Are These Patients Having Myocardial Infarctions?
A 57-year-old man presents to the emergency department with squeezing retrosternal pain that started 1 hour ago. He is diaphoretic. His blood pressure is 110/70 mm Hg, his heart rate is 74/min, and he has an audible fourth heart sound. The electrocardiogram (ECG) reveals a 2-mm ST-segment elevation in leads V1 to V4.
A 70-year-old man, with a myocardial infarction (MI) 5 years previously, presents to the emergency department with severe tightness in the neck. The discomfort started 30 minutes ago and was associated with diaphoresis. His blood pressure is 90/60 mm Hg, his heart rate is 50/min, and the ECG reveals Q waves in V1 to V4 (present in the old ECG).
A 50-year-old woman presents to the emergency department with retrosternal burning of 1 hour's duration and nausea. Antacids provided no relief. The findings of the clinical examination were unremarkable. The ECG reveals 3-mm ST-segment elevation in leads II, III, and aVF and 1-mm ST-segment depression in leads I and aVL.
A 40-year-old woman presents to the emergency department with a 24-hour history of left-sided chest pain. The pain is worsened by exertion and movement. Her medical history is unremarkable. The examination reveals normal vital signs and tenderness with palpation of the left lower costal cartilages. An ECG result is normal.
Why Is This an Important Question to Answer With a Clinical Examination?
There have been numerous technologic advancements made in the assessment of patients with symptoms suggestive of acute MI. These include evaluation of time-dependent changes in enzyme levels and biomarkers, as well as an assessment of wall-motion abnormality using echocardiography, radionuclide angiography, or nuclear imaging.
Despite this progress, a carefully conducted history-taking and physical examination remain the first components—and the cornerstones—in the initial assessment of patients presenting with suspected MI. The medical history and physical examination are critical in guiding the selection of further diagnostic and therapeutic interventions. Clinicians complement their clinical examination with a 12-lead ECG and biomarkers, which are additional data that provide the most definitive diagnosis of MI. We will focus on features of medical history, physical examination, and ECG that aid in increasing or decreasing the likelihood of acute MI. We include the ECG in our review because the clinician often interprets the results at the patient's bedside as part of a prompt initial clinical evaluation.
For the purpose of clarification, we begin by describing the 3 diagnostic groupings of patients with acute chest pain currently used by clinicians and then contrast these with the categorization of chest pain as presence or absence of MI, as is evident in the literature. We then briefly describe signs and symptoms of MI, mechanisms of chest pain, and conditions that may present with symptoms suggestive of MI. After these introductory topics, a detailed account of the precision and accuracy of the medical history, physical examination, and ECG in the diagnosis of MI is provided.
Cardiac ischemic chest pain presents in a spectrum of conditions, including angina, unstable angina, and MI. Angina is defined as a discomfort in the chest or adjacent areas, caused by myocardial ischemia, usually brought on by exertion, and associated with a disturbance of myocardial function, but without myocardial necrosis.1 Various grading systems of the severity of angina pectoris have been developed. The classification proposed by the Canadian Cardiovascular Society,2 outlined in Table 35-1, is a practical one adopted in a variety of settings.
Table 35-1Grading of Angina of Effort by the Canadian Cardiovascular Society |Favorite Table|Download (.pdf) Table 35-1 Grading of Angina of Effort by the Canadian Cardiovascular Society
|Grade ||Description |
|I ||“Ordinary physical activity does not cause angina,” such as walking or climbing stairs. Angina with strenuous or rapid or prolonged exertion at work or recreation. |
|II ||“Slight limitation of ordinary activity.” Walking or climbing stairs rapidly, walking uphill, or walking or stair climbing after meals, in cold, in wind, or under emotional stress, or only during the few hours after awakening. Walking more than 2 blocks on the level and climbing more than 1 flight of ordinary stairs at a normal pace and in normal conditions. |
|III ||“Marked limitation of ordinary physical activity.” Walking 1 or 2 blocks on a level surface and climbing 1 flight of stairs in normal conditions and at a normal pace. |
|IV ||“Inability to carry on any physical activity without discomfort—angina syndrome may be present at rest.” |
Unstable angina encompasses a spectrum of symptomatic manifestations of ischemic heart disease intermediate between stable angina and acute MI. According to historical features, ECG findings (with and without pain), and hemodynamic changes (low blood pressure, third heart sound, mitral regurgitation, and pulmonary crackles), guidelines have been developed to stratify patients with suspected unstable angina into high, intermediate, or low risk of complications after initial evaluation.3 These guidelines also recommend disposition based on initial assessment of risk.
The diagnosis of MI used in most studies is based on criteria proposed by the World Health Organization (WHO). In an attempt to standardize the diagnosis of acute MI, the WHO requires evolutionary changes on serially obtained ECG tracings or an increase and decrease in biomarker levels, either with typical ischemic-type chest discomfort and an ECG result that was not normal or with an ECG progression labeled probable and associated with lesser symptoms.4
Diagnosis in Acute Chest Pain
Determining the correct diagnosis is imperative to administering the appropriate therapy. The available therapeutic options create the categories for patients presenting to the emergency department with chest pain or other symptoms suggesting cardiac ischemia. Three distinct management strategies determine the diagnostic groupings clinicians use currently (Figure 35-1).
Diagnostic Groupings of Acute Chest Pain Based on Management Strategies
For the first group of patients, which includes those with MI and ST-segment elevation or left bundle-branch block (LBBB) (Figure 35-1, group A), current therapy consists of early percutaneous coronary interventions or thrombolytic therapy. A second group of patients includes those with MI but without ST-segment elevation or LBBB, or those with high-risk unstable angina (Figure 35-1, group B). These patients require intensive monitoring, immediate administration of antiplatelet agents, and possibly antithrombotic therapy. The third group includes patients with low-risk unstable angina or nonischemic chest pain (Figure 35-1, group C). Clinicians may consider either admitting these patients to an intermediate care setting or ward bed or discharging them home with plans for subsequent diagnostic testing to establish the cause of their symptoms. Economic pressures on the health care system have highlighted the importance of distinguishing the second from the third group of patients.
Ideally, we should have information that allows us to classify patients into one of these 3 groups. This is not, however, the issue addressed by most studies of the medical history and physical examination in the setting of acute chest pain. Rather, as shown in Figure 35-2, studies typically classify patients with acute chest pain into 2 groups according to the presence (group 1) or absence (group 2) of MI. Specifically, all patients with MI (Figure 35-1, groups A and B) are compared with all those without MI (Figure 35-1, group C).
Categorization of Patients With Acute Chest Pain in Studies Ascertaining Test Properties of History, Physical Examination, and Electrocardiogram
The results of studies that used the Figure 35-2 design may mislead clinicians who need to discriminate among the 3 groups of patients as shown in Figure 35-1. Clinical features that fail to distinguish patients with infarct or high-risk unstable angina from those with low-risk unstable angina or nonischemic chest pain might still be useful in the decision about whether to admit to a monitored bed in an acute care hospital. The study design that most investigators have chosen, depicted in Figure 35-2, does not correlate with the current triage of chest-pain patients according to the therapeutic options available. Current therapeutic interventions for MI require the presence of ECG changes. Categorizing patients as in Figure 35-2 will, however, provide clinically important information when we have interventions that are clearly useful in acute MI both with and without ECG changes. Our review will aid the reader in identifying features of the medical history, physical examination, and ECG that help differentiate acute MI patients, both with and without ECG changes, from non-MI patients. Clinicians must avoid misinterpreting the diagnostic information we will present as if it were useful in differentiating among the 3 groups in Figure 35-1.
Relevant Signs and Symptoms
Patients with acute MI typically present with a characteristic combination of signs and symptoms, as outlined in standard textbooks of medicine. Pain is described as being the most common presenting complaint, and considerable emphasis is placed on the characteristics of the pain, including its location, duration, radiation, and quality. Location of the pain includes the central portion of the chest or epigastrium, with potential radiation to the arms, neck, jaw, or less commonly to the abdomen and back. Quality of the chest pain is characteristically described with adjectives such as squeezing, crushing, and pressure.
Other symptoms also may be present, including diaphoresis, nausea, vomiting, weakness, and syncope. Although certain features have been identified as being important in recognizing MI, follow-up data from the Framingham study cohort estimate that approximately 25% of infarcts may go unrecognized because of either lack of chest pain or atypical symptoms.5
Mechanism of Chest Pain in Myocardial Infarction
Three-fourths of all patients with recognized acute MI present with chest pain.6 Cardiac ischemic pain originates in the myocardium, where free nerve endings are the sensory receptors. Cardiac afferent impulses travel through fibers in the cardiac sympathetic nerves, the upper 5 sympathetic ganglia, the white rami communicants, the gray rami, and then via the upper 4 or 5 thoracic roots. Cardiac afferent impulses project to the dorsal horn convergent neurons, travel via the spinothalamic tract to the thalamus, and subsequently to the cortex, where the cardiac stimuli are decoded.
Afferent impulses also travel in the cholinergic fibers of the vagus nerve, many of which arise from the inferior cardiac wall. The signs and symptoms of nausea, bradycardia, and hypotension, which appear to be more prevalent in patients with inferior wall MI, are believed to be related to the larger number of vagal afferent fibers located in the inferior cardiac wall.7
Like other visceral sensations, myocardial pain is poorly and variably localized. In addition, sensations originating in other intrathoracic structures (particularly the esophagus) can cause pain that is indistinguishable from cardiac pain.
Conditions That May Present With Symptoms Suggestive of Myocardial Infarction
There are many other clinical conditions that can present with symptoms suggestive of acute MI, which can be broadly divided into cardiac and noncardiac disorders. The noncardiac causes of chest pain are further divided into gastroesophageal diseases and nongastroesophageal diseases, whereas the cardiac causes are grouped into ischemic and nonischemic conditions. Figure 35-3 illustrates the most common of these conditions but is not all inclusive.
Cardiac and Noncardiac Conditions Presenting With Chest Pain
Given the diversity of the conditions presenting with chest pain, and the extent of the diagnostic testing that would be required, it is difficult to determine the relative frequency of each of these conditions occurring in the setting of chest pain. Pozen et al,8 in an evaluation of 1032 patients presenting to the emergency department with a chief symptom of chest pain, including follow-up ECG and cardiac enzyme tests for both hospitalized and nonhospitalized patients, reported an overall incidence of acute ischemia of 29% (ischemia included new-onset or unstable angina and MI). In an attempt to determine the etiology of noncardiac chest pain, Panju et al9 conducted further cardiac and gastrointestinal (GI) investigations in 100 patients discharged from a cardiac care unit (CCU) with chest pain not yet diagnosed (8.1% of the CCU admissions for chest pain). More than 75% of these patients had evidence of esophageal disorders by objective testing, including 24-hour intraesophageal pH monitoring, upper GI tract endoscopy with biopsy, esophageal motility studies, or upper GI tract barium series. These results are generalizable to patients discharged from the CCU with chest pain not yet diagnosed, a distinct subset of the patients who have noncardiac chest pain and present to the emergency department.
Inclusion Criteria of Tests for Precision and Accuracy
Given the limited number of studies that have focused on the precision of the medical history, physical examination, and ECG in the diagnosis of MI, we developed a broad set of inclusion criteria. We included studies that consisted of an assessment of the interobserver or intraobserver variation, of features of the medical history, physical examination, and ECG among patients with chest pain or a diagnosis of MI.
For the accuracy of the medical history, physical examination, and ECG, we included studies that met the following criteria: patients: those with chest pain thought to be ischemic in nature; test: history, physical examination, or ECG described in adequate detail; outcome: MI or no infarction using the definition described above; sample size: studies with a sample size of at least 200 patients.
For both precision and accuracy of the medical history, physical examination, and ECG, we performed an English-language MEDLINE search from 1980 to 1997, using the following Medical Subject Heading terms and search strategy: (1) “medical history taking or physical examination” and “myocardial infarction or chest pain” and (2) “reproducibility of results or observer variation” and “myocardial infarction” or “chest pain.” A textword search was also performed, using “interobserver,” “intraobserver,” “accuracy,” “precision,” “reliability,” “sensitivity,” “specificity,” and “myocardial infarction” or “chest pain.” Additional search strategies for accuracy included the term “myocardial infarction, diagnosis” (subheading). For all strategies, references from appropriate articles were reviewed to provide additional references for this article. Of the 14 references used to assess the precision and accuracy of the history, physical examination, and ECG in the diagnosis of acute MI, 12 were obtained from the MEDLINE search strategy and 2 from the review of reference lists.
One author (B.R.H.) initially screened the titles and abstracts. If she thought the articles might be relevant, she and another author (A.A.P.) reviewed the articles in detail and determined their eligibility.
Methodologic Quality Assessments
We evaluated the methodologic quality of articles addressing the accuracy of medical history, physical examination, or ECG using criteria developed for this series (see Table 1-7).10 A grade A designation meant an independent, blind comparison of sign or symptom with a gold standard among 500 or more consecutive patients suspected of having the target condition; grade B meant an independent, blind comparison of sign or symptom with a gold standard among fewer than 500 consecutive patients suspected of having the target condition; grade C meant an independent, blind comparison of sign or symptom with a standard of uncertain validity or independent, blind comparison of sign or symptom with a gold standard among nonconsecutive patients suspected of having the target disorder.
To calculate likelihood ratios (LRs) for features of the medical history, physical examination, and ECG, we considered studies suitable for combination if the sensitivity and specificity met one of the following criteria: χ2 test of sensitivity and specificity excluding statistically significant heterogeneity (P > .05) or range of sensitivity and specificity across studies of 15% or less. We pooled studies satisfying at least 1 criterion and calculated LRs by simple combination of results across studies. The 95% confidence intervals (CIs) were calculated according to the method of Simel et al.11
Precision of the Medical History and Physical Examination
Precision refers to the degree of variation between observers (interobserver variation) or within observers (intraobserver variation) regarding a particular clinical finding. Hickan et al12 studied the precision of an important aspect of the history, namely, that of chest pain. They assessed the interobserver agreement in chest pain histories obtained by general internists, nurse practitioners, and self-administered questionnaires for 197 inpatients and 112 outpatients with chest pain. As outlined in Table 35-2, the 2 internists, who each independently interviewed 47 of 197 inpatients, showed high agreement for 7 of the 10 items, including location and description of the pain, as well as aggravating and relieving factors. Agreement was slightly lower between internist and questionnaire and between the nurse practitioners and internist, with the lowest level of agreement between nurse and questionnaire. Features of the chest pain associated with a lower probability of MI, namely, pleuritic, positional, and sharp chest pain, typically showed a lower level of agreement for all comparisons.
Table 35-2Interobserver Agreement in Recording Chest Pain Historiesa |Favorite Table|Download (.pdf) Table 35-2 Interobserver Agreement in Recording Chest Pain Historiesa
|Attribute ||Inpatients (n = 197) || ||Outpatients (n = 112) |
|Two Internists, κ ||Internists and Questionnaire, κ || ||Nurse and Internists, κ ||Nurse and Questionnaire, κ |
|Pain radiates to left arm ||0.89 ||0.58 || ||0.43 ||0.41 |
|Pain relieved by nitroglycerin ||0.79 ||0.51 || ||0.94 ||0.77 |
|History of myocardial infarction ||0.78 ||0.81 || ||0.70 ||0.81 |
|Pain in substernal location ||0.74 ||0.50 || ||0.38 ||0.19 |
|Pain brought on by exertion ||0.63 ||0.51 || ||0.42 ||0.22 |
|Pain described as “pressure” ||0.57 ||0.37 || ||0.49 ||0.50 |
|Patient must stop activities when pain occurs ||0.50 ||0.47 || ||0.44 ||0.40 |
|Pain brought on by cough or deep breath ||0.44 ||0.30 || ||0.55 ||0.62 |
|Pain described as “sharp” ||0.30 ||0.26 || ||0.33 ||0.31 |
|Pain brought on by moving arms or torso ||0.27 ||0.44 || ||0.52 ||0.54 |
The precision of the medical history obtained also depends on the reliability of the sources themselves. Kee et al13 assessed the reliability of a reported family history of MI from patients who had recently survived MI with that of other documented sources, including hospital charts and death certificates. They reported a moderate level of agreement, with a κ of 0.65.
Few studies have evaluated the precision of features of the physical examination in the assessment of patients with suspected MI. One study did evaluate the interobserver agreement among 3 clinicians in the assessment of physical symptoms and signs of heart failure in 102 MI patients.14 As shown in Table 35-3, agreement was high for dyspnea, as well as for the displaced apex beat. However, the level of agreement for the other physical symptoms and signs of heart failure, particularly the assessment of pulmonary rales and hepatomegaly, was considerably lower.
Table 35-3Interobserver Agreement in Assessment of Physical Symptoms and Signs of Heart Failure in Patients With Myocardial Infarctiona |Favorite Table|Download (.pdf) Table 35-3 Interobserver Agreement in Assessment of Physical Symptoms and Signs of Heart Failure in Patients With Myocardial Infarctiona
|Physical Sign ||Range, κ |
|Dyspnea ||0.62-0.75 |
|Displaced apex beat ||0.53-0.73 |
|S3 gallop ||0.14-0.37 |
|Rales ||0.12-0.31 |
|Neck vein distention ||0.31-0.51 |
|Hepatomegaly ||0-0.16 |
|Dependent edema ||0.27-0.64 |
Precision of the Electrocardiogram Interpretation
Unfortunately, most studies that assessed the precision of ECG interpretation reported the percentage agreement between clinicians, without taking into account chance agreement through the use of κ or other statistical measures.15 Precise interpretations are important because they are made at the bedside and set off immediate management strategies. There are several factors that may influence the interpretation of the ECG, including the clinical observation of the patient and clinical data (expectation bias), as well as the training and experience of the individual reading the ECG. Although they must be interpreted with caution, the results of earlier studies suggest appreciable variability in precision in the interpretation of ECGs.
In one of the earlier studies,16 10 clinicians with experience in cardiology read 100 ECGs on 2 separate occasions and classified the tracings as normal, abnormal, or infarction. The 3 clinicians agreed completely in only one-third of the ECGs. After a second reading, the clinicians disagreed with 1 of 8 of their original reports. Gjorup et al17 had 16 residents in internal medicine read 107 ECGs of suspected MI patients and assess whether signs indicative of acute infarction were present. There was disagreement in approximately 70% of the cases.
Brush et al18 reported much higher agreement in a study in which 2 clinicians classified 50 ECGs according to evidence of infarction, ischemia or strain, left ventricle hypertrophy, LBBB, or paced rhythm. They obtained agreement in 45 of the 50 cases (κ = 0.69).
The precision in the interpretation of ECGs appears to increase with experience. Eight cardiologists interpreted ECGs of 1220 clinically validated cases of various cardiac disorders, including anterior, inferior, or combined MI, as well as right, left, or biventricular hypertrophy.19 The interobserver agreement among cardiologists was reasonably high, with an average κ of 0.67. For the 125 selected ECGs that were read twice by each cardiologist, different diagnoses were given for 10% to 23% of the ECGs (intraobserver reproducibility, 77%-90%).
Sgarbossa et al20 assessed the precision of features of the ECG that may aid in the diagnosis of acute MI in the presence of LBBB. In this study, 4 investigators read 2600 ECGs and achieved a κ of more than 0.85 for QRS-complex and T-wave polarities, with a high degree of correlation among the investigators for interpretation of ST-segment deviation (Pearson product moment correlation coefficient, > 0.9).
Studies Used to Determine Accuracy of the Medical History, Physical Examination, and Electrocardiogram
Table 35-4 summarizes features of the 14 studies 8, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, and 33 used to determine the accuracy of the medical history, physical examination, and ECG in the diagnosis of acute MI. Five of the studies included consecutive patients presenting to the emergency department with chest pain,8, 23, 24, 27, 28 7 included patients admitted to the hospital or CCU for suspected MI,21, 22, 25, 26, 29, 31, 32 and 2 included patients with chest pain who were brought to the emergency department by paramedics.30, 33
Table 35-4Features of Studies Used to Determine Accuracy of the Medical History, Physical Examination, and Electrocardiogram |Favorite Table|Download (.pdf) Table 35-4 Features of Studies Used to Determine Accuracy of the Medical History, Physical Examination, and Electrocardiogram
|Source, y ||Methodologic Qualitya ||Inclusion Criteria ||Incidence of MI, % ||No. of Patients (% Women) ||Age, y ||Country |
|Rude et al,21 1983 ||A ||Consecutive patients admitted to CCU with suspected MI ||50 ||3697 (38) ||Mean = 61 ||United States |
|Yusuf et al,22 1984 ||B ||Consecutive patients admitted to CCU with suspected MI ||85 ||475 (15) ||Mean = 56 ||United Kingdom |
|Pozen et al,8 1984 ||A ||Consecutive patients presenting to ED with chest pain ||NR ||2801 (NR) ||Men ≥ 30Women ≥ 40 ||United States |
|Lee et al,23 1985 ||A ||Consecutive patients presenting to ED with chest pain ||17 ||596 (52) ||≥25 ||United States |
|Tierney et al,24 1986 ||B ||Consecutive patients presenting to ED with chest pain ||12 ||492 (NR) ||Men ≥ 30Women ≥ 40 ||United States |
|Herlihy et al,25 1987 ||B ||Consecutive patients admitted to CCU with suspected MI ||44 ||265 (NR) ||NR ||United States |
|Klaeboe et al,26 1987 ||B ||Consecutive patients admitted to CCU with suspected MI ||59 ||237 (36) ||Range = 29-90 ||Norway |
|Rouan et al,27 1989 ||A ||Consecutive patients presenting to ED with chest pain ||14 ||7115 (50) ||≥30 ||United States |
|Solomon et al,28 1989 ||A ||Consecutive patients presenting to ED with chest pain ||14 ||7734 (50) ||≥30 ||United States |
|Berger et al,29 1990 ||B ||Consecutive patients admitted to hospital with chest pain ||36 ||278 (31) ||57 ||Switzerland |
|Weaver et al,30 1990 ||C ||Patients with chest pain brought to ED by paramedics ||18 ||2472 (NR) ||<75 ||United States |
|Jonsbu et al,31 1991 ||B ||Consecutive patients admitted to hospital with suspected MI ||36 ||200 (NR) ||NR ||Norway |
|Karlson et al,32 1991 ||A ||Consecutive patients admitted to hospital with suspected MI ||20 ||4690 (NR) ||NR ||Sweden |
|Kudenchuk et al,33 1991 ||C ||Patients brought to ED by paramedics ||33 ||1189 (34) ||≤74 ||United States |
The studies examined a variety of features of the clinical examination and ECG. For the sake of relevance and clarity, we highlight the results of those variables in which an LR of 2.0 or more, or an LR of 0.5 or less, was obtained. These studies provide the best available evidence for identifying those features that aid in the diagnosis of MI.
Accuracy of the Medical History and Physical Examination
Nine of the studies outlined in Table 35-4 reported the relation between features of the clinical examination of patients presenting to the emergency department with chest pain, as determined by physicians, with that of the final diagnosis of MI. In all studies, the gold standard for the diagnosis of MI was based on cardiac enzyme and ECG changes, except for the study by Weaver et al,30 in which the discharge diagnosis was used to define acute MI. Although features of the clinical examination are extremely insensitive in diagnosing MI, they are reasonably specific and their presence is more likely to occur in patients with MI.
Although patients can present with MI and have no chest pain, chest pain always prompts a consideration that the patient is having myocardial ischemia. Nonetheless, multivariate models show that the independent value of chest pain or pain in the left arm, once all factors are considered, has an odds ratio (OR) of only 2.7.8 Confining chest pain in the model to “chest pain as the most important symptom” has an even lower OR for MI (OR, 2.0).8
As noted in Table 35-5, chest pain radiation was the clinical feature that increased the probability of MI the most, with a wider extension of pain associated with the highest likelihood of MI. In particular, chest pain radiating to the left arm was twice as likely to occur in patients with, as opposed to those without, MI, whereas radiation to the right shoulder was about 2 times as likely, and radiation to both the left and right arm was 9 times as likely to occur in such patients. Chest pain radiating to the right arm alone has been reported to be an extremely specific, but insensitive, marker of MI (LR, 7.3; 95% CI, 3.9-14).29 However, as reflected by the width of the CI, these results were based on a small number of subjects (6 of the 100 patients with MI) and therefore require confirmation.
Table 35-5Clinical Features That Increase the Probability of a Myocardial Infarction in Patients Presenting With Acute Chest Pain |Favorite Table|Download (.pdf) Table 35-5 Clinical Features That Increase the Probability of a Myocardial Infarction in Patients Presenting With Acute Chest Pain
|Clinical Feature ||LR (95% CI) ||Reference |
|Chest pain radiation ||Both arms with pain ||9.7 (4.6-20) ||29 |
|Left arm pain ||2.2 (1.6-3.1) ||29 |
|Right shoulder pain ||2.9 (1.4-6.0) ||24, 29 |
|Third heart sound on auscultation ||3.2 (1.6-6.5) ||24 |
|Hypotension (systolic blood pressure ≤ 80 mm Hg) ||3.1 (1.8-5.2) ||30 |
|Pulmonary crackles on auscultation ||2.1 (1.4-3.1) ||24 |
|Diaphoresis ||2.0 (1.9-2.2) ||24, 28, 31 |
|Nausea or vomiting ||1.9 (1.7-2.3) ||24, 25, 29, 31 |
|History of MI ||1.5-3.0a ||8, 24 |
Other items of the history that aided in the diagnosis of MI included history of MI (LR ≤ 3.0) or diaphoresis (LR, 2.0).
A number of features from the history and clinical examination thought to be useful in determining the presence of MI were of little value in establishing such a diagnosis. Features of the history, including age older than 60 years, male sex, history of angina or coronary artery disease, history of nitroglycerin use, duration of chest pain greater than 60 minutes, constant or episodic chest pain, and chest pain of sudden onset, were all associated with LRs of less than 2. Adjectives used to describe the quality of the chest pain, including that of pressure, aching, and squeezing, were also associated with LRs of less than 2. Therefore, none of these features carry information independently useful in establishing an MI diagnosis.
The 3 components of the physical examination associated with LRs higher than 2 included the presence of a third heart sound (LR, 3.2), hypotension (LR, 3.1), and pulmonary crackles on auscultation (LR, 2.1). Dyspnea was not found to be an important component of the clinical examination. Other features frequently described in the assessment of the patient with chest pain, including bradycardia and tachycardia, were not evaluated.
Cardiac risk factors, including hypertension, smoking, obesity, hypercholesterolemia, diabetes, and a family history of cardiovascular disease, are frequently included in the medical history of a patient presenting with chest pain. However, current evidence provides little support for the diagnostic value of a history of these risk factors. In 3 large studies of patients presenting to the emergency department with chest pain, none of the classic cardiac risk factors emerged as independent predictors of acute MI.8, 34, 35
Table 35-6 presents clinical features that decrease the probability of MI. Chest pain described as pleuritic, sharp, stabbing, or positional decreased the likelihood of MI significantly. In addition, chest pain reproduced by palpation on physical examination was associated with a low LR, ranging from 0.2 to 0.4.
Table 35-6Clinical Features That Decrease the Probability of a Myocardial Infarction in Patients Presenting With Acute Chest Pain |Favorite Table|Download (.pdf) Table 35-6 Clinical Features That Decrease the Probability of a Myocardial Infarction in Patients Presenting With Acute Chest Pain
|Clinical Feature ||LR (95% CI) ||Reference |
|Pleuritic chest pain ||0.2 (0.2-0.3) ||23, 24, 28 |
|Chest pain sharp or stabbing ||0.3 (0.2-0.5) ||23, 24 |
|Positional chest pain ||0.3 (0.2-0.4) ||23, 28 |
|Chest pain reported by palpation ||0.2-0.4a ||23, 24, 28 |
Accuracy of the Electrocardiogram
Eight studies addressed the accuracy of the ECG in diagnosing MI. The results reported in this article are for interpretation of the ECGs by clinicians and not by computer algorithms. Interpretation of the ECG was by an independent physician blinded to the clinical data in 5 of the studies,8, 21, 22, 32, 33 by the emergency department physician alone in 2 others,23, 27 and by the emergency department physician with a review by an independent physician blinded to the clinical data in 1.24 In all studies, the gold standard for the diagnosis of MI was based on cardiac enzyme levels, except for the study by Kudenchuk et al,33 in which the hospital discharge diagnosis was used to define MI.
Several features of the ECG have been used to assist in the diagnosis of acute MI. The most common characteristics include the presence of Q waves, ST-segment elevation or depression, and T-wave inversion. As noted in Table 35-7, there was a considerable degree of variability among the studies for some of these features. New ST-segment elevation was the most powerful feature in increasing the probability of MI, with the LRs ranging from 5.7 to 54. The presence of a new Q wave was also much more likely to occur in patients with, as opposed to those without, MI, with LRs ranging from 5.3 to 25, although the usefulness of this finding was reduced when patients with old Q waves were included.
Table 35-7Features of the Electrocardiogram That Increase the Probability of a Myocardial Infarction in Patients Presenting With Acute Chest Pain |Favorite Table|Download (.pdf) Table 35-7 Features of the Electrocardiogram That Increase the Probability of a Myocardial Infarction in Patients Presenting With Acute Chest Pain
|Feature of the Electrocardiogram ||LR (95% CI) ||Reference |
|Any ST-segment elevation ||11 (7.1-18) ||24 |
|New ST-segment elevation ≥ 1 mm ||5.7-54a ||21-24, 32, 33 |
|New conduction defect ||6.3 (2.5-16) ||24 |
|New Q wave ||5.3-25a ||21, 24, 32, 33 |
|Any Q wave ||3.9 (2.7-5.7) ||24 |
|Any ST-segment depression ||3.2 (2.5-4.1) ||24 |
|T-wave peaking or inversion ≥ 1 mm ||3.1b ||8 |
|New ST-segment depression ||3.0-5.2a ||21, 24, 32 |
|Any conduction defect ||2.7 (1.4-5.4) ||24 |
|New T-wave inversion ||2.4-2.8a ||24, 32, 33 |
ST-segment depression, whether new or known to have been present previously, and new T-wave peaking or inversion were all approximately 3 times as likely to occur in patients with, as opposed to those without, MI. In addition, conduction defects, particularly those reported to be new, also increased the probability of MI.
A normal ECG result decreased the probability of MI the most and was associated with LRs of 0.1 to 0.3.19, 20, 26, 31
The Role of Combined Findings and Clinical Prediction Rules for Myocardial Infarction
Clinicians are frequently presented with multiple clinical examination items, each of which can be considered a separate diagnostic test for establishing the diagnosis of MI. The problem in situations such as this is in knowing how to combine the LRs from these multiple tests to obtain an accurate estimate of the posttest probability of MI. The simple serial multiplication of LRs that has been proposed assumes that the tests are conditionally independent15; that is, that the patient's results on one test bear no relationship to the results on any of the other tests. As demonstrated by Holleman and Simel,36 violation of the conditional independence assumption can yield inaccurate posttest probabilities of disease. Unfortunately, the precision and accuracy of serial combinations of findings were not reported in the studies included in this review. However, the combination of clinical findings considered as a group is assessed in clinical prediction rules.
By combining findings from patients’ medical history, physical examination, and ECG, investigators have developed probability-based decision aids, as well as computer-based protocols and guidelines, that categorize patients with chest pain into risk groups according to their probability of MI.34, 35, 37 These tools have been devised to improve physician recognition and triage of patients with acute ischemic events.8, 38 Although these measures have helped clinicians make appropriate decisions, not all studies of probability-based risk assessment tools have demonstrated improvement in emergency department triage or reduction in resource use.39 These clinical prediction rules conform to the methodologic standards of clinical prediction rules initially proposed by Wasson et al40 and recently revised,41 except for the validation of the rule by Tierney et al,34 which was performed on a subset, rather than on a prospective sample of the population.
Tierney et al34 developed an instrument for the prediction of MI. According to multivariate analysis of 540 emergency department patients with chest pain, 4 variables with independent predictive value for infarction were identified. These included diaphoresis with chest pain, history of MI, ECG changes of a new Q wave, and ST-segment elevation either new or old.
Goldman et al35, 37 also developed a protocol to predict MI in emergency department patients with chest pain. The instrument was based on the medical history, physical examination, and ECG of more than 6000 patients presenting at an emergency department with a chief complaint of chest pain. Variables in Goldman's algorithm include patient older than 40 years, history of angina or MI, chest pain that began less than 48 hours before arrival at the emergency department, longest pain episode 1 hour or more, pain worse than usual angina or the same as earlier MI, and radiation of pain to neck, left shoulder, or left arm as predictors of infarction. Features of the chest pain, including radiation to the back, abdomen, or legs; stabbing pain; and pain reproduced by palpation included in the algorithm decrease the probability of infarction. The ECG changes predictive of an acute MI included new ST-segment elevation or Q waves in 2 or more leads and new ST-T-segment changes of ischemia or strain. According to the algorithm, patients can be assigned to one of 14 subgroups, with a probability of acute MI ranging from 1% to 77%.
These prediction rules included several of the common variables identified in univariate analysis and included in this review, namely, the location and extent of the chest pain, chest pain with diaphoresis, and ECG changes, including new Q-wave and ST-segment elevation. However, in situations in which the independence of features of the medical history and clinical examination has not been tested, as in these studies, clinicians may be misled when combining these multiple clinical findings. In these situations they should look to clinical prediction rules to help integrate and interpret the results.
Pretest Probability in the Diagnosis of Myocardial Infarction
To determine the posttest probability, or likelihood, of disease according to the clinical features and their associated LRs, one must take into account the pretest probability, or likelihood, of that condition. Although much focus has been placed on the combination of multiple clinical variables and the development of prediction rules for MI, as described above, there has been little emphasis on establishing the pretest probability of MI according to standard clinical assessment. If an estimate of the pretest probability of MI is available, a diagnostic test, based on its sensitivity, specificity, and LR, can be used to establish a new estimate of disease likelihood. A classic and widely used example of this concept was proposed by Diamond and Forrester.42 Estimates of the pretest probability of coronary artery disease according to age, sex, and chest pain description have been published and are easily used in the clinical setting. A more comprehensive attempt to consider all clinical characteristics has also been undertaken.43
The predictive value of the medical history, physical examination, and ECG depends on the pretest probability of MI. Even with a normal ECG result, for example, a high pretest probability of MI would result in a high posttest probability of this condition being present. Proper use of these findings must therefore incorporate the pretest probability of MI.
The diagnosis of MI in the setting of chest pain is a complex task. Clinicians categorize patients with chest pain into 3 groups according to current therapeutic interventions, whereas in the literature patients with chest pain are typically categorized into the presence or absence of MI. According to this latter categorization, we have assessed the features of the medical history, physical examination, and ECG, which aid in increasing or decreasing the likelihood of acute MI. We have also addressed the use of clinical prediction rules, which use a number of clinical variables, to aid in the diagnosis of MI, as well as the need to take into account pretest probability of disease when assessing the predictive value of individual variables.
Referring to the scenarios presented at the beginning of this article, the first 3 have features that increase the likelihood of acute MI. Patient 1 has chest pain, diaphoresis, and ST-segment elevation. Patient 2 has diaphoresis, hypotension, and history of an MI. Patient 3 has nausea and ST-segment elevation. In contrast, patient 4 has features that decrease the likelihood of MI, namely, a normal ECG result and chest pain that is both positional and reproducible by palpation.
Clinicians interested in distinguishing patients with acute MI from those with unstable angina and nonanginal chest pain can use either Goldman's algorithm or the individual clinical features that we summarize in Tables 35-5, 35-6, and 35-7. However, the distinction between MI and non-MI chest pain may not be the most relevant initial clinical decision; it is more important to decide on appropriate immediate therapy.
The presence of any of the following clinical findings increases the likelihood of MI: patients presenting with chest pain radiating to the left arm, radiating to the right shoulder, or radiating to both left and right arms; and patients presenting with chest pain diaphoresis, a third heart sound, or with hypotension.
The presence of any of the following clinical findings decreases the likelihood of MI: patients presenting with chest pain that is described as pleuritic, sharp or stabbing, positional, or reproduced by palpation.
Features of ECG that increase the likelihood of MI include the following: new ST-segment elevation, new Q waves, any ST-segment elevation, and new conduction defect. A normal ECG result is a powerful feature in ruling out MI.
Finally, as noted previously, these findings may not be relevant for distinguishing between patients with acute ischemic syndromes requiring CCU admission from those with less dangerous ischemia or nonischemic pain. Further research is required in this regard.
Author Affiliations at the Time of the Original Publication
Departments of Medicine (Drs Panju and Guyatt), Clinical Epidemiology and Biostatistics (Dr Guyatt), and McMaster Medical Programme (Dr Hemmelgarn), McMaster University, Hamilton, Ontario, Canada; and the Center for Health Services Research in Primary Care, Durham Veterans Affairs Medical Center, Duke University Medical Center, Durham, North Carolina (Dr Simel). Dr Hemmelgarn is currently a resident in internal medicine at the University of Calgary, Alberta, Canada.
We are indebted to Eric C. Westman, MD, Michael Cuffe, MD, Salim Yusuf, MD, and Ernest Fallen, MD, for their review and contribution to the manuscript, as well as to John Attia, MD, Arie Levinson, MD, and James Velianou, MD, for their suggestions on the final manuscript.
DG. Angina pectoris: definition and description. In: Julian DG, ed. Angina Pectoris. 2nd ed. New York, NY: Churchill Livingstone; 1985:2.
L. Grading of angina pectoris. Circulation.
et al.. Diagnosing and managing unstable angina. Circulation.
D. Rajakangas AM, Pajak A. Myocardial infarction and coronary deaths in the World Health Organization Monica Project. Circulation.
WB. Symptomatic myocardial infarction without chest pain: prevalence
and clinical course. Am J Cardiol.
WB. A predictive instrument to improve coronary care unit admission practices in acute ischemic heart
disease. N Engl J Med.
et al.. Outcome of patients discharged from a coronary care unit with a diagnosis of “chest pain not yet diagnosed.” CMAJ.
DB. Likelihood ratios with confidence: sample size estimation for diagnostic test studies. J Clin Epidemiol.
CH. Systematic bias
in recording the history in patients with chest pain. J Chronic Dis.
et al.. Symptoms and signs of heart
failure in patients with myocardial infarction: reproducibility and relationship to chest x-ray, radionuclide ventriculography and right heart
catheterization. Eur Heart J.
P. Clinical Epidemiology: A Basic Science for Clinical Medicine. 2nd ed. Boston, MA: Little Brown & Co; 1991.
J. Interpretation of the electrocardiogram in suspected myocardial infarction: a randomized controlled study of the effect of a training programme to reduce interobserver variation. J Intern Med.
FJ. Use of the initial electrocardiogram to predict in-hospital complications of acute myocardial infarction. N Engl J Med.
et al.. The diagnostic performance of computer programs for the interpretation of electrocardiograms. N Engl J Med.
et al.. Electrocardiographic diagnosis of evolving acute myocardial infarction in the presence of left bundle-branch block. N Engl J Med.
et al.. Electrocardiographic and clinical criteria for recognition of acute myocardial infarction based on analysis of 3,697 patients. Am J Cardiol.
P. Sleight P. The entry ECG in the early diagnosis and prognostic stratification of patients with suspected acute myocardial infarction. Eur Heart J.
et al.. Physicians’ estimates of the probability
of myocardial infarction in emergency room patients with chest pain. Med Decis Making.
and vomiting during acute myocardial infarction and its relation to infarct size and location. Am J Cardiol.
MC. Goldman L. Clinical characteristics and outcome of acute myocardial infarction in patients with initially normal or nonspecific electrocardiograms. Am J Cardiol.
et al.. Comparison of clinical presentation of acute myocardial infarction in patients older than 65 years of age to younger patients: the Multicenter Chest Pain Study experience. Am J Cardiol.
E, Van Melle
B. Right arm involvement and pain extension can help to differentiate coronary diseases from chest pain of other origin: a prospective emergency ward study of 278 consecutive patients admitted for chest pain. J Intern Med.
et al.. Myocardial Infarction Triage and Intervention Project, phase I: patient characteristics and feasibility of prehospital initiation of thrombolytic therapy. J Am Coll Cardiol.
et al.. Rapid and correct diagnosis of myocardial infarction: standardized case history and clinical examination provide important information for correct referral to monitored beds. J Intern Med.
A. Early prediction of acute myocardial infarction from clinical history, examination and electrocardiogram in the emergency room. Am J Cardiol.
et al.. Accuracy of computer-interpreted electrocardiography in selecting patients for thrombolytic therapy. J Am Coll Cardiol.
et al.. Predictors of myocardial infarction in emergency room patients. Crit Care Med.
et al.. A computer protocol to predict myocardial infarction in emergency department patients with chest pain. N Engl J Med.
DL. Quantitative assessments from the clinical examination: how should clinicians integrate the numerous results? J Gen Intern Med.
et al.. A computer-derived protocol to aid in the diagnosis of emergency room patients with acute chest pain. N Engl J Med.
et al.. Impact of the acute cardiac ischemia time-insensitive predictive instrument (ACI-TIPI) on the speed of triage decision making for emergency department patients presenting with chest pain. J Gen Intern Med.
T. Physician response to a prediction rule for triage of emergency department patients with chest pain. J Gen Intern Med.
JS. Analysis of probability
as an aid in the clinical diagnosis of coronary artery disease. N Engl J Med.
RA. Estimating the likelihood of significant coronary artery disease. Am J Med.