Original Paper - Full-length version

Signs and symptoms in diagnosing acute myocardial infarction and acute coronary syndrome: a diagnostic meta-analysis

Rudi Bruyninckx, Bert Aertgeerts, Pieter Bruyninckx and Frank Buntinx
British Journal of General Practice 2008; 58 (547): e1-e8. DOI: https://doi.org/10.3399/bjgp08X277014

Abstract

Background Prompt diagnosis of acute myocardial infarction or acute coronary syndrome is very important.

Aim A systematic review was conducted to determine the accuracy of 10 important signs and symptoms in selected and non-selected patients.

Design of study Diagnostic meta-analysis.

Method Using MEDLINE, CINAHL, EMBASE, tracing references, and by contacting experts, studies were sought out that described one of the 10 signs and symptoms on one or both conditions. Studies were excluded if they were not based on original data. Validity was assessed using QUADAS and all data were pooled using a random effects model.

Results Sixteen of the 28 included studies were about patients who were non-selected. In this group, absence of chest-wall tenderness on palpation had a pooled sensitivity of 92% (95% confidence interval [CI] = 86 to 96) for acute myocardial infarction and 94% (95% CI = 91 to 96) for acute coronary syndrome. Oppressive pain followed with a pooled sensitivity of 60% (95% CI = 55 to 66) for acute myocardial infarction. Sweating had the highest pooled positive likelihood ratio (LR+), namely 2.92 (95% CI = 1.97 to 4.23) for acute myocardial infarction. The other pooled LR+ fluctuated between 1.05 and 1.49. Negative LRs (LR−) varied between 0.98 and 0.23. Absence of chest-wall tenderness on palpation had a LR− of 0.23 (95% CI = 0.18 to 0.29).

Conclusions Based on this meta-analysis it was not possible to define an important role for signs and symptoms in the diagnosis of acute myocardial infarction or acute coronary syndrome. Only chest-wall tenderness on palpation largely ruled out acute myocardial infarction or acute coronary syndrome in low-prevalence settings.

INTRODUCTION

‘Chest pain’ is a symptom of illnesses of different organs (heart, lung, stomach and intestines, muscles, and skeleton) or of psychiatric disorders, all of which require specific treatment. Due to the high mortality and morbidity of coronary disease, in the event of chest pain, a GP will always consider the possibility of an acute myocardial infarction or unstable angina. Moreover, fast treatment — such as thrombolysis, percutaneous coronary intervention, or coronary artery bypass graft — can be life-saving and increase the patient's life expectancy and quality of life.1

The annual incidence of acute myocardial infarction for persons aged 30–69 years is estimated by the British Heart Foundation at 0.6% for men and at 0.1% for women.2 In Belgium the figures are comparable: in the 45–75-year-old age group Bartholomeeussen et al3 found a yearly incidence of acute myocardial infarction of 0.55% for men and 0.19% for women. The incidence of severe heart disease in people complaining of chest pain is highly dependent on the care setting: for Belgium percentages vary between 4.8% when a GP is contacted and 24.2% for patients in the emergency department of a university teaching hospital.4

Severe prolonged chest pain of acute onset is rarely a decision-making problem. Attacks of chest pain that are experienced by the patient and defined as not very severe or prolonged, but distressing enough for them to contact a GP, present a more difficult problem in diagnosis and management.5 In the majority of European countries GPs will perform most of the triage in patients with chest pain and so can only rely on signs and symptoms. The accuracy of these signs and symptoms has already been the subject of systematic reviews. Several authors only used groups consisting of patients with known acute myocardial infarctions in their reviews;6–8 such studies can only determine the sensitivity. The specificity, the positive or negative likelihood ratio (LR+, LR−), the positive predictive value (PPV), and the negative predictive value (NPV) cannot be determined using such samples. Consequently, the accuracy of a test cannot be described fully.

Panju et al only used studies concerning patients included via an emergency department or patients admitted to a hospital.9 Mant et al only used articles dated before 1992 in their review on signs and symptoms,10 while Chun and McGee only used MEDLINE for their search strategy.11 More recent studies were included in this systematic review. Two analyses were made: one of studies of patients who were non-selected (recruited by GPs, paramedics, or emergency departments) and one of studies of patients who were selected (recruited by coronary care units and cardiologists).

Ten signs and symptoms that could be found by history taking or physical examination were investigated. The diagnostic value was examined for acute myocardial infarction or acute coronary syndrome of:

  • radiating pain (left arm and/or shoulder, right arm and/or shoulder, both arms and/or shoulder, neck, back, epigastric);

  • oppressive pain;

  • nausea and/or vomiting;

  • sweating; and

  • absence of chest-wall tenderness on palpation (absence of tenderness).

METHOD

Search strategy

MEDLINE, EMBASE and CINAHL were searched. All searches were up to date as of 31 May 2006. In MEDLINE a combination of terms was used involving all possible elements, the target disease and no filters: (“Physicians, Family”[MeSH] OR “Emergency Service, Hospital”[MeSH] OR “Emergency Medical Services”[MeSH] OR “Emergency Medicine”[MeSH]) AND (“Chest Pain”[MeSH] OR “Myocardial Ischemia”[MeSH]).

How this fits in

Most information about signs and symptoms is derived from studies in coronary care units with patients who have 100% acute myocardial infarction. Those data are not similarly accurate in a primary care setting (GP surgery, emergency department, and paramedics). This study was not able to define an important role for signs and symptoms in the diagnosis of acute myocardial infarction or acute coronary syndrome. Only chest-wall tenderness on palpation largely ruled out acute myocardial infarction or acute coronary syndrome in low-prevalence settings.

An adapted version of this search string was used in CINAHL: ((Emergency-Medicine) OR (Emergency-Service) OR (Physicians-Emergency) OR (Emergencies) OR (Emergency-Care) OR (Emergency-Medical-Services) OR (Physicians-Family) OR (Prehospital-Care)) AND ((Angina-Pectoris) OR (Chest-Pain) OR (Myocardial-Infarction) OR (Myocardial-Ischemia)).

The search string used in EMBASE was: (‘emergency health service’ OR ‘general practitioner’ OR ‘emergency health service’ OR ‘emergency ward’ OR ‘emergency medicine’) AND (‘thorax pain’ OR ‘heart muscle ischemia’)

In addition, the reference lists of the retrieved articles were checked. A search for any unpublished study results was limited to contacting known researchers in the field.

Study selection

The study strategy was designed to include all published diagnostic accuracy studies on signs and symptoms for the diagnosis of acute myocardial infarction, unstable angina, or acute coronary syndrome. Studies were excluded if diagnostic tests were not one of the 10 selected signs or symptoms and if they were not based on original data or if the data were insufficient to construct a 2×2 table. Language restrictions were English, French, German, and Dutch. Two independent reviewers screened the titles; a third reviewer resolved any disagreements that occurred between the two. All the selected titles were studied in full text by one reviewer. A list of excluded studies and a log of reasons for exclusion are available from the authors on request. When patients were recruited by GPs, paramedics, or emergency departments, they were considered ‘non-selected’. Patients recruited by coronary care units and cardiologists were considered ‘selected’.

Chosen articles were retrieved in full and further included in the review after they had been assessed for quality using the QUADAS instrument, shown in Appendix 1.12 The selection of participants and the validity of the reference standard were the most important considerations. Studies were excluded from the review if they failed on one of these two items. Studies that failed on other QUADAS questions were not excluded, not even those without blind interpretation of the other tests, as blinding is almost impossible in this case.

Data extraction

The following data were extracted (in duplicate) from the studies:

  • the design: whether the data were collected prospectively or retrospectively, and whether the participants were included consecutively;

  • the setting: whether participants were recruited by GPs, cardiologists, paramedics, emergency departments, chest pain observation units, or coronary care units;

  • age and sex;

  • index test: pain radiating to left arm and/or shoulder; to right arm and/or shoulder; to both arms and/or shoulders; to neck; to back; epigastric, oppressive pain; nausea and/or vomiting; sweating; absence of tenderness;

  • the number of patients and the prevalence of the disease in the study group;

  • the results from the study in absolute numbers (in the absence of the absolute numbers, they were calculated from prevalence, sensitivity and specificity);

  • the inclusion and exclusion criteria; and

  • the reference standard.

Statistical analysis and data synthesis

Two groups were analysed separately: the patients who were non-selected and those who were selected. Standard methods recommended for the meta-analysis of diagnostic test evaluations were used.13–15 Analyses were performed using Stata (version 8, Stata Corporation, Texas). Sensitivity, specificity, LR+ (= sensitivity/[1 — specificity]; a positive test result makes the odds of the disease ‘LR+’ times more possible), LR− (= [1 — sensitivity]/specificity; a negative test result makes the odds of the disease ‘LR−’ times less possible) and the odds ratio (OR) were pooled using a random effects model. PPV or NPV were not reported because of the heterogeneity between studies due to differences in setting and prevalence.

Heterogeneity in meta-analysis refers to the degree of variability in results across studies. Forest plots were examined and used, the χ2 and Fisher's Exact tests were used and, in view of the low power of the χ2 test, the I2 statistic was also estimated to detect heterogeneity.16 In order to keep the tables readable, only the I2 data are reported. The potential presence of publication bias using funnel plots and the Egger test was tested for.17–18

RESULTS

Included studies

Figure 1 outlines the study selection process. The great majority of publications concerning acute myocardial infarction and acute coronary syndrome discuss the technical tests and treatments. The number of studies found reporting the selected signs and symptoms was not very extensive — there were 57 in all. A further 29 were excluded because only patients with confirmed acute myocardial infarctions or acute coronary syndromes were included. Twenty-eight articles were included in the meta-analysis:19–46 16 studies were about patients who were non-selected, 11 studies were about patients who were selected, and one study was made in a chest pain observation unit.

Figure 1
Figure 1

Retrieval of eligible studies: flowchart.

Study characteristics and quality

During the selection process the inter-rater agreement between the two reviewers was very good with a κ of 0.82 (95% confidence interval [CI] = 0.79 to 0.85). There was no disagreement in items of the QUADAS instrument. The results of the studies included on the QUADAS list are outlined in Appendix 2. In an attempt to analyse subgroups for sex and age, 14 authors were contacted by e-mail and additional data were obtained for two studies. Appendices 3 and 4 present the descriptive data from the studies included.

For the final diagnosis of acute myocardial infarction the reference tests used were enzyme rises (n = 23), electrocardiogram (ECG) change (n = 22), history (n = 11), scintigraphy (n = 8), autopsy (n = 5), criteria of the World Health Organization or European Society of Cardiology (n = 4), sudden death (n = 3), coronary angiogram (n = 2), echocardiography (n = 2), or urgent revascularisation (n = 1). In some studies, at least two tests were required. History alone was always insufficient to diagnose an acute myocardial infarction.

Reference tests for unstable angina were: history (pain: frequency, worse, new) (n = 5), ECG changes without enzymes rises (n = 3), unproven acute myocardial infarction (n = 2), Canadian Cardiovascular Society classification criteria (n = 1), and clinical judgement (n = 1).

One study46 gave only reference tests for acute coronary syndrome: troponin rise, cardiac death, acute myocardial infarction, new onset heart failure, life-threatening arrhythmia, or coronary revascularisation.

Prevalence

Two large studies36,37 provided 50% of the subjects. When the results of all the studies were combined, there were 5067 (11.6%) patients with acute myocardial infarction out of a group of 43 138, and 4594 (26.3%) patients with acute coronary syndrome out of a group of 17 416. Of these 17 416, 13 108 (75.3%) belonged to a group also examined for acute myocardial infarction. There are approximately 50% more patients with unstable angina than acute myocardial infarction.

The varying prevalence of acute myocardial infarction depended on the setting and inclusion criteria. Graff et al's37 low prevalence of about 2% was caused by the very large inclusion criteria, that is, ‘all patients with possible acute myocardial infarction for whom a rapid ECG was performed’. The chest pain observation unit, to which patients with unclear signs and symptoms and without clear ECG abnormalities and/or blood abnormalities were admitted, had a prevalence of 4%.40 In other studies executed in emergency departments, prevalences of between 6% and 18% were found. The group transported by ambulance in Svenson et al's study,44 with a prevalence of 29%, situates itself between the patients seen in an emergency department and those admitted to a coronary care unit (prevalence from 36–50%). In the study of Van der Does et al21 the prevalence of referred patients was as low as 7%.

Heterogeneity in the non-selected group

For acute myocardial infarction there was homogeneity in the LR+ of oppressive pain and in the LR− for tenderness. For acute coronary syndrome there was homogeneity in the LR+ of left-arm pain and the LR− for sweating and tenderness. For the other analyses, a moderate to high level of heterogeneity was found.

Indications of diagnostic accuracy in the non-selected group

Appendix 5 (for the diagnosis of acute myocardial infarction) and Appendix 6 (for a diagnosis acute coronary syndrome) (both subgroups separately) show the pooled sensitivity, specificity, LR+, LR−, and OR with their 95% CI and I2. The sensitivity and specificity per sign or symptom varied greatly.

The sensitivity of absence of tenderness was high, namely 92% (95% CI = 85.5 to 96.4) for acute myocardial infarction and 94% (95% CI = 91.4 to 96.1) for acute coronary syndrome. Oppressive pain followed with a sensitivity of 60% (95% CI = 53.7 to 66.0 for acute myocardial infarction). Sweating had the highest LR+, namely 2.92 (95% CI = 1.97 to 4.32 for acute myocardial infarction).

The LR+ of right arm or shoulder pain was 2.89 (95% CI = 1.40 to 5.98) for acute myocardial infarction (one study). The other LR+ fluctuated between 1.05 and 1.49 for acute coronary syndrome.

Absence of tenderness had a LR- of 0.23 (95% CI = 0.18 to 0.29) for acute myocardial infarction and 0.17 (95% CI = 0.11 to 0.26) for acute coronary syndrome. Other LR− varied between 0.69 (oppressive pian and sweating for acute myocardial infarction) and 0.98 (epigastric pain) for acute coronary syndrome.

Publication bias

A funnel plot, signifying publication bias, is shown in Figure 2. The plot appears symmetrical, suggesting absence of publication bias. This was confirmed by a non-significant Egger test (0.79).

Figure 2
Figure 2

Funnel plot for evaluation of publication bias in all studies.

DISCUSSION

Studies included

More than half of the studies dated from after Mant et al's10 selection. Sixteen new articles about several signs and symptoms that were not included in Chun and McGee's review11 were included, indicating the necessity for a new systematic review.

Although the authors aimed to find all relevant studies, some could have been missed. However, the search strategy will have detected most studies. As only two studies were performed in a general practice setting, it was decided to look for ‘primary care’ studies, which were defined as settings in which patients who had not been referred by other medical practitioners were seen. In Europe and some other parts of the world this mostly concerns general practice. In the US and a number of other countries however, this frequently includes the emergency department and patients admitted by paramedics. The information on these unselected patients is certainly relevant for GPs.

Quality

A fair amount of research dates from several decades ago. It could be argued that these older studies are disadvantaged in terms of quality as empirical research on design-related bias and the STARD (Standards for Reporting of Diagnostic Accuracy) initiative to improve quality are fairly recent.47–49 Although new research on the quality of diagnostic accuracy studies confirms that quality is still not optimal, the quality of the studies included was good according to the QUADAS criteria.

A good reference test is essential in diagnostic research. It was unclear how frequently these criteria were used for the definite diagnosis of acute myocardial infarction. The acceptance of a broad range of inclusion criteria (autopsy, sudden death, scintigraphy, echocardiography, and angiography) as reference tests increased the number of real positives at the risk of spectrum bias.10 Verification bias was not a major problem because almost all patients received a reference standard. The increasing sensitivity of the blood tests used over the years — starting with transaminase via lactate dehydrogenase, creatine kinase (CK) and the isoenzyme CK-MB, and recently troponin T — has caused a rise in real positives. However, no increase in the prevalence of acute myocardial infarction in the emergency departments or the coronary care units was noticed over the course of time. The reference test for unstable angina was not as clearly defined as that for acute myocardial infarction because it often depended on the clinical picture and its interpretation. All of this could cause either over- or underestimation of the prevalence found.

Although ‘acute myocardial infarction + unstable angina = acute coronary syndrome’, a distinction was made between acute myocardial infarction and acute coronary syndrome to ensure that no data was left out of those studies that dealt only with acute myocardial infarction.

Prevalences

In 2000, the definition of acute myocardial infarction changed to: ‘typical rise and gradual fall of cardiac troponin, or more rapid fall of CK-MB, with at least one of the following: ischemic symptoms; the development of pathological Q waves; ECG changes indicative of ischemia (ST-segment elevation or depression); coronary artery intervention’.50 This definition of acute myocardial infarction will increase the sensitivity of diagnosing acute myocardial infarction and thereby increase the findings of its incidence. The increased specificity of troponin, however, should decrease the number of false-positive diagnoses. The combined effect that these two factors may have on the case-fatality rate is currently unclear.51

The larger number of acute myocardial infarctions in patients transported by ambulance compared to those in patients transported to the emergency department by other means has been documented previously.4 The low prevalence of referred patients in the study by van der Does et al21 is possibly explained by the underestimation of the number of acute myocardial infarctions due to the absence of sensitive blood analyses in 1972.

It should also be noted that in most studies the true population prevalence of acute myocardial infarction was higher because patients who died at home could not be included.

Heterogeneity

Most of the pooled results were heterogeneous, due to different settings, inclusion criteria, and reference standards. The non-homogenous pooled results must be interpreted very carefully.

Diagnostic accuracy of signs and symptoms in the non-selected patients group

Absence of tenderness was highly sensitive for acute myocardial infarction (92%) and acute coronary syndrome (94%). The presence of palpation pain greatly reduces the chance of acute myocardial infarction and acute coronary syndrome with a LR− of 0.23 and 0.17 respectively. Similar pleuretic or positional thoracic pain was not selected in this study. In Mant's et al's study the absence of pleuretic pain had a LR− of 0.19 and the absence of positional pain a LR− of 0.27.10 Oppressive pain, with a pooled sensitivity of 60% and a specificity of 58% has almost no influence on the likelihood of acute myocardial infarction. The sensitivities of the other signs and symptoms were even lower and could not be used to exclude acute myocardial infarction or acute coronary syndrome. The differences in sensitivity and specificity between acute myocardial infarction and acute coronary syndrome remained small and were therefore not relevant.

It is true that, even in unselected settings such as general practice, patients have a reason for visiting their GP with chest pain. Fear of having a myocardial infarction may be one such reason. Anyone not visiting their doctor will not be diagnosed with acute myocardial infarction so the classical signs and symptoms of chest pain and irradiation are always part of the diagnostic work-up.

Clinical implications

To summarise the interpretation of signs and symptoms in the clinical context, consider a patient in a low-, intermediate-, and high-prevalence setting. For the sake of clarity the highest pooled LR+ and the lowest LR− found for acute myocardial infarction, namely sweating (LR+ 2.92, LR− 0.69), and absence of chest-wall tenderness (LR+ 1.47, LR− 0.23) were used.

In a low pre-test probability situation of 5%, which may be regarded as the prevalence in those patients who are unselected and contact a GP with chest pain, these LR+ translate to a 13% and 7% post-test probability of a positive test result.4 In low pre-test settings the presence of the signs and symptoms listed above is insufficient to definitively confirm acute myocardial infarction. In their absence the post-test probability is lowered to 4% and 1%. Absence of sweating should scarcely affect GPs' management; the presence of chest-wall tenderness results in a post-test probability of 1.1% and so largely rules out acute myocardial infarction for clinical purposes.

In an intermediate-prevalence setting of 15%, which is the prevalence expected in a patient seen by the GP during an urgent home visit or in an emergency department, the same reasoning produces a post-test probability of 34% and 21%. If these symptoms are absent this becomes 11% and 4%. These results should barely influence GPs' treatment strategy.

In a high-prevalence setting of 40%, such as a coronary care unit the same signs or symptoms represent a post-test probability of 66% and 49% if positive, and 32% and 13% if negative. These results will also add nothing to the diagnostic process.

Each of these signs and symptoms may also trigger consideration of acute myocardial infarction or acute coronary syndrome: non-specific complaints such as back pain or vomiting/nausea can also be caused by acute myocardial infarction or acute coronary syndrome. In Goodacre et al's45 study of patients with undifferentiated chest pain (with normal ECG and without a clear clinical diagnosis of acute coronary syndrome) the final diagnosis was acute coronary syndrome in 7.9%. This group of missed acute coronary syndrome probably still has a higher mortality than patients without acute coronary syndrome.52

Previous meta-analyses of signs and symptoms

All the pooled results were situated within the 95% CIs of the previous investigations, except in the absence of chest-wall tenderness. Here a LR+ of 1.47 (95% CI = 1.23 to 1.75) was found, which was somewhat higher than in Mant et al's10 research (1.18; 95% CI = 1.16 to 1.22).

Limitations of the review

Some studies suggested a difference in the diagnostic accuracy of signs and symptoms according to age27,38 or sex,43 but there were not enough studies to perform a subgroup analysis. Although the combination of signs and symptoms, their context, the severity, and the progression from the start influence the interpretation, it was impossible to examine this because there were almost no included studies that investigated the diagnostic accuracy of combinations of signs and symptoms. Only three of the selected studies combined different signs and symptoms: Short22 (previous or not-previous history of acute coronary syndrome and studied signs and symptoms), Lee et al23 (sharp or stabbing pain and pain pleuretic, positional or reproduced by palpation and no prior acute coronary syndrome), and Hargarten et al25 (radiating pain and sweating, difficult breathing, and nausea/vomiting).

Persons with chest pain can also be subject to serious, even life-threatening, diseases other than acute myocardial infarction or acute coronary syndrome, such as pulmonary embolism, and stomach bleeding. This requires analysis with CART-type models in the individual studies. CART is a statistical package that produces decision trees using variables (coded signs and symptoms) directing to classes (diagnostic categories). At each node of the decision tree, the programme calculates which variable is the ‘most discriminating’ and constructs, at that node, a bifurcation of two branches. For each resulting branch, CART calculates the next most discriminating variable and continues in this way until either the subgroups or the discriminating power become ‘too small’. A final statistical pruning technique results in an optimal tree, where optimality is measured by various criteria.53–55 As far as the authors know no systematic review has been published pooling the results of such studies.

In 2005 a new multilevel method for the bivariate pooling of combined sensitivity and specificity was published.56 This method may be superior to classic pooling. The authors were asked to do the calculations on the current study's results of the absence of chest-wall tenderness on palpation in relation to acute myocardial infarction. Because of the minimal differences, the previous calculations were not reworked.

Conclusions

Based on this meta-analysis, it was not possible to define an important role for signs and symptoms in the diagnosis of acute myocardial infarction or acute coronary syndrome. Only chest-wall tenderness on palpation largely ruled out acute myocardial infarction or acute coronary syndrome in low-prevalence settings.

Acknowledgments

We are grateful to the authors of the primary studies who sent additional data as well as Dr Johannes Reitsma for doing the bivariate analysis of combined sensitivity and specificity

Appendices

View this table:
Appendix 1

The QUADAS tool.12

View this table:
Appendix 2

Qualification of the articles with the QUADAS tool.

View this table:
Appendix 3

Characteristics of acute myocardial infarction (AMI) included studies.

View this table:
Appendix 4

Characteristics of acute coronary syndrome = acute myocardial infarction + unstable angina included studies.

View this table:
Appendix 5

Pooled sensitivity, specificity, positive and negative likelihood ratios, odds ratios of signs and symptoms for acute myocardial infarction in patient groups.

View this table:
Appendix 6

Pooled sensitivity, specificity, positive and negative likelihood ratios, odds ratios of signs and symptoms for acute coronary syndrome in patients groups.

Notes

Competing interests

The authors have stated that there are none

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  • Received June 22, 2007.
  • Revision received August 9, 2007.
  • Accepted November 19, 2007.

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British Journal of General Practice: 58 (547)
British Journal of General Practice
Vol. 58, Issue 547
February 2008
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Signs and symptoms in diagnosing acute myocardial infarction and acute coronary syndrome: a diagnostic meta-analysis
Rudi Bruyninckx, Bert Aertgeerts, Pieter Bruyninckx, Frank Buntinx
British Journal of General Practice 2008; 58 (547): e1-e8. DOI: 10.3399/bjgp08X277014
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British Journal of General Practice