in cardiac rhythm and discriminate them from the background sensations of normal cardiac activity. Their palpitations are best viewed in this broader context as only one manifestation of the multiple somatic symptoms they report in many bodily locations. Likewise, the palpitations of patients with more psychiatric disorders may also be thought of as merely one instance of a more general phenomenon, a more global state of physical distress. Focusing on their palpitations to the exclusion of their other functional, somatic symptoms risks missing the forest for the trees; Holter-monitoring such patients may sometimes be like taking roentgenograms of only the interphalangeal joints of a patient with widespread arthritis. That does not necessarily mean, however, that these patients do not need monitoring-somatizing and psychiatric patients have their share of significant heart disease. But this work does suggest monitoring might be delayed until the physician has searched carefully for a psychiatric disorder or a more general pattern of somatization. Treatment of a psychiatric disorder, such as panic disorder or major depression, could then be initiated and Holter monitoring only carried out if psychiatric treatment fails to eliminate the palpitations. Thus our findings do not dictate whether or not monitoring should be performed, but rather suggest a temporal sequencing of diagnostic and therapeutic efforts. In addition, the study implies that more precision is necessary in the task of history-taking. The simple term “palpitations,” as used both by patients and doctors, is too imprecise, ambiguous, and vague. Although our data do not confii a literal correspondence between the patient’s description and the nature of the arrhythmia, we did find that some descriptive terms have higher predictive values than others. Finally, there are implications for the use of physician services and of ambulatory monitoring. Rising concerns about the cost of medical care force us to improve the diagnostic yield of history-taking itself and to develop better criteria for the use of expensive laboratory tests. This problem is particularly accute for somatizing patients, since they are among the greatest users of medical care.45l46The ability to recognize such patients earlier and to diagnose and treat their underlying psychiatric disorders instead of pursuing extensive and fruitless medical evaluation will only become more crucial with the growing need to contain medical costs.
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