Family Practice Vol. 18, No. 4, 383-392
© Oxford University Press 2001
New-onset palpitations in general practice: assessing the discriminant value of items within the clinical history
Winterton Medical Practice, The Surgery, Manlake Avenue, Winterton, Scunthorpe DN15 9TA, UK.
Summerton N, Mann S, Rigby A, Petkar S and Dhawan J. New-onset palpitations in general practice: assessing the discriminant value of items within the clinical history. Family Practice 2001; 18: 383–392.
Received 13 June 2000; Revised 28 November 2000; Accepted 12 March 2001.
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Abstract |
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Background. Palpitations are non-specific, with less than half of patients experiencing palpitations having a cardiac arrhythmia. Currently it seems that there is little evidence available to assist GPs in discriminating between patients complaining of palpitations who have significant cardiac arrhythmias and those who do not.
Objectives. Our aim was to estimate discriminant functions for specific items of clinical information in relation to the categorization of a patient (aged over 18 years) with a symptom of new-onset palpitations presenting to primary care.
Methods. A network of 62 GPs spread amongst 36 practices agreed to recruit patients with new-onset palpitations over the course of a 9-month study period. Patients consenting to be involved in the study were asked a number of questions, focusing particularly on the medical history, and were requested to complete a Hospital Anxiety and Depression Scale. Each patient was also provided with a RhythmCard cardiac event recorder for up to 2 weeks and was asked to record their heart rhythm if they experienced palpitations. Odds ratios (adjusted for age and sex) were used to compare the clinical information obtained from patients with the final diagnosis.
Results. Of the 139 patients with palpitations presenting to GPs, it would appear that males [odds ratio = 2.1 (1.0–4.5)], those with regular palpitations [odds ratio = 2.5 (1.0–5.8)], those experiencing palpitations at work [odds ratio = 3.0 (1.3–7.2)] and those experiencing palpitations affected by sleeping (odds ratio = 3.3 (1.4–7.7)] were more likely to have a cardiac cause for their palpitations. Similar findings were made in an analysis focusing solely on the 81 patients with a RhythmCard result. Furthermore, amongst this group, it is interesting to note that patients with regular palpitations were more than twice as likely to have a ‘significant’ cardiac arrhythmia as a cause for their palpitations. There were suggestions of dose–response effects between the rate of the palpitation, the duration of the palpitation and the likelihood of it being a ‘significant’ arrhythmia.
Conclusions. This study provides some information on the characteristics of patients reporting palpitations to GPs who may have ‘significant’ cardiac arrhythmias. Based on this work, we believe that a larger community-based study would be worthwhile and would provide useful and useable clinical discriminant information for GPs in the settings where they work and amongst the types of patients they encounter.
Keywords. Arrhythmia, diagnosis, family practice, palpitations, medical history taking.
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Introduction |
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Palpitations are non-specific and represent one of the most common symptoms in general medical settings, reported by as many as 16% of patients.1 It can be estimated that a GP with an average list size of 2000 patients will see about six patients with new-onset palpitations per year.2
In most cases, palpitations are not associated with structural heart disease. They may be provoked by a host of factors including exercise, emotional stress, fever, caffeine, nicotine and alcohol. Situations in which awareness of the heartbeat may lead an individual to seek medical attention include hyperthyroidism, anaemia and sick sinus syndrome. Other causes of palpitations are panic attacks, depression and somatization disorders.3 In a recent study of secondary care patients in New York State, the aetiology of the palpitations was stated to be cardiac in 43% and psychiatric in 31%.4
Currently, it seems that it is mainly clinical experience combined with information derived from studies within referred populations that guides GPs in determining what action to take when confronted by a patient with new-onset palpitations. Despite an extensive literature search of MEDLINE (1966–1999) using free text and MeSH terms combined with a hand search of key primary care-orientated journals over the last 2 years, we have been able to identify only one study that describes the usefulness of either specific items or clusters of items of clinical information in the evaluation of new-onset palpitations within primary care.5 Unfortunately, in applying the results from this paper into routine general practice, difficulties are encountered in relation to the patient inclusion criteria. The authors involved not only patients consulting their GP with palpitations but also patients with dyspnoea, faintness, angina, fatigue, collapse and "other complaints . . . if the GP considered an arrhythmia as a possible cause of the complaints". In addition, patients also had to present a diagnostic problem for the GP who they were consulting. Concerns must also be expressed about the validity of the gold standard (a usual ECG recording) used by Zwietering et al. because of the paroxysmal nature of some arrhythmias. Even supplementing this by asking certain patients to return for a further ECG recording during symptoms is clearly open to bias due to time constraints affecting both the participating GPs and the patients. All this detail is important because, in making any decisions based on probabilities, especially in low prevalence populations, it is essential to be certain of the adequacy of the diagnostic knowledge base. If the internal or external validity is dubious, the information may become inapplicable in relation to the amount of risk GPs are willing to accommodate.
In the current study, we have sought to restrict our recruitment to patients clearly describing palpitations in accordance with an explicit case definition. In addition, we have elected to use a transtelephonic post-event recorder (RhythmCard) as the gold standard. These hand-held credit card-sized devices are given to patients and are applied to the chest when symptoms occur. The patient presses a button to record ~30 seconds of the cardiac rhythm, which is stored in the memory of the device. The recording is transmitted later over the telephone for printing and interpretation.
Both the published evidence and unpublished information from the manufacturers indicate that the RhythmCard is a valid and reliable assessment of the likelihood of the patient having a significant cardiac arrhythmia.6 According to Kinley et al., in a small randomized controlled trial, cardiac event recorders were demonstrated to yield more diagnoses than 48-h Holter monitoring in patients with palpitations.7 If patients are provided with a RhythmCard for 2 weeks, it will detect 94% of clinically relevant arrhythmias; a further 2 weeks will pick up an additional 3%.
Using the RhythmCard as the gold standard, the purpose of the present study was to seek to estimate the discriminant functions for specific items of clinical information in relation to the categorization of a patient (aged over 18 years) with a symptom of new-onset palpitations presenting to primary care. The classification was dichotomous (cardiac versus non-cardiac) to reflect the realities of general practice decision making. Furthermore, cardiac diagnoses were divided into ‘significant’ arrythmias and ‘insignificant’ arrhythmias.
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Methods |
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As a result of a positive response to a postal invitation, a network of 62 GPs spread amongst 36 practices within Yorkshire, Lincolnshire, Leicestershire, Cumbria and County Durham agreed to recruit patients with new-onset palpitations over the course of a 9-month study period. Palpitations were defined as one or more of the following complaints: fast heartbeats, skipped heart beats, irregular heart rate and heart fluttering, racing or pounding. Any patient remarking on one or more of these complaints during the course of any consultation with a GP participating in the study was eligible for inclusion.
In order to be included, the patient's symptoms had to have occurred within 3 months preceding the visit to the GP. The following were ineligible: those under the age of 18 years, patients with fever >39°C, patients with aphasia or dementia, and pregnant women. Patients who had a history of previous episodes of palpitations were also excluded.
Patients consenting to be involved in the study were asked a number of questions, focusing particularly on the medical history, and were requested to complete a Hospital Anxiety and Depression Scale.8 These forms were then sent to a research co-ordinating centre at Winterton where it was arranged for a RhythmCard to be despatched to every patient. In addition, the information from the forms was entered onto an SPSS computerized research database at Winterton.
Each patient was provided with a RhythmCard for up to 2 weeks and asked to use it to record their heart rhythm if they experienced palpitations. The RhythmCard had a capacity to store up to three 30-seconds readings and, at the end of the recording period, any recordings were transmitted to CardioAnalytics Ltd. Here the recording was printed out and interpreted by a CardioAnalytics technician. An independent and separate interpretation was also provided by SP under the supervision of JD. The results from the RhythmCards were then classified by NS and SP as ‘normal‘, ‘significant cardiac arrhythmia’ or ‘insignificant cardiac arrhythmia’. A ‘significant cardiac arrhythmia’ constituted one of the following: ventricular tachycardia (including torsade de pointes), paroxysmal supraventricular tachycardia, atrial fibrillation (including paroxysmal atrial fibrillation), atrial flutter, atrial tachycardia, junctional tachycardia or ventricular ectopics occurring in salvoes, in couplets or having a multifocal origin. Such diagnoses warranted further investigation. ‘Insignificant cardiac arrhythmias’ encompassed patients with non-pathological ventricular ectopics (e.g. sporadic, occasional unifocal ectopics), sinus tachycardia and atrial ectopics.
Five randomly selected practices were approached on completion of the study with a request to check their computerized records in order to assess the degree of selection bias in relation to the recruitment of patients into the study.
The data were analysed by calculating odds ratios using the GLIM statistical package,9 odds ratios being used as an approximation to the true relative risk.10 The 95% confidence intervals were calculated according to the methods outlined in Morris and Gardner.11
Three comparisons were made: (i) normal RhythmCard results/no RhythmCard results compared with RhythmCard results indicating a ‘cardiac’ diagnosis; (ii) normal RhythmCard results compared with RhythmCard results indicating a ‘cardiac’ diagnosis; and (iii) normal/ ‘insignificant’ arrhythmias on RhythmCards compared with ‘significant’ arrhythmias on RhythmCards.
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Results |
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Demographic details: patients
There were 139 patients of whom 93 (67%) were female: the mean (median) age of all patients was 46.4 (45) years with a range of 19–77 years.
There were 58 patients with no RhythmCard result; 39 with a RhythmCard result had a normal (‘non-cardiac’ diagnosis). Of the 42 patients with a RhythmCard-generated ‘cardiac’ diagnosis, 16 warranted no further action (‘insignificant’ arrythmias) while 26 patients had ‘significant’ arrhythmias.
Demographic details: patients and practices
Amongst the 36 participating practices, the mean number of partners was 4.7 and the mean number of patients 9880. One-third of practices were predominantly rural, one-third urban and the remainder mixed.
Seventy-nine per cent of the participating GPs were male, 66% were members of the Royal College of General Practitioners and the mean age was 43.5 years.
Selection bias
By checking against their computerized records, the five randomly selected practices were able to provide reassurance that selection bias did not occur in relation to their recruitment.
Statistical analysis
The detailed comparisons are presented in Tables 1–8
. Odds ratios are adjusted for age and sex.
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Discussion |
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Within this study, we have made a number of interesting findings. Amongst all the 139 patients with palpitations presenting to GPs, it would appear that males [odds ratio = 2.1, 95% confidence interval (CI) 1.0–4.5], those with regular palpitations (odds ratio = 2.5, 95% CI 1.0–5.8), those experiencing palpitations at work (odds ratio = 3.0, 95% CI 1.3–7.2) and those experiencing palpitations affected by sleeping (odds ratio = 3.3, 95% CI 1.4–7.7) were significantly more likely to have a cardiac cause for their palpitations. Although many of the other associations are non-significant in a strict statistical sense, it would appear that treatment with a ß-blocker, diuretic, angiotensin-converting enzyme (ACE) inhibitor or an anti-hypertensive was correlated with an increased risk of cardiac arrhythmia. The use of antidepressants/benzodiazepines was associated with a decreased risk of cardiac arrhythmia. There also appeared to be a dose–response effect with duration; the longer the duration of the palpitation the more likely an arrhythmia.
Unfortunately, a RhythmCard result was not available for 58 patients, as these patients did not, apparently, experience an arrhythmia during the time in which they had the RhythmCard. The first-level analysis assumes that these 58 patients' palpitations were non-cardiac. However, in order to avoid either verification bias or misclassification bias, it is important to repeat the analysis only on those patients with definite gold standard results. Amongst the 81 patients with a RhythmCard result, 41 subsequently were classified as ‘cardiac’. In a second-level analysis, odds ratios >1.9 were again identified amongst males, those with regular palpitations, those experiencing palpitations at work and those experiencing palpitations affected by sleeping. However, in view of the small numbers, the confidence intervals are broad and only the ‘palpitations at work’ reached significance at the 5% level.
For the GP, the bottom line is not whether the patient has an arrhythmia but rather whether the arrhythmia matters. Hence, a third-level analysis seeks to compare patients with normal/‘insignificant’ cardiac arrhythmias on a RhythmCard with those with ‘significant' cardiac arrhythmias requiring further investigation or treatment. Amongst the 81 patients with a RhythmCard result, 26 were classified as having ‘significant’ cardiac arrhythmias. Although only one of the numerical associations identified reached statistical significance (palpitations affected by sleeping), it is interesting to note that patients with regular palpitations were more than twice as likely to have a ‘significant’ cardiac arrhythmia as a cause for their palpitations. There were also suggestions of dose– response effects between the rate of the palpitation, the duration of the palpitation and the likelihood of it being a ‘significant’ cardiac arrhythmia.
In considering the broader applicability of the results, it is reassuring to note that the characteristics of the 36 participating practices were comparable with the national picture in terms of numbers of partners, patient list size and urban/rural classification.12 The 62 participating GPs were also similar to their peers as judged by their average age, but contained a higher proportion of men and MRCGP holders than the national average.
Unfortunately, some concerns must be raised that the patients recruited into this study were not typical of all general practice patients presenting with palpitations. GPs may selectively enlist those with intermediate probabilities of illness or those without significant co-morbidities, thereby altering the spectrum of patients being examined. However, by checking against their computerized records, five practices were able to provide reassurance that selection bias did not occur in relation to their recruitment. In addition, there does seem to be some consistency between our results and those of others5 in terms of the proportion of palpitation patients within primary care (one-third) exhibiting cardiac arrhythmias. However, if a GP with an average list size of 2000 patients would expect to see six patients with palpitations per year, we should have expected the 62 GPs involved in the study over a 9-month period to have recruited 279 patients and yet only 139 were entered into the study (with 81 of these providing a RhythmCard recording).
Based on our work, we now feel able to suggest a more focused examination of some specific discriminators within the history, i.e. patient sex, regularity of palpitations, rate and duration of palpitations, and whether palpitations occur at work or were affected by sleeping. However, we do not believe that our study is sufficiently powerful or free of bias in order to encourage the use of these discriminators within routine clinical practice at present. A larger study would need to address selection bias more formally and also to assess both the reliability13 and the validity of the suggested discriminators.
One approach to the problem of selection is to consent a random proportion of patients to be re-interviewed by phone in order to validate the eligibility criteria being applied by the recruiting GPs. Another way is to contact all patients directly: this was the method adopted by Stoffers et al. when they sought to assess the diagnostic value of signs and symptoms associated with peripheral arterial occlusive disease seen in general practice. A list was obtained of all the patients aged 40–75 years registered with 18 GPs in Limburg, The Netherlands. These 26 620 subjects then received a simple postal questionnaire enquiring about ‘leg complaints on walking’ and those reporting in the affirmative were invited to attend for assessment. However, in adopting such an approach, care must be taken to enquire about whether such patients do consult or would consider consulting their GP about such symptoms as we clearly need to understand both the significance of community symptoms as well as identifying those patients that may present to the GP. Clearly some symptoms such as chest pain have a greater ‘iatrotrophic stimulus’15 than, perhaps, palpitations.
Although we have reasonable confidence in the sensitivity of the RhythmCard, it remains possible that some short duration episodes of cardiac arrhythmia might have been missed as it clearly takes time for an individual to respond and to activate the recorder. Therefore, in order to enhance the validity of any larger study, we would propose that a proportion of patients could also undergo continuous loop recording.16 Unfortunately, we have been unable to identify any information on the specificity of the RhythmCard; in particular the number of false positives.
Finally, some statistical issues warrant further examination. In our analysis, we have made a large number of comparisons and it could be argued that some of our results could have come about by chance. However, the need to take account of this and to undertake a Bonferroni adjustment is the subject of much discussion in the literature.17 Perneger contends that adjusting for the perceived problem of multiple comparisons creates more difficulties than it actually solves. For example, Bonferroni methods suggest that all null hypotheses are either true or false simultaneously, and we do not feel that such a general null hypothesis should be applied to our study. Although we could have derived a multiple regression model from our data, it is clear that the numbers are not large enough to produce reliable estimates. However, we can use the information from our study to calculate an appropriate sample size in order to power a larger study. The sample size depends on the background frequency of the risk factor in the ‘no arrhythmia‘ group and the odds ratio to be detected. For example, to show a 2-fold difference between patients with/without significant arrhythmia assuming a background frequency of 27.3% (i.e. 15/55 from Table 3
; palpitations affected by sleeping) would require a total of 420 patients with 90% power and 5% significance (two-tailed). Such a larger study would also provide sufficient power to enable combinations of clinical information to be examined using the statistical techniques advocated by Speigelhalter.18 These clusters may be particularly appropriate within low prevalence primary care populations to assist in rapid problem solving by increasingly busy GPs.19
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Acknowledgments |
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We would like to acknowledge the assistance of CardioAnalytics for supplying the RhythmCards and for interpreting the results. We are also grateful for the advice received from colleagues at 3M Pharmaceuticals, in particular Sue Ellerby and Steve Foster. In re-drafting the paper, we should also like to acknowledge the helpful comments made by the anonymous referee. Funding was provided by 3M Pharmaceuticals (RhythmCards) and NHS Executive (Research and Development, Trent).
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14
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