Article, Cardiology

Prognostic value of the Thrombolysis in Myocardial Infarction risk score in a unselected population with chest pain. Construction of a new predictive model

Original Contribution

Prognostic value of the Thrombolysis in Myocardial Infarction risk score in a unselected population with chest pain. Construction of a new predictive modeli

Francisco J. Garcia-Almagro MDa,?, Juan R. Gimeno MDa, Manuel Villegas MDa, Jose Hurtado MDa, Francisca Teruel MDa, Maria C. Cerdan MDa,

Josefa Gonzalez-Carrillo MDa, Domingo Pascual MDa,

Miguel Rodriguez-Barranco PhDb, Mariano Valdes PhDa

aCardiac Department, University Hospital Virgen de la Arrixaca, 30120 El Palmar, Murcia, Spain

bEpidemiology Department, General Section of Public Health, Murcia, Spain

Received 4 June 2007; revised 20 July 2007; accepted 21 July 2007


Introduction: The Thrombolysis in Myocardial Infarction risk score (TRS) has proven to be a useful and simple tool for risk stratification of patients with chest pain in intermediate- and high-risk populations. There is little information on its applicability in daily clinical routine with unselected populations.

Aims: The aims of the study were to prospectively analyze the predictive value of the TRS in a heterogeneous population admitted for chest pain and to construct where possible a new modified model with a greater prognostic capacity.

Population and Methods: Seven hundred eleven consecutive patients were admitted over a 1-year period to the cardiology unit for chest pain without ST-segment elevation. Thrombolysis in Myocardial Infarction risk score variables, relevant medical history variables, in-hospital examination results, and therapy information were collected. Cardiac events at 1 and 6 months were recorded.

Results: Seventy-one (9.8%) patients had a compound event (myocardial infarction/revascularization/ cardiac death) at 6 months. On multivariate analysis, the variables associated with cardiac events were left ventricular ejection fraction (EF) of b35% (hazard ratio [HR] = 2.9, P = .002), diabetes (HR = 1.8, P = .02), and TRS (HR = 1.3, P = .007). Events at 6 months were 2.3% for a TRS of 0/1, 4.2% for 2, 10.2% for 3, 11.0% for 4, and 18.7% for a score of more than 5. A new modified scale was constructed to include EF and diabetes as independent variables, and this yielded an increase of 44% in the combined event at 6 months per score unit increase (HR = 1.44, P = .001). The modified scale showed a greater predictive capacity than the original model.

Conclusions: The TRS is an important short- and long-term prognostic predictor when applied to an unselected population consulting for chest pain. The inclusion of diabetes and EF as variables in the model increases predictive capacity at no expense to simplicity.

(C) 2008

? Dr Gimeno was supported by a grant from Merck Sharp and Dhome, Madrid, Spain.

* Corresponding author. Tel.: +34 629488658; fax: +34 868951279.

E-mail address: [email protected] (F.J. Garcia-Almagro).

0735-6757/$ – see front matter (C) 2008 doi:10.1016/j.ajem.2007.07.011


Chest pain is one of the most common reasons for consultation in emergency units, accounting for between 5% and 10% of the total [1-3]. Of these patients, between 10% and 20% present with a high risk of complications and would benefit from admission and aggressive treatment. The association of different clinical variables, electrocardiogram (ECG), and laboratory markers with an unfavorable evolu- tion has been shown widely [4-6].

In this context, Antman et al [7] developed the Thrombolysis In Myocardial Infarction risk score (TRS), a scoring system with 7 risk variables in patients with unstable angina or acute myocardial infarction (AMI) without ST elevation. This scale was created by retro- spectively applying multivariate statistic models to the populations of 2 tests with heparins: TIMI 11B [8] and Efficacy and Safety of Subcutaneous Enoxaparin in Unstable Angina and Non-Q-wave Myocardial Infarction (ESSENCE) [9]. It has since been validated in various studies such as CURE, PRISM-PLUS, and TACTICS-TIMI 18, among others [10,11], in which it has proved capable of predicting both the prognosis and the response to new therapies in both the short and long term.

However, there is little information on its applicability to daily clinical practice beyond the trials in which it was developed or to very selected populations [12]. The presence of ECG changes and the elevation of cardiac markers were inclusion criteria in these studies; however, many of the patients admitted to cardiology units with chest pain do not present with such a homogeneous or high-risk profile [13]. The aims of the present study were (1) to analyze the prognostic value of the TRS in a heterogeneous population admitted to a cardiology unit for chest pain; and (2) to construct if possible a new predictive model based on the TRS including other variables with independent prognostic value.

Population and methods

The study population was made of consecutive patients with chest pain suggestive of an ischemic origin and admitted to the cardiology unit between May 1, 2003, and April 30, 2004. The only exclusion criterion was presenta- tion of chest pain and persistent ST-segment elevation. After clinical evaluation, the patients received serial ECGs and determination of cardiac markers at the emergency depart- ment (ED) (with at least 1 blood extraction more than 6 hours after the onset of pain) and echocardiogram within 72 hours of admission. An ischemia test (treadmill exercise test or dobutamine stress echocardiogram, with or without single- photon emission Computed tomography imaging) was done where appropriate. On admission, they were given antiag- gregation and subcutaneous enoxaparin in anticoagulant doses, in the absence of contraindications. All decisions

regarding management and treatment were made according to the criteria of the responsible cardiologist.

The main epidemiological aspects of the population and the variables of clinical manifestation, including character- istics of pain, were collected. Pain was defined as typical angina, suggestive or unspecific based on the score by Geleinjse et al [14]. Electrocardiograms were classed according to the absence or presence of pain and ECG changes–elevation or depression in the ST segment by

0.5 mm in any lead. Measurements of cardiac enzymes such as total creatine kinase (CK), MB fraction (CK-MB), and troponin I level were determined. Normal values were based on the center’s biochemistry laboratory (CK, b150 U/L; CK-MB, b2.5 U/L and b5% of total CK; TnI, b0.1 ng/mL). Acute myocardial infarction was established as an increase in CK and CK-MB levels to twice the reference value and to 6 times the value for TnI, based on the consensus for redefining infarction [15,16]. We recorded the treatments performed during admission and the results of the different ischemia, echocardiography, and cardiac catheterization tests. The appearance of complications such as death, infarction, recurrent ischemia, and bleeding was recorded, the last one defined according to criteria of the TIMI trials [12,17].

A prospective calculation of the TRS was made for each patient. This yielded between 0 and 7 possible points according to the simple mathematical sum of each of the following characteristics: age of 65 years; existence of 3 or more classical risk factors (hypertension, hypercholesterole- mia, diabetes mellitus, smoking, or family history of ischemic heart disease); previous significant coronariopathy (stenosis of >=50%); aspirin (acetylsalicylic acid [ASA]) consumption in the previous 7 days; at least 2 episodes of angina in the previous 24 hours; elevation of cardiac necrosis markers; and ST deviations of at least 0.5 mm [7].


Clinical follow-up was done at 1 and 6 months after discharge by personal interview or telephone to record data relating to the control of risk factors, adherence to treatment, functional class, and appearance of symptoms or complica- tions. The incidence of the combined event of Cardiovascular death, infarction, and need for revascularization was recorded during follow-up.

Statistical analysis

Data are expressed as mean +- SD of the mean (range) or frequency (percentage). Four possible events during follow- up were defined: cardiovascular death (sudden death, death from heart failure, or procedure-related death); revascular- ization; AMI; and combined event, defined as the occurrence of any of the 3 mentioned events. For each type of event, a Cox univariate proportional risk model was constructed with each of the following episode-related variables: age, sex,

previous revascularization, previous AMI, TRS items, ejection fraction (EF; b35%, 35%-44%, 45%-54%, 55%- 89%), characteristics of pain (unspecific, angina/suggestive), changes in ECG with pain, final diagnosis, revascularization during admission, diabetes, and number of affected vessels in the coronary angiogram. The assumption of proportional risks was evaluated by graph. Cox multivariate regression models were used to study the predictive variables for the occurrence of events. A New indicator (modified TRS [TRSm]), which included the variables associated with the combined event at a significance level of ? = .05, was constructed. To study its predictive capacity, a Cox multi- variate regression model was again constructed with substitution of the TRS with the new TRSm indicator.

Table 2 Results of the in-hospital examinations, treatments,

and relevant events


Ischemia test Positive Negative Inconclusive

Coronary angiogram

  1. Vessel disease
  2. Vessel disease
  3. Vessel disease Nonsignificant lesions Other lesions


Aspirin + clopidogrel

Aspirin + clopidogrel + tirofiban Revascularization

Percutaneous Surgery

Recurrent Ischemia AMI a

Bleeding Minor Major

In-hospital death Sudden death Heart failure death

Death related to revascularization Noncardiac death

a Nonrelated to the episode that lead to admission.


314 (44.2%)

114 (36.3%)

140 (44.6%)

60 (19.1%)

326 (45.9%)

99 (30.4%)

83 (25.5%)

69 (21.2%)

67 (20.6%)

8 (2.5%)

172 (24.2%)

449 (63.2%)

99 (13.9%)

210 (29.5%)

182 (86.7%)

28 (13.3%)

85 (12.0%)

14 (2.0%)

16 (2.2%)

10 (1.4%)

15 (2.1%)

4 (26.7%)

4 (26.7%)

4 (26.7%)

3 (20.0%)

A multivariate logistic regression model was adjusted for the new indicator (TRSm) in which the variable response was the occurrence of the combined event, and this was compared with the same model including the TRS. The Akaike information criterion and bayesian information criterion (BIC) were used to compare the efficiency of adjustment of the 2 models. All the multivariate regression models were constructed using a backward selection procedure. Included in the initial model were the variables yielding P b .10 in the univariate analysis. The level of confidence for the construction of Confidence levels was set at 95%. Statistical analysis was done with the Stata software package (StataCorp 2001, Stata Statistical Software: Release 7.0; Stata Corporation, College Station, Tex).


The patients’ baseline characteristics are summarized in Table 1. Chest pain was typical or suggestive of anginal pain

in 598 (84.1%) cases and unspecific in the rest. There were ECG recordings coinciding with pain in 506 (71.2%) patients, and dynamic changes were observed in 158 (31.0%) of them. Serial TnI level was shown to be above normal limit in 313 (44.0%) patients.

Twenty-eight (3.9%) patients underwent surgical revas- cularization and 182 (25.6%) percutaneous coronary angio- plasty. Details of treatment and complementary tests are summarized in Table 2.

As far as complications are concerned, 85 (12.0%) patients presented with recurrent ischemia, 14 (16.5%) of them with ECG changes. Fourteen (2.0%) patients had an infarction


474 (66.7%) during their hospital stay, and there were 15 (2.1%) deaths–4


192 (27.0%) sudden deaths, 4 due to heart failure, 3 in the postsurgery


45 (6.3%) period, 1 during catheterization, and 3 not cardiac related.

Hypertension Diabetes

459 (64.6%)

227 (31.9%) There were 16 (2.2%) episodes of minor bleeding and 10


338 (47.5%)

(1.4%) major episodes (Table 2). The final diagnoses at


345 (48.5%)

discharge were AMI in 146 (20.5%) cases, unstable angina in

Family history of IHD

160 (22,5%)

231 (32.5%), secondary angina in 26 (3.7%), other causes of a

Prior AMI

192 (27.0%)

Cardiac origin in 119 (16.7%), and noncardiological pain in

Prior revascularization

156 (21.9%)

189 (26.6%) cases.

ECG dynamic changes

158 (22.2%)

TnI-positive EF (%)

313 (44.0%)

56.1 +- 11.6

3.1. Follow-up and events

A complete clinical follow-up was achieved in 661 (93.0%) patients. At 6 months, 100 (15.1%) patients were

Table 1 Baseline characteristics of the patients studied

NYHA indicates New York Heart Association; IHD, ischemic heart disease.


66 +- 13

463 (65.1%)


Age (y) Sex (male)

NYHA functional class

1 mo

6 mo


38 (5.3%)

100 (15.1%)


14 (1.9%)

36 (5.1%)


3 (0.4%)

10 (1.4%)

Cardiac death

12 (1.7%)

25 (3.5%)


29 (4.1%)

771 (9.8%)


Excluded revascularization and AMI during first admission.

readmitted, 36 (5.1%) required coronary revascularization,

Table 3 Cardiac events at 1 and 6 months of follow-up

10 (1.4%) had AMI, and there were 25 (3.5%) deaths of a cardiovascular origin. In total, 29 (4.1%) patients presented with the combined death/AMI/revascularization event at 1 month and 71 (9.8%) at 6 months (Table 3).

In the multivariate analysis, the variables related to the combined event were the TRS (hazard ratio [HR] = 1.3 [1.0- 1.6], P = .007), EF of less than 35% (HR = 2.9 [1.5-5.4], P =

.002), and diabetes (HR = 1.8 [1.0-3.1], P = .02). An

individual breakdown of the events is shown in Table 4.

In multivariate analysis, the combination of ASA and clopidogrel was compared with the triple therapy with the addition of tirofiban, and a protective effect for the occurrence of the combined event was associated with the triple therapy (HR = 0.47 [0.19-1.13], P = .09), although it did not reach statistical significance.

Table 4 Variables associated with the occurrence of cardiac events

Fig. 1 Distribution of patients according to TRS.

3.2. Thrombolysis in Myocardial Infarction risk score

Distribution of the TRS in the population is shown in Fig. 1. The model proved to be an important predictor of risk. Patients with higher scores presented more often with the combined event: 0.6%, 2.1%, 4.8%, 6.1%, and 7% in the first month, for a TRS of 0/1, 2, 3, 4, and more than 5,

respectively, and 2.3%, 4.2%, 10.2%, 11%, and 18.7% at 6 months (HR per unit increase = 1.3 [95% confidence interval, 1.0-1.6], P = .007)] (Fig. 2).

Univariate analysis

Multivariate analysis


HR (95% CI)


HR (95% CI)

Combined event



1.5 (1.3-1.7)


1.3 (1.1-1.6)

EF b35% b


3.9 (2.1-7.3)


2.9 (1.5-5.4)



2.5 (1.6-3.9)


1.8 (1.1-3.1)

Unstable angina c


7.8 (3.0-19.8)


2.7 (1.0-7.2)




1.5 (1.2-1.8)


1.3 (1.0-1.6)

Unstable angina c


12.4 (2.9-52-8)


7.9 (1.8-35.0)


Age d


1.06 (1.00-1.11)


1.05 (1.00-1.11)



4.0 (1.3-11.9)


3.5 (1.2-10.3)

Cardiac death

Age d


1.05 (1.02-1.09)


1.04 (1.01-1.08)



5.1 (2.6-10.1)


5.3 (2.4-11.7)

EF (%)






0.45 (0.15-1.36)


0.47 (0.16-1.40)



0.22 (0.07-0.65)


0.23 (0.08-0.68)



0.12 (0.05-0.29)


0.16 (0.07-0.38)

CI indicates confidence interval.

a Increase per unit of TRS.

b Compared with EF N35%.

c Final diagnosis compared with noncardiac origin.

d Per year increase in age.

Fig. 2 Cardiac events (AMI/revascularization/cardiac death) at 1 and 6 months according to TRS.

3.3. Modified TRS

In the univariate analysis, all but 1 of the TRS variables showed a significant association with the occurrence of the combined event, with the exception of “>=2 episodes of angina in the previous 24 hours” (HR = 1.3 [0.8-2.1], P =

.185]. Thus, a new risk scale was constructed to exclude this variable and include other independent risk factors such as diabetes and EF. This TRSm was therefore made up of 8 variables, with a scoring system as follows:

  1. one point if age is at least 65 years,
  2. one point if with presence of 3 or more risk factors for coronary disease (hypertension, hypercholester- olemia, diabetes, smoking or family history of is- chemic heart disease),
  3. one point if with presence of known coronary disease (stenosis >=50% in previous coronary angiogram),
  4. one point if with ASA consumption in the previous 7 days,
  5. one point if with ST-segment deviation of at least

0.5 mm in the presentation ECG,

  1. one point if with elevation of cardiac markers,
  2. one point if patient is diabetic–independent of b, and
  3. two points if EF if less than 35% and 1 point if EF ranges from 35% to less than 45%.

The total score was still a simple mathematical sum but now ranging from 0 to 9. After adjusting the multivariate logistic regression model for the TRSm, we noted a 44% increase in occurrence of the combined event per unit increase on the scale (HR = 1.44 [1.19-1.73], P b .001). Comparison of the 2 indicators, TRS and TRSm, using the Akaike information criterion and BIC (see “Statistical analysis” in the methods section) showed that the latter yielded a better predictive adjustment than the original TRS (difference of 13.387 in the BIC between both). Moreover, the simultaneous presence of the 2 scales in the multivariate model yielded a significant association with the combined event for the TRSm (HR = 1.69 [1.28-2.22], P b .001),

whereas the coefficient of the TRS did not reach significance (HR = 0.87 [0.62-1.19], P = .389).

A third model adding only diabetes as an independent variable to the traditional TRS, without considering EF, was also tested. Predictive value of this model was significantly better than traditional TRS (difference of 6.9 in the BIC between TRS and TRS + diabetes, P b .001) but worse than the proposed TRSm (difference of 6.5 in the BIC between TRS + diabetes and TRSm, P b .001).


In this prospective study the TRS is confirmed as an important short- and long-term prognostic predictor, even in unselected populations with chest pain; it establishes a risk curve ranging from a low probability of events with the lower scores (around 4% at 6 months with TRS b3) to almost 20% at the opposite extreme. Furthermore, a new modified scale is obtained which, with the addition of presence of diabetes and left ventricular EF to the other variables, increases prognostic capacity at no expense to the simplicity of the model.

Risk stratification

Various methods of prognostic stratification have been developed for the management of chest pain. Certain algorithms of risk prediction such as that of Goldman or Pozen et al [18] are complex and little used. In the context of immediate assessment, the integration of clinical variables and complementary examinations at the patient’s bedside has been sought from the moment the patient is admitted to the ED. One of the most widespread classifications is one proposed a decade ago by Hamm and Braunwald [19] for unstable angina, subsequently modified with the addition of enzyme elevation as a clinical criterion. The PEPA study [20] was developed in our midst and defined the risk of death or infarction at 90 days in patients with acute coronary syndrome (ACS) without ST-segment elevation by means of clinical data and ECG. A new validated model has recently been published with data from the Global Registry of Acute coronary events [21] with prediction of overall mortality at 6 months for any type of ACS, which is applied with 9 prognostic variables weighted by computer calculation.

Thrombolysis of Myocardial Infarction risk score

The present study prospectively includes a very wide spectrum of consultations for chest pain and confirms the capacity of the TRS for discriminating the probability of events in routine clinical practice. In fact, the 1-month incidence of the combined event of death, infarction, and need for revascularization ranges from less than 1% for a score of 0/1 to 7% if more than 5 and furthermore maintains

its prognostic value over the long term, with 2% of events at 6 months for the lowest TRS and 20% for the highest.

The fact that this is a more heterogeneous population might explain the general prognosis being slightly better than that published in the original study [7], although it is also true that high-risk patients are included (mean age, 66 years; more than 30% diabetic; 27% with former infarction, 22% previously revascularized, and almost 45% with raised troponin levels). This difference may also be justified by a higher rate of invasive strategies (46% of the patient total went to diagnostic catheterization, and 30% were revascu- larized) and of the combination of antiplatelet therapies (ASA and clopidogrel were associated in 63% of cases and tirofiban in 14%), thus attenuating the risk of events. This idea is reinforced when comparing the results with those from medication trials such as CURE [10] (approximately 3% of events in 9 months for a TRS of 0/1 and 19% for 6/7 in the treated arm).

Modified TRS

The inclusion of diabetes and EF as variables in the scale improves prognostic capacity. It is shown that the presence of diabetes alone yields a poorer prognosis in ACS. In the OASIS Registry [22], the 2-year mortality rate was the same in Diabetic patients without previous disease and those with established cardiovascular disease who were not diabetic. The recent SYMPHONY study [23] revealed almost twice the 1-year mortality rate among diabetic patients after an ACS, and it also seems that these differences are maintained despite more aggressive treatments [24]. The predictive contribution of diabetes in the TRS might be greater if it were not integrated together with the other risk factors into a single common variable.

On the other hand, EF is strongly related to survival and can also be obtained easily in the patient’s initial evaluation. Sabia et al [25] found up to 4 times more cardiac events in 2 years in patients with chest pain and left ventricular systolic

Fig. 3 Probability of occurrence of combined cardiac event at 6 months and TRS in 3 groups of EF (based on a multivariate model).

dysfunction, evaluated by 2-dimensional echocardiogram in the ED, than those with a preserved EF.

In the present study, the multivariate analysis showed that EF also added prognostic value to the TRS (Fig. 3). The excellent result of integrating these 2 variables lies possibly in the fact that they predict different complications. The TRS was developed to evaluate the risk of ischemic episodes (including infarction and the need for revascularization in the combined event), whereas the factors predicting mortality are usually related to left ventricular dysfunction (worse Killip index, severe hypotension, etc).


The study includes certain potential limitations such as the fact that the distribution of the TRS is not entirely homogeneous (b5% of individuals had a score of 6/7) despite the size of the population (N = 711) and may have influenced the frequency of events in this group. There are some differences in definitions and populations with respect to the TRS original article that could explain some of the findings of the present work. The aim of the study was to verify the Predictive power of the TRS in a nonselected population with chest pain. The small number of patients enrolled led us to include revascularization together with death and myocardial infarction. One- and 6-month event periods were used, and, finally, a 6-month period was used for the statistical analysis.

There are also differences in the determination of enzymes with respect to the original and subsequent validation tests. In the present study, TnI was determined in all patients together with CK and CK-MB. The greater sensitivity shown by the former [6,26] could have produced differences in the risk score. It is also worth mentioning that the analysis does not include quantitative data on the level of these enzymes (as in the original study), nor does it evaluate the contribution of other biologic markers such as C-reactive protein.

Finally, it must be remembered that this is a single- center-based study, and results should be extrapolated carefully to other environments with different populations and clinical management schemes. Further studies would be welcomed for verification of this new score.


The TRS is an important short- and long-term prognostic predictor when applied to an unselected population consult- ing for chest pain. The inclusion of diabetes and EF as variables in the model shows an increase in predictive capacity at no expense to the simplicity of the model. We have, therefore, a simple and useful tool for risk stratification

in these patients, which enables us to decide on the most appropriate Management strategy.


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