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A chest pain score for stratifying the risk of coronary artery disease in patients having day case coronary angiography
International Journal of Cardiology 78 (2001) 257–264 www.elsevier.com / locate / ijcard
A chest pain score for stratifying the risk of coronary artery disease in patients having day case coronary angiography a, b a E.B. Wu *, N. Smeeton , J.B. Chambers a
Cardiothoracic Centre, Guy’ s and St Thomas’ Hospitals, London, UK b Department of Public Health Medicine, GKT, London, UK
Received 4 July 2000; received in revised form 5 January 2001; accepted 10 January 2001
Abstract ‘Typical’ or ‘atypical’ are universally used descriptions of chest pain, but they are limited by subjectivity. This study tested the ability of a semi-objective chest pain score to predict the likelihood of coronary disease. A chest pain questionnaire was given to 250 patients with stable chest pain attending coronary angiography. The answers to three questions were defined as ‘typical’ or ‘atypical’ and summed to give a ‘typical’ score between 0 and 3. Logit analysis was performed based on an age cut-off of 55 years and ‘typical’ score. There were 96 (38%) patients with normal coronary arteries and 154 (62%) with coronary disease. In patients aged under 55 years, the likelihood of coronary disease by ‘typical’ score was 11% (score 0), 30% (score 1), 40% (score 2), 53% (score 3). Similar figures for age 55 years were 39% (score 0), 45% (score 1), 77% (score 2), and 85% (score 3). There is a direct relationship between ‘typical’ chest pain score and the likelihood of coronary artery disease. This scoring system may be useful in the clinical characterization of patients for research, for guiding referral to a cardiologist or for aiding the decision to perform coronary angiography. 2001 Elsevier Science Ireland Ltd. All rights reserved. Keywords: Chest pain; Coronary artery disease; Coronary angiography
1. Introduction Chest pain occurs frequently in the community [1,2] and usually has a benign non-cardiac explanation [3] In deciding which patients should be referred for further investigation, the physician will be guided by the presence of risk factors for coronary disease, the clinical examination, the results of noninvasive investigation, and importantly by the quality of the chest pain. Although chest pain varies widely in character it is usually summarized as either ‘typical’ or ‘atypical’ of *Correspondence author. Cardiothoracic Centre, 6th Floor, East Wing, St Thomas’ Hospital, Lambeth Palace Road, London SE1 7EH, UK. Tel.: 144-20-7928-9292, ext. 6036; fax: 144-20-7960-5680. E-mail address: e [email protected] (E.B. Wu). ]
a cardiac origin. These terms are subjective and rarely defined, which may help to explain why rates for normal coronary anatomy at coronary angiography vary from 7 to 31% [4,5]. Day and Sowton [4] showed that 60% of patients had chest pain that could be related to exertion, while only 16% had pain reproducibly on exertion. The incidence of ‘typical’ pain in this study could be taken as either 16 or 60% and it would clearly be an advantage if ‘typical’ could be defined more precisely. However, the validity of any method of clinical categorisation must be tested against an independent standard, for example coronary angiography. There is preliminary evidence that a semi-quantitative chest pain score rating the degree of being ‘typical’ on a 4-point scale can differentiate patients
0167-5273 / 01 / $ – see front matter 2001 Elsevier Science Ireland Ltd. All rights reserved. PII: S0167-5273( 01 )00382-5
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with normal coronary anatomy and those with coronary artery disease [6] If this model could be validated it might be expected to improve the noninvasive assessment of a patient with chest pain to guide referral to a cardiologist or help determine the need for coronary angiography. Previous work derived the chest pain model retrospectively in sex-matched patients chosen to have either completely normal coronary anatomy or significant coronary disease [6]. The aim of this study was to assess the ability of the model to predict the likelihood of coronary disease prospectively in patients undergoing diagnostic coronary angiography.
2. Methods
2.1. Subjects The day-case lists of three participating consultants were examined between 1st September 1997 and 30th June 1998. Of 829 consecutive patients undergoing day case coronary angiography, 250 had the required inclusion criteria of chest pain for longer than 1 month and no previous evidence of coronary artery disease. Patients were excluded if there were pathological Q waves or anything more than nonspecific ST / T wave changes on the electrocardiogram or regional wall motion abnormalities on the echocardiogram, abnormal coronary arteries demonstrated by previous coronary angiography, or a history of coronary angioplasty or coronary artery bypass grafting. Other exclusion criteria were anything more than mild valve disease, atrial fibrillation, abnormal left ventricular systolic function (fractional shortening ,28% or estimated left ventricular ejection fraction ,50% on echocardiography), left ventricular hypertrophy, and renal failure.
2.2. Procedure Patients granted oral consent and were then interviewed within 8 h of coronary angiography by one author (E.B.W.) who was blinded to the results of the angiogram. A modification of the Master [7] questionnaire was used with the addition of three specific questions previously shown to differentiate normal from abnormal coronary angiograms [6]: (1) ‘‘If you
go up a hill (or another individually appropriate stress) on ten separate occasions, on how many of these do you experience chest pain?’’ The answer to this question was called the reproducibility score; (2) ‘‘If you have the pain ten times in a row, how many happen when you are resting or sitting quietly?’’ The answer to this question was called the rest score; (3) ‘‘How long does the pain usually last?’’ The answers to these questions were dichotomized as either ‘typical’ or ‘atypical’ [6]. For question 1, a reproducibility score of 10 was defined as ‘typical’ and a score of 1–9 was defined as ‘atypical’. For question 2, a rest score of 0 or 1 was defined as ‘typical’ and 2 or more was defined as ‘atypical’. Pain duration of 5 min or less was ‘typical’ and longer than 5 min was ‘atypical’. The answers to these 3 questions were added to give a ‘typical’ chest pain score between 0 and 3 for each patient. The coronary angiogram was performed using the standard Sones or Judkins techniques with multiple orthogonal views. The angiogram was recorded as abnormal if a stenosis judged by eye to be 50% or more of the luminal diameter was shown in at least one main epicardial vessel or a major branch. The angiogram was recorded as normal or near-normal if the most severe stenosis was ,50% of the luminal diameter. For simplicity, patients with an abnormal angiogram were grouped as ‘coronary disease’ and those with normal or near-normal angiograms were grouped as ‘normal anatomy’. The classification of patients with near-normal anatomy as normal is an oversimplification, which was permitted since it was likely to underestimate rather than exaggerate the validity of our results
2.3. Statistics Mean and standard deviation values were calculated. The Student’s t test was used for comparison of continuous variables and the Mann–Whitney U test for non-parametric data. Frequencies of each chest pain characteristic were calculated and odds ratios between those with coronary artery disease and those without were calculated; 95% confidence intervals calculated with the method described by Woolf [8]. A model composed of the ‘typical’ chest pain score and age dichotomized to less than or greater than or equal to 55 years was analyzed by logit regression. The
E.B. Wu et al. / International Journal of Cardiology 78 (2001) 257 – 264
259
Table 1 Demographics
Age Duration of pain (months) % males a *
Normal (n596) Mean (S.D.a) (range)
Abnormal (n5154) Mean (S.D.) (range)
58.3 (9.2) (34–80) 34 (50) (2–288) 52%
63 (8.8) (28–86) 25 (32) (1–180) 78%*
S.D., standard deviation. P,0.001.
cut-off of 55 years was chosen based on the results of earlier work [6]. A P value of less than 0.05 was considered to be significant. Statistical analysis was performed using the Statistical Package for Social Sciences for windows, release 7.0.
3. Results
Fig. 1. Diagram of site numbers on the chest wall.
3.1. General Of the 250 patients, 96 (39%) had normal anatomy and 154 (61%) had coronary disease. There were no significant differences in age, but more males had abnormal angiography than females (OR 0.3, 95% CI 0.18–0.52, P,0.001) (Tables 1 and 2). Diabetes was more common in those with coronary artery disease (odds ratio 1.9, 95% CI 0.06–0.66), but there were no significant differences in other coronary risk factors (Table 2).
3.2. Chest pain characteristics The median duration of chest pain was 15 months (range: 2–228 months) in those with normal anatomy and 12 months (range: 1–180 months) (P50.07) in those with coronary disease. Pain at site 5 (Fig. 1) was more common in those with normal coronary anatomy (odds ratio 2.00, 95% CI 1.13–3.53), but there were no other significant differences between
the two groups in the site, radiation, quality and distribution of the chest pain (Tables 3–6). There were no significant differences in precipitating factors including emotional stress, food, lying down or stooping, carrying, or neck movement (Table 7). Relief of chest pain with short acting nitrates was reported more frequently in those with coronary Table 3 Pain characteristics — site (see also Fig. 1) Site
Normal (n596)
Abnormal (n5154)
Odds ratio
95% CI a
1 2 3 4 5 6 7 8 9
11 (11%) 26 (27%) 12 (13%) 22 (23%) 74 (76%) 33 (34%) 11 (12%) 53 (55%) 21 (22%)
20 31 24 35 95 61 14 73 34
0.86 1.45 0.76 1.00 2.00 0.79 1.28 1.34 0.98
0.39–1.88 0.80–2.64 0.36–1.61 0.54–1.83 1.13–3.53* 0.46–1.34 0.56–2.95 0.80–2.23 0.53–1.80
a *
(13%) (20%) (16%) (23%) (62%) (39%) (9%) (48%) (22%)
CI is confidence interval. P,0.05.
Table 2 Coronary risk factors Risk factors
Normal (n596)
Abnormal (n5154)
Odds ratio
95% CI
Cholesterol Diabetes Hypertension Smoking Family history
38 3 37 31 43
67 22 67 65 63
0.84 0.19 0.78 0.64 1.15
0.50–1.40 0.06–0.66* 0.46–1.31 0.38–1.10 0.69–1.92
*
P,0.05.
(40%) (3%) (39%) (32%) (45%)
(44%) (29%) (44%) (42%) (41%)
E.B. Wu et al. / International Journal of Cardiology 78 (2001) 257 – 264
260 Table 4 Pain characteristics — radiation Radiation
Normal (n596)
Abnormal (n5154)
Odds ratio
95% CI a
Back Left arm Right arm Neck Legs Abdomen
14 40 13 19 3 1
11 54 32 30 4 0
2.19 1.30 0.59 1.01 1.19
0.95–5.05 0.77–2.19 0.29–1.19 0.53–1.91 0.26–5.43
a
(14%) (42%) (14%) (20%) (3%) (1%)
(7%) (35%) (21%) (20%) (3%) (0%)
CI is confidence interval.
Table 5 Quality of chest pain Quality
Normal (n596)
Abnormal (n5154)
Odds ratio
95% CI a
Heavy Gripping Stabbing Burning
28 (29%) 36 (38%) 12 (13%) 6 (6%)
32 62 14 6
1.57 0.89 1.43 1.64
0.87–2.83 0.53–1.50 0.63–3.23 0.51–5.25
a
(21%) (40%) (9%) (4%)
artery disease [93 (60%)] than those with normal anatomy [42 (43%) (odds ratio 0.5, 95% CI 0.30– 0.84, P50.009)] (Table 8). However, relief within 5 min occurred in only 30 (31%) of those with normal coronary anatomy as compared to 81 (53%) with coronary artery disease (odds ratio 0.4, 95% CI 0.24– 0.69, P50.003). Improvement of pain with rest was significantly more common in those with coronary
CI is confidence interval.
Table 6 Distribution of chest pain and chest wall tenderness Distribution
Normal (n596)
Abnormal (n5154)
Odds ratio
95% CI a
Generalised One-pointed Tenderness
44 (45%) 19 (20%) 3 (3%)
78 (50%) 28 (18%) 2 (1%)
0.81 1.10 2.43
0.49–1.35 0.57–2.09 0.40–14.80
a
CI is confidence interval.
Table 7 Precipiating factors Factor
(Normal (n596)
Abnormal (n5154)
Odds ratio
95% CI a
Carrying Food Lying down / stooping Emotional stress Inspiration Movement
14 18 17 18 6
29 20 21 23 2 1
(19%) (13%) (14%) (15%) (1%) (1%)
0.73 1.44 1.28 1.30 5.01 3 (2%)
0.36–1.46 0.72–2.87 0.64–2.54 0.66–2.55 1.00–25.35
a
(14%) (19%) (18%) (19%) (6%)
CI is confidence interval.
Table 8 Relieving factors Relieving factors
Normal (n596)
Abnormal (n5154)
Odds ratio
95% CI a
Rest Milk / antacids GTN Relief #5 min
56 7 42 30
125 (82%) 7 (5%) 93 (61%) 81 (53%)
0.32 1.62 0.50 0.40
0.18–0.56* 0.55–4.78 0.30–0.84* 0.24–0.69*
a *
CI is confidence interval. P,0.05.
(58%) (7%) (43%) (31%)
E.B. Wu et al. / International Journal of Cardiology 78 (2001) 257 – 264
261
Table 9 Assiciated symptoms Associated symptoms
Normal (n596)
Abnormal (n5154)
Odds ratio
95% CI a
Tingling in fingers Dizziness Palpitations Dyspnoea
47 35 37 67
47 28 37 97
2.14 2.54 1.95 1.31
1.27–3.62* 1.42–4.55* 1.12–3.39* 0.76–2.25
a *
(49%) (36%) (39%) (69%)
(31%) (18%) (24%) (63%)
CI is confidence interval. P,0.05.
artery disease, occurring in 125 (81%) compared with 56 (58%) of those with normal anatomy (odds ratio 0.32, 95% CI 0.18–0.56, P,0.001). There was no difference between the two groups in the frequency of associated shortness of breath, but dizziness, palpitations and paraesthesiae of the fingers were all significantly more frequent in patients with normal anatomy (Table 9).
3.3. Differentiating factors Ten patients (6%) with coronary disease and seven (7%) with normal anatomy could not answer all three questions. In the remaining 89 patients with normal anatomy and 144 with coronary disease, there were major differences in the answers given to the three question model. A consistent relation between chest pain and exercise (reproducibility score 10) was significantly less common in patients with normal anatomy (n534) (38%) than in those with coronary disease (n5104) (72%) (odds ratio 0.23, 95% CI 0.13–0.41). Infrequent rest pain (rest score 0 or 1) was less likely in patients with normal anatomy (n536) (40%) than in those with coronary disease (n5105) (73%) (odds ratio 0.26, 95% CI 0.15–0.45). Short pain episodes lasting 5 min or less were less common in those with normal anatomy (n557) (59%) than with coronary disease (n5111) (72%) (odds ratio 0.53, 95% CI 0.31–0.91) (Table 10).
Table 11 The logit model for the prediction of normal vs. abnormal coronary angiogram Chest pain score and age
Coefficient
Z value
S.E.
Age (,55 years vs. $55 years) Reproducibility (10 vs. 1–9) Duration (#5 min vs. .5 min) Rest score (0 or 1 vs. 2–10)
1.39 0.98 20.53 20.77
3.84 2.71 21.62 22.1
0.36 0.36 0.33 0.37
A logit analysis was performed using age ($55 years vs. ,55 years) and the three symptoms from the symptom model categorized as described above as either ‘typical’ or ‘atypical’. A gradation in the likelihood of coronary disease was given by the aggregate number of ‘typical’ responses to the three questions as shown in detail in Table 11. For example, patients aged ,55 years with no ‘typical’ symptoms had an 11% chance of coronary artery disease while those aged 55 years or more with three ‘typical’ responses had an 85% chance of coronary artery disease (Table 12). Of the nine patients aged ,55 years with no ‘typical’ responses, only one had coronary artery disease. This patient had occlusion of the left anterior descending artery after the first diagonal branch and a 90% lesion in the mid-right coronary artery. He stopped after 4 min of a standard Bruce protocol exercise test with chest pain but no significant ST segment changes. He remains pain-free on antianginal therapy 1 year after angiography.
Table 10 Reproducibility, rest score, duration Chest pain scores
Normal (n596)
Abnormal (n5154)
Odds ratio
95% CI a
Reproducibility (10) Rest score (0 or 1) Duration (#5 min)
34 (38%) 36 (40%) 57 (59%)
104 (72%) 105 (73%) 111 (72%)
0.23 0.26 0.53
0.13–0.41* 0.15–0.45* 0.31–0.91*
a *
CI is confidence interval. Statistically significant at 95%, or P,0.05.
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Table 12 Probability of abnormal coronary angiogram (CA) based on pain characteristics and age Number of typical symptoms
Likelihood of abnormal CA (%)
Actual incidence (%)
,55 years of age 0/3 1/3 2/3 3/3
11 20–28 35–46 59
1 / 9 (11) 3 / 10 (30) 6 / 15 (40) 9 / 17 (53)
#55 years of age 0/3 1/3 2/3 3/3
37 50–61 68–77 85
9 / 23 17 / 38 41 / 53 58 / 68
4. Discussion A simple model based solely on age and three chest pain characteristics can stratify the likelihood of coronary disease prospectively in patients admitted for day-case diagnostic coronary angiography. The likelihood rose from 11 to 30 to 40% and finally to 53% in patients aged under 55 years according to whether the number of ‘typical’ responses was 0, 1, 2 or 3. Similar figures for ages equal to or greater than 55 years were 35, 45, 77 and 85%. The conventional assessment of pain as either ‘typical’ or ‘atypical’ of a cardiac origin is highly subjective and expressions like ‘typical with atypical features’ are so vague as to be almost meaningless. We suggest instead that chest pain could be characterized according to the number of ‘typical’ responses to give a ‘typical’ chest pain score between 0 and 3. This score could be used to standardize descriptions of chest pain in research studies for example of patients with normal coronary anatomy. Furthermore, we showed that the likelihood of coronary disease was directly related to the number of typical responses. This suggests that the score could also be of clinical use. Together with the results of noninvasive testing, it could aid in stratifying the need for coronary angiography. It might be of even greater use in the outpatient clinic where 11–27% only of patients with chest pain have evidence of cardiac disease [3,9]. These possibilities would need to be tested further in larger populations. The importance of clinical assessment in outpatients has been shown by Pryor et al. [10] who demonstrated in 1030 consecutive outpatient referrals that the clinician’s
(39) (45) (77) (85)
initial clinical judgement was better than exercise tolerance testing in predicting coronary anatomy and 3-year outcome. Other authors have differentiated cardiac and non-cardiac chest pain using a 26 question psychological model [11]. McCroskery et al. [12] demonstrated that the Millon Behavioural Health Inventory Questionnaire could discriminate between those with and without coronary artery disease in patients listed for coronary angiography. It is possible that a combination of our three-question chest pain model and psychological questions could improve stratification of the likelihood of coronary disease. The chest pain model is based on three questions previously identified by a logit analysis of selected patients with either significant coronary disease or completely normal angiograms. These questions consider the relationship with exercise (reproducibility score), the number of episodes at rest (rest score) and the average perceived duration of pain episodes. These characteristics are consistent with subjective clinical experience and at first sight seem obvious. However, although we know that cardiac pain is precipitated by exercise [13], what constitutes a reproducible relationship to exercise has not previously been defined. Thus, we previously showed [6] that 94% of patients with normal anatomy had chest pain thought by the cardiologist to be related to exercise but in only 38% was it reproducibly related to exercise as defined by the chest pain model. Other authors also showed that chest pain with a poor relationship to exercise or occurring in episodes of long duration are associated with normal coronary anatomy [4]. We showed that site, radiation and quality of the
E.B. Wu et al. / International Journal of Cardiology 78 (2001) 257 – 264
chest pain did not differentiate patients with normal and abnormal angiograms. Furthermore, a number of features such as localization of chest pain in a small region, sometimes thought to suggest non-cardiac pain [14], did not in fact differentiate our patients. This is in agreement with previous work [6]. Dizziness and digital paraesthesiae were more common in patients with normal anatomy [11], but occurred too frequently in those with coronary disease to be clinically useful.
4.1. Limitations The model alone cannot be used as a reliable predictor of normal coronary anatomy since one patient with coronary disease was misclassified. However, this patient had chest pain early during Bruce protocol exercise. This underlines that the model must be interpreted in the context of the whole noninvasive assessment. The questionnaire is no more than semi-objective. However, this is not as major a limitation as it first seems since the statistically determined cut-off between ‘typical’ and ‘atypical’ is at extremes of the scoring scales. A patient is likely to be able to recall whether he or she experiences pain every time he is subjected to a particular stressor or whether pain occurs almost never at rest. Had the statistically determined threshold been at 7 or 8 times out of 10 its accuracy might have been more in question. A small number of patients were unable to answer the questions adequately. We did not use quantitative analysis of coronary lesions nor intravascular ultrasound, but confined ourselves to the same method of analysis as used in routine clinical practice. Furthermore, we used an imperfect cut-off between our two clinical groups. Some patients with a coronary stenosis at around 50% have no evidence of objective myocardial ischaemia while others may have significant ischaemia. It is therefore possible that some patients in our normal group may have had myocardial ischaemia and others in the coronary group may have had no ischaemia. These potential errors of classification are unlikely to be numerous and in any case would have tended to underestimate rather than exaggerate the significance of our results.
263
4.2. Conclusion A chest pain model previously derived in selected patients using logit analysis has been tested prospectively in patients having day case coronary angiography. This model allows a semi-objective classification of chest pain avoiding some of the imprecision of conventional descriptions such as ‘typical’ or ‘atypical’. There is a direct relationship between the ‘typical’ chest pain score and the likelihood of coronary disease suggesting that it might be clinically useful. As well as improving the clinical description of patients for research studies, this score could be useful for defining guidelines for referral from the community to a cardiologist and could also help in determining the need for coronary angiography.
Acknowledgements Financial information: Dr Wu was supported by a grant from the Special Trustees of Guy’s and St Thomas’ Hospitals
References [1] LaCroix AZ, Haynes SG, Savage DD, Havlik RJ. Rose questionnaire angina among United States black, white, and Mexican– American women and men. Prevalence and correlates from the second National and Hispanic Health and Nutrition Examination Surveys. Am J Epidemiol 1989;129:669–86. [2] Hannay DR. The ‘iceberg’ of illness and ‘trivial’ consultations. J R Coll Gen Pract 1980;30:551–4. [3] Kroenke K, Mangelsdorff AD. Common symptoms in ambulatory care: incidence, evaluation, therapy, and outcome. Am J Med 1989;86:262–6. [4] Day LJ, Sowton E. Clinical features and follow-up of patients with angina and normal coronary arteries. Lancet 1976;2:334–7. [5] Bass C, Jackson G. Angina with normal coronary arteriograms. Clinical status at one year. Archives des Maladies du Coeur et des Vaisseaux 1983;76:237–45. [6] Cooke RA, Smeeton N, Chambers JB. Comparative study of chest pain characteristics in patients with normal and abnormal coronary angiograms. Heart 1997;78:142–6. [7] Master AM. The spectrum of anginal and non cardiac pain. J Am Med Assoc 1964;187:894–9. [8] Gardner MJ, Altman DG. In: Statistics with confidence — Confidence interval and statistical guidelines, BMJ Publishers, 1989, p. 53. [9] Jain D, Fluck D, Sayer JW, Ray S, Paul EA, Timmis AD. Ability of a one-stop chest pain clinic to identify patients with high cardiac risk in a district general hospital. J R Coll Physicians Lond 1997;31:401–4.
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[10] Pryor DB, Shaw L, McCants CB, Lee KL, Mark DB, Harrell Jr FE, Muhlbaier LH, Califf RM. Value of the history and physical in identifying patients at increased risk for coronary artery disease. Ann Intern Med 1993;118:81–90. [11] Serlie AW, Duivenvoorden HJ, Passchier J, ten Cate FJ, Deckers JW, Erdman RA. Empirical psychological modeling of chest pain: a comparative study. J Psychosom Res 1996;40:625–35. [12] McCroskery JH, Schell RE, Sprafkin RP et al. Differentiating anginal patients with coronary artery disease from those with normal coronary arteries using psychological measures. Am J Cardiol 1991;67:645–6.
[13] Costa PT, Zonderman AB, Engel BT, Baile WF, Brimlow DL, Brinker J. The relation of chest pain symptoms to angiographic findings of coronary artery stenosis and neuroticism. Psychosom Med 1985;47:285–93. [14] Chambers J, Bass C. Chest pain with normal coronary anatomy: a review of natural history and possible etiologic factors. Prog Cardiovasc Dis 1990;33:161–84.
A chest pain score for stratifying the risk of coronary artery disease in patients having day case coronary angiography a, b a E.B. Wu *, N. Smeeton , J.B. Chambers a
Cardiothoracic Centre, Guy’ s and St Thomas’ Hospitals, London, UK b Department of Public Health Medicine, GKT, London, UK
Received 4 July 2000; received in revised form 5 January 2001; accepted 10 January 2001
Abstract ‘Typical’ or ‘atypical’ are universally used descriptions of chest pain, but they are limited by subjectivity. This study tested the ability of a semi-objective chest pain score to predict the likelihood of coronary disease. A chest pain questionnaire was given to 250 patients with stable chest pain attending coronary angiography. The answers to three questions were defined as ‘typical’ or ‘atypical’ and summed to give a ‘typical’ score between 0 and 3. Logit analysis was performed based on an age cut-off of 55 years and ‘typical’ score. There were 96 (38%) patients with normal coronary arteries and 154 (62%) with coronary disease. In patients aged under 55 years, the likelihood of coronary disease by ‘typical’ score was 11% (score 0), 30% (score 1), 40% (score 2), 53% (score 3). Similar figures for age 55 years were 39% (score 0), 45% (score 1), 77% (score 2), and 85% (score 3). There is a direct relationship between ‘typical’ chest pain score and the likelihood of coronary artery disease. This scoring system may be useful in the clinical characterization of patients for research, for guiding referral to a cardiologist or for aiding the decision to perform coronary angiography. 2001 Elsevier Science Ireland Ltd. All rights reserved. Keywords: Chest pain; Coronary artery disease; Coronary angiography
1. Introduction Chest pain occurs frequently in the community [1,2] and usually has a benign non-cardiac explanation [3] In deciding which patients should be referred for further investigation, the physician will be guided by the presence of risk factors for coronary disease, the clinical examination, the results of noninvasive investigation, and importantly by the quality of the chest pain. Although chest pain varies widely in character it is usually summarized as either ‘typical’ or ‘atypical’ of *Correspondence author. Cardiothoracic Centre, 6th Floor, East Wing, St Thomas’ Hospital, Lambeth Palace Road, London SE1 7EH, UK. Tel.: 144-20-7928-9292, ext. 6036; fax: 144-20-7960-5680. E-mail address: e [email protected] (E.B. Wu). ]
a cardiac origin. These terms are subjective and rarely defined, which may help to explain why rates for normal coronary anatomy at coronary angiography vary from 7 to 31% [4,5]. Day and Sowton [4] showed that 60% of patients had chest pain that could be related to exertion, while only 16% had pain reproducibly on exertion. The incidence of ‘typical’ pain in this study could be taken as either 16 or 60% and it would clearly be an advantage if ‘typical’ could be defined more precisely. However, the validity of any method of clinical categorisation must be tested against an independent standard, for example coronary angiography. There is preliminary evidence that a semi-quantitative chest pain score rating the degree of being ‘typical’ on a 4-point scale can differentiate patients
0167-5273 / 01 / $ – see front matter 2001 Elsevier Science Ireland Ltd. All rights reserved. PII: S0167-5273( 01 )00382-5
258
E.B. Wu et al. / International Journal of Cardiology 78 (2001) 257 – 264
with normal coronary anatomy and those with coronary artery disease [6] If this model could be validated it might be expected to improve the noninvasive assessment of a patient with chest pain to guide referral to a cardiologist or help determine the need for coronary angiography. Previous work derived the chest pain model retrospectively in sex-matched patients chosen to have either completely normal coronary anatomy or significant coronary disease [6]. The aim of this study was to assess the ability of the model to predict the likelihood of coronary disease prospectively in patients undergoing diagnostic coronary angiography.
2. Methods
2.1. Subjects The day-case lists of three participating consultants were examined between 1st September 1997 and 30th June 1998. Of 829 consecutive patients undergoing day case coronary angiography, 250 had the required inclusion criteria of chest pain for longer than 1 month and no previous evidence of coronary artery disease. Patients were excluded if there were pathological Q waves or anything more than nonspecific ST / T wave changes on the electrocardiogram or regional wall motion abnormalities on the echocardiogram, abnormal coronary arteries demonstrated by previous coronary angiography, or a history of coronary angioplasty or coronary artery bypass grafting. Other exclusion criteria were anything more than mild valve disease, atrial fibrillation, abnormal left ventricular systolic function (fractional shortening ,28% or estimated left ventricular ejection fraction ,50% on echocardiography), left ventricular hypertrophy, and renal failure.
2.2. Procedure Patients granted oral consent and were then interviewed within 8 h of coronary angiography by one author (E.B.W.) who was blinded to the results of the angiogram. A modification of the Master [7] questionnaire was used with the addition of three specific questions previously shown to differentiate normal from abnormal coronary angiograms [6]: (1) ‘‘If you
go up a hill (or another individually appropriate stress) on ten separate occasions, on how many of these do you experience chest pain?’’ The answer to this question was called the reproducibility score; (2) ‘‘If you have the pain ten times in a row, how many happen when you are resting or sitting quietly?’’ The answer to this question was called the rest score; (3) ‘‘How long does the pain usually last?’’ The answers to these questions were dichotomized as either ‘typical’ or ‘atypical’ [6]. For question 1, a reproducibility score of 10 was defined as ‘typical’ and a score of 1–9 was defined as ‘atypical’. For question 2, a rest score of 0 or 1 was defined as ‘typical’ and 2 or more was defined as ‘atypical’. Pain duration of 5 min or less was ‘typical’ and longer than 5 min was ‘atypical’. The answers to these 3 questions were added to give a ‘typical’ chest pain score between 0 and 3 for each patient. The coronary angiogram was performed using the standard Sones or Judkins techniques with multiple orthogonal views. The angiogram was recorded as abnormal if a stenosis judged by eye to be 50% or more of the luminal diameter was shown in at least one main epicardial vessel or a major branch. The angiogram was recorded as normal or near-normal if the most severe stenosis was ,50% of the luminal diameter. For simplicity, patients with an abnormal angiogram were grouped as ‘coronary disease’ and those with normal or near-normal angiograms were grouped as ‘normal anatomy’. The classification of patients with near-normal anatomy as normal is an oversimplification, which was permitted since it was likely to underestimate rather than exaggerate the validity of our results
2.3. Statistics Mean and standard deviation values were calculated. The Student’s t test was used for comparison of continuous variables and the Mann–Whitney U test for non-parametric data. Frequencies of each chest pain characteristic were calculated and odds ratios between those with coronary artery disease and those without were calculated; 95% confidence intervals calculated with the method described by Woolf [8]. A model composed of the ‘typical’ chest pain score and age dichotomized to less than or greater than or equal to 55 years was analyzed by logit regression. The
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259
Table 1 Demographics
Age Duration of pain (months) % males a *
Normal (n596) Mean (S.D.a) (range)
Abnormal (n5154) Mean (S.D.) (range)
58.3 (9.2) (34–80) 34 (50) (2–288) 52%
63 (8.8) (28–86) 25 (32) (1–180) 78%*
S.D., standard deviation. P,0.001.
cut-off of 55 years was chosen based on the results of earlier work [6]. A P value of less than 0.05 was considered to be significant. Statistical analysis was performed using the Statistical Package for Social Sciences for windows, release 7.0.
3. Results
Fig. 1. Diagram of site numbers on the chest wall.
3.1. General Of the 250 patients, 96 (39%) had normal anatomy and 154 (61%) had coronary disease. There were no significant differences in age, but more males had abnormal angiography than females (OR 0.3, 95% CI 0.18–0.52, P,0.001) (Tables 1 and 2). Diabetes was more common in those with coronary artery disease (odds ratio 1.9, 95% CI 0.06–0.66), but there were no significant differences in other coronary risk factors (Table 2).
3.2. Chest pain characteristics The median duration of chest pain was 15 months (range: 2–228 months) in those with normal anatomy and 12 months (range: 1–180 months) (P50.07) in those with coronary disease. Pain at site 5 (Fig. 1) was more common in those with normal coronary anatomy (odds ratio 2.00, 95% CI 1.13–3.53), but there were no other significant differences between
the two groups in the site, radiation, quality and distribution of the chest pain (Tables 3–6). There were no significant differences in precipitating factors including emotional stress, food, lying down or stooping, carrying, or neck movement (Table 7). Relief of chest pain with short acting nitrates was reported more frequently in those with coronary Table 3 Pain characteristics — site (see also Fig. 1) Site
Normal (n596)
Abnormal (n5154)
Odds ratio
95% CI a
1 2 3 4 5 6 7 8 9
11 (11%) 26 (27%) 12 (13%) 22 (23%) 74 (76%) 33 (34%) 11 (12%) 53 (55%) 21 (22%)
20 31 24 35 95 61 14 73 34
0.86 1.45 0.76 1.00 2.00 0.79 1.28 1.34 0.98
0.39–1.88 0.80–2.64 0.36–1.61 0.54–1.83 1.13–3.53* 0.46–1.34 0.56–2.95 0.80–2.23 0.53–1.80
a *
(13%) (20%) (16%) (23%) (62%) (39%) (9%) (48%) (22%)
CI is confidence interval. P,0.05.
Table 2 Coronary risk factors Risk factors
Normal (n596)
Abnormal (n5154)
Odds ratio
95% CI
Cholesterol Diabetes Hypertension Smoking Family history
38 3 37 31 43
67 22 67 65 63
0.84 0.19 0.78 0.64 1.15
0.50–1.40 0.06–0.66* 0.46–1.31 0.38–1.10 0.69–1.92
*
P,0.05.
(40%) (3%) (39%) (32%) (45%)
(44%) (29%) (44%) (42%) (41%)
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260 Table 4 Pain characteristics — radiation Radiation
Normal (n596)
Abnormal (n5154)
Odds ratio
95% CI a
Back Left arm Right arm Neck Legs Abdomen
14 40 13 19 3 1
11 54 32 30 4 0
2.19 1.30 0.59 1.01 1.19
0.95–5.05 0.77–2.19 0.29–1.19 0.53–1.91 0.26–5.43
a
(14%) (42%) (14%) (20%) (3%) (1%)
(7%) (35%) (21%) (20%) (3%) (0%)
CI is confidence interval.
Table 5 Quality of chest pain Quality
Normal (n596)
Abnormal (n5154)
Odds ratio
95% CI a
Heavy Gripping Stabbing Burning
28 (29%) 36 (38%) 12 (13%) 6 (6%)
32 62 14 6
1.57 0.89 1.43 1.64
0.87–2.83 0.53–1.50 0.63–3.23 0.51–5.25
a
(21%) (40%) (9%) (4%)
artery disease [93 (60%)] than those with normal anatomy [42 (43%) (odds ratio 0.5, 95% CI 0.30– 0.84, P50.009)] (Table 8). However, relief within 5 min occurred in only 30 (31%) of those with normal coronary anatomy as compared to 81 (53%) with coronary artery disease (odds ratio 0.4, 95% CI 0.24– 0.69, P50.003). Improvement of pain with rest was significantly more common in those with coronary
CI is confidence interval.
Table 6 Distribution of chest pain and chest wall tenderness Distribution
Normal (n596)
Abnormal (n5154)
Odds ratio
95% CI a
Generalised One-pointed Tenderness
44 (45%) 19 (20%) 3 (3%)
78 (50%) 28 (18%) 2 (1%)
0.81 1.10 2.43
0.49–1.35 0.57–2.09 0.40–14.80
a
CI is confidence interval.
Table 7 Precipiating factors Factor
(Normal (n596)
Abnormal (n5154)
Odds ratio
95% CI a
Carrying Food Lying down / stooping Emotional stress Inspiration Movement
14 18 17 18 6
29 20 21 23 2 1
(19%) (13%) (14%) (15%) (1%) (1%)
0.73 1.44 1.28 1.30 5.01 3 (2%)
0.36–1.46 0.72–2.87 0.64–2.54 0.66–2.55 1.00–25.35
a
(14%) (19%) (18%) (19%) (6%)
CI is confidence interval.
Table 8 Relieving factors Relieving factors
Normal (n596)
Abnormal (n5154)
Odds ratio
95% CI a
Rest Milk / antacids GTN Relief #5 min
56 7 42 30
125 (82%) 7 (5%) 93 (61%) 81 (53%)
0.32 1.62 0.50 0.40
0.18–0.56* 0.55–4.78 0.30–0.84* 0.24–0.69*
a *
CI is confidence interval. P,0.05.
(58%) (7%) (43%) (31%)
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261
Table 9 Assiciated symptoms Associated symptoms
Normal (n596)
Abnormal (n5154)
Odds ratio
95% CI a
Tingling in fingers Dizziness Palpitations Dyspnoea
47 35 37 67
47 28 37 97
2.14 2.54 1.95 1.31
1.27–3.62* 1.42–4.55* 1.12–3.39* 0.76–2.25
a *
(49%) (36%) (39%) (69%)
(31%) (18%) (24%) (63%)
CI is confidence interval. P,0.05.
artery disease, occurring in 125 (81%) compared with 56 (58%) of those with normal anatomy (odds ratio 0.32, 95% CI 0.18–0.56, P,0.001). There was no difference between the two groups in the frequency of associated shortness of breath, but dizziness, palpitations and paraesthesiae of the fingers were all significantly more frequent in patients with normal anatomy (Table 9).
3.3. Differentiating factors Ten patients (6%) with coronary disease and seven (7%) with normal anatomy could not answer all three questions. In the remaining 89 patients with normal anatomy and 144 with coronary disease, there were major differences in the answers given to the three question model. A consistent relation between chest pain and exercise (reproducibility score 10) was significantly less common in patients with normal anatomy (n534) (38%) than in those with coronary disease (n5104) (72%) (odds ratio 0.23, 95% CI 0.13–0.41). Infrequent rest pain (rest score 0 or 1) was less likely in patients with normal anatomy (n536) (40%) than in those with coronary disease (n5105) (73%) (odds ratio 0.26, 95% CI 0.15–0.45). Short pain episodes lasting 5 min or less were less common in those with normal anatomy (n557) (59%) than with coronary disease (n5111) (72%) (odds ratio 0.53, 95% CI 0.31–0.91) (Table 10).
Table 11 The logit model for the prediction of normal vs. abnormal coronary angiogram Chest pain score and age
Coefficient
Z value
S.E.
Age (,55 years vs. $55 years) Reproducibility (10 vs. 1–9) Duration (#5 min vs. .5 min) Rest score (0 or 1 vs. 2–10)
1.39 0.98 20.53 20.77
3.84 2.71 21.62 22.1
0.36 0.36 0.33 0.37
A logit analysis was performed using age ($55 years vs. ,55 years) and the three symptoms from the symptom model categorized as described above as either ‘typical’ or ‘atypical’. A gradation in the likelihood of coronary disease was given by the aggregate number of ‘typical’ responses to the three questions as shown in detail in Table 11. For example, patients aged ,55 years with no ‘typical’ symptoms had an 11% chance of coronary artery disease while those aged 55 years or more with three ‘typical’ responses had an 85% chance of coronary artery disease (Table 12). Of the nine patients aged ,55 years with no ‘typical’ responses, only one had coronary artery disease. This patient had occlusion of the left anterior descending artery after the first diagonal branch and a 90% lesion in the mid-right coronary artery. He stopped after 4 min of a standard Bruce protocol exercise test with chest pain but no significant ST segment changes. He remains pain-free on antianginal therapy 1 year after angiography.
Table 10 Reproducibility, rest score, duration Chest pain scores
Normal (n596)
Abnormal (n5154)
Odds ratio
95% CI a
Reproducibility (10) Rest score (0 or 1) Duration (#5 min)
34 (38%) 36 (40%) 57 (59%)
104 (72%) 105 (73%) 111 (72%)
0.23 0.26 0.53
0.13–0.41* 0.15–0.45* 0.31–0.91*
a *
CI is confidence interval. Statistically significant at 95%, or P,0.05.
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Table 12 Probability of abnormal coronary angiogram (CA) based on pain characteristics and age Number of typical symptoms
Likelihood of abnormal CA (%)
Actual incidence (%)
,55 years of age 0/3 1/3 2/3 3/3
11 20–28 35–46 59
1 / 9 (11) 3 / 10 (30) 6 / 15 (40) 9 / 17 (53)
#55 years of age 0/3 1/3 2/3 3/3
37 50–61 68–77 85
9 / 23 17 / 38 41 / 53 58 / 68
4. Discussion A simple model based solely on age and three chest pain characteristics can stratify the likelihood of coronary disease prospectively in patients admitted for day-case diagnostic coronary angiography. The likelihood rose from 11 to 30 to 40% and finally to 53% in patients aged under 55 years according to whether the number of ‘typical’ responses was 0, 1, 2 or 3. Similar figures for ages equal to or greater than 55 years were 35, 45, 77 and 85%. The conventional assessment of pain as either ‘typical’ or ‘atypical’ of a cardiac origin is highly subjective and expressions like ‘typical with atypical features’ are so vague as to be almost meaningless. We suggest instead that chest pain could be characterized according to the number of ‘typical’ responses to give a ‘typical’ chest pain score between 0 and 3. This score could be used to standardize descriptions of chest pain in research studies for example of patients with normal coronary anatomy. Furthermore, we showed that the likelihood of coronary disease was directly related to the number of typical responses. This suggests that the score could also be of clinical use. Together with the results of noninvasive testing, it could aid in stratifying the need for coronary angiography. It might be of even greater use in the outpatient clinic where 11–27% only of patients with chest pain have evidence of cardiac disease [3,9]. These possibilities would need to be tested further in larger populations. The importance of clinical assessment in outpatients has been shown by Pryor et al. [10] who demonstrated in 1030 consecutive outpatient referrals that the clinician’s
(39) (45) (77) (85)
initial clinical judgement was better than exercise tolerance testing in predicting coronary anatomy and 3-year outcome. Other authors have differentiated cardiac and non-cardiac chest pain using a 26 question psychological model [11]. McCroskery et al. [12] demonstrated that the Millon Behavioural Health Inventory Questionnaire could discriminate between those with and without coronary artery disease in patients listed for coronary angiography. It is possible that a combination of our three-question chest pain model and psychological questions could improve stratification of the likelihood of coronary disease. The chest pain model is based on three questions previously identified by a logit analysis of selected patients with either significant coronary disease or completely normal angiograms. These questions consider the relationship with exercise (reproducibility score), the number of episodes at rest (rest score) and the average perceived duration of pain episodes. These characteristics are consistent with subjective clinical experience and at first sight seem obvious. However, although we know that cardiac pain is precipitated by exercise [13], what constitutes a reproducible relationship to exercise has not previously been defined. Thus, we previously showed [6] that 94% of patients with normal anatomy had chest pain thought by the cardiologist to be related to exercise but in only 38% was it reproducibly related to exercise as defined by the chest pain model. Other authors also showed that chest pain with a poor relationship to exercise or occurring in episodes of long duration are associated with normal coronary anatomy [4]. We showed that site, radiation and quality of the
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chest pain did not differentiate patients with normal and abnormal angiograms. Furthermore, a number of features such as localization of chest pain in a small region, sometimes thought to suggest non-cardiac pain [14], did not in fact differentiate our patients. This is in agreement with previous work [6]. Dizziness and digital paraesthesiae were more common in patients with normal anatomy [11], but occurred too frequently in those with coronary disease to be clinically useful.
4.1. Limitations The model alone cannot be used as a reliable predictor of normal coronary anatomy since one patient with coronary disease was misclassified. However, this patient had chest pain early during Bruce protocol exercise. This underlines that the model must be interpreted in the context of the whole noninvasive assessment. The questionnaire is no more than semi-objective. However, this is not as major a limitation as it first seems since the statistically determined cut-off between ‘typical’ and ‘atypical’ is at extremes of the scoring scales. A patient is likely to be able to recall whether he or she experiences pain every time he is subjected to a particular stressor or whether pain occurs almost never at rest. Had the statistically determined threshold been at 7 or 8 times out of 10 its accuracy might have been more in question. A small number of patients were unable to answer the questions adequately. We did not use quantitative analysis of coronary lesions nor intravascular ultrasound, but confined ourselves to the same method of analysis as used in routine clinical practice. Furthermore, we used an imperfect cut-off between our two clinical groups. Some patients with a coronary stenosis at around 50% have no evidence of objective myocardial ischaemia while others may have significant ischaemia. It is therefore possible that some patients in our normal group may have had myocardial ischaemia and others in the coronary group may have had no ischaemia. These potential errors of classification are unlikely to be numerous and in any case would have tended to underestimate rather than exaggerate the significance of our results.
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4.2. Conclusion A chest pain model previously derived in selected patients using logit analysis has been tested prospectively in patients having day case coronary angiography. This model allows a semi-objective classification of chest pain avoiding some of the imprecision of conventional descriptions such as ‘typical’ or ‘atypical’. There is a direct relationship between the ‘typical’ chest pain score and the likelihood of coronary disease suggesting that it might be clinically useful. As well as improving the clinical description of patients for research studies, this score could be useful for defining guidelines for referral from the community to a cardiologist and could also help in determining the need for coronary angiography.
Acknowledgements Financial information: Dr Wu was supported by a grant from the Special Trustees of Guy’s and St Thomas’ Hospitals
References [1] LaCroix AZ, Haynes SG, Savage DD, Havlik RJ. Rose questionnaire angina among United States black, white, and Mexican– American women and men. Prevalence and correlates from the second National and Hispanic Health and Nutrition Examination Surveys. Am J Epidemiol 1989;129:669–86. [2] Hannay DR. The ‘iceberg’ of illness and ‘trivial’ consultations. J R Coll Gen Pract 1980;30:551–4. [3] Kroenke K, Mangelsdorff AD. Common symptoms in ambulatory care: incidence, evaluation, therapy, and outcome. Am J Med 1989;86:262–6. [4] Day LJ, Sowton E. Clinical features and follow-up of patients with angina and normal coronary arteries. Lancet 1976;2:334–7. [5] Bass C, Jackson G. Angina with normal coronary arteriograms. Clinical status at one year. Archives des Maladies du Coeur et des Vaisseaux 1983;76:237–45. [6] Cooke RA, Smeeton N, Chambers JB. Comparative study of chest pain characteristics in patients with normal and abnormal coronary angiograms. Heart 1997;78:142–6. [7] Master AM. The spectrum of anginal and non cardiac pain. J Am Med Assoc 1964;187:894–9. [8] Gardner MJ, Altman DG. In: Statistics with confidence — Confidence interval and statistical guidelines, BMJ Publishers, 1989, p. 53. [9] Jain D, Fluck D, Sayer JW, Ray S, Paul EA, Timmis AD. Ability of a one-stop chest pain clinic to identify patients with high cardiac risk in a district general hospital. J R Coll Physicians Lond 1997;31:401–4.
264
E.B. Wu et al. / International Journal of Cardiology 78 (2001) 257 – 264
[10] Pryor DB, Shaw L, McCants CB, Lee KL, Mark DB, Harrell Jr FE, Muhlbaier LH, Califf RM. Value of the history and physical in identifying patients at increased risk for coronary artery disease. Ann Intern Med 1993;118:81–90. [11] Serlie AW, Duivenvoorden HJ, Passchier J, ten Cate FJ, Deckers JW, Erdman RA. Empirical psychological modeling of chest pain: a comparative study. J Psychosom Res 1996;40:625–35. [12] McCroskery JH, Schell RE, Sprafkin RP et al. Differentiating anginal patients with coronary artery disease from those with normal coronary arteries using psychological measures. Am J Cardiol 1991;67:645–6.
[13] Costa PT, Zonderman AB, Engel BT, Baile WF, Brimlow DL, Brinker J. The relation of chest pain symptoms to angiographic findings of coronary artery stenosis and neuroticism. Psychosom Med 1985;47:285–93. [14] Chambers J, Bass C. Chest pain with normal coronary anatomy: a review of natural history and possible etiologic factors. Prog Cardiovasc Dis 1990;33:161–84.