ST elevation myocardial infarction risk stratification and prognosis

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Editor-In-Chief: C. Michael Gibson, M.S., M.D. [1]

Overview

Five variables explain 90% of the prognosis in STEMI: Advanced age,sinus tachycardia, reduced systolic blood pressure, heart failure or Killip class of two or greater, and anterior myocardial infarction location. Two main risk-stratification scores are used when assessing a patient with ST elevation MI and acute coronary syndromes; the TIMI Risk Score (for STEMI), and the GRACE risk score (for acute coronary syndrome.

Prognosis

Factors Associated with a Poor Prognosis in STEMI

While we as physicians often labor under the impression that we can dramatically change a patient's prognosis, it is noteworthy that 90% of the predictive information regarding 30 day mortality is contained in the following 5 baseline variables that can be modified to only a limited degree: [1]

  1. Advanced age
  2. Sinus tachycardia
  3. Reduced systolic blood pressure
  4. Heart failure or Killip class of two or greater
  5. Anterior myocardial infarction location

Sinus tachycardia, hypotension, Killip class, and anterior MI are all essentially markers of poor pump function on admission. These risk factors for 30 day mortality have been well validated in a multivariate analysis of 41,020 patients in the GUSTO-I trial. Advanced age was the most significant factor associated with higher 30-day mortality. The rate was only 1.1% in the youngest decile (< 45 years) and climbed to 20.5% in patients > 75 (adjusted chi 2 = 717, P < .0001). Other variables most closely associated with an increased risk of mortality were lower systolic blood pressure at randomization (chi 2 = 550, P < .0001), higher Killip class (chi 2 = 350, P < .0001), elevated heart rate (chi 2 = 275, P < .0001), and the presence of an anterior infarction (chi 2 = 143, P < .0001). When taken together, these five baseline characteristics contained 90% of the prognostic information. Other significant though less important factors included previous myocardial infarction, height, time to treatment, diabetes, weight, smoking status, type of thrombolytic, previous bypass surgery, hypertension, and prior cerebrovascular disease. When these variables were combined, a validated model was created which stratified patients according to their mortality risk and accurately estimated the likelihood of death.

Other Prognostic Variables not Identified in GUSTO I

Other risk factors include, serum creatinine concentration [2], and peripheral vascular disease.[3][4]

Left Ventricular Function as a Risk Stratifier

Assessment of left ventricular ejection fraction may increase the predictive power of some risk stratification models.[5] The prognostic importance of Q-waves is debated.[6] Prognosis is significantly worsened if a mechanical complication (papillary muscle rupture, myocardial free wall rupture, and so on) were to occur.

There is evidence that case fatality of myocardial infarction has been improving over the years in all ethnicities.[7]

The Smokers Paradox

Interestingly, although tobacco abuse is a risk factor for CAD and STEMI, smoking is associated with a lower risk of mortality among patients who present with STEMI [8][9] This is due, at least in part, to the finding that smokers who present with STEMI are, on average, at least a decade younger than non-smokers. Smokers more often have involvement of the right coronary artery rather than the left anterior descending artery as well. Smokers paradoxically have better myocardial perfusion following reperfusion therapy than non smokers [10].

The TIMI Risk Score

The Thrombolysis in Myocardial Infarction TIMI Risk Score [11] and TIMI Risk Index [12] are two prognostic indices that have been validated in clinical trials and epidemiologic studies to predict 30-day mortality among patients with STEMI.

The TIMI risk score for STEMI was created from simple arithmetic sum of independent predictors of mortality weighted according to the adjusted odds ratios from logistic regression analysis. The risk score was derived from 14,114 patients enrolled in the Intravenous nPA for Treatment of Infarcting Myocardium Early II trial (TIME II). The TIMI risk score was subsequently validated in an unselected heterogeneous community population through the National Registry of Myocardial Infarction (NRMI) 3 & 4. The TIMI Risk Score incorporates eight clinical variables (age, systolic blood pressure [SBP], heart rate [HR], Killip class, anterior ST elevation or left bundle branch block on electrocardiogram, diabetes mellitus, history of hypertension or angina, low weight and time to treatment >4 hours) and assigns them a point value based on their odds ratio for mortality.

The TIMI Risk Score was developed and validated in clinical trials of fibrinolytic therapy, but it has also been reported to be prognostic in community-based real-world registries [13] as well as elderly patients [14]. The TIMI risk score for TIMI is calculated by adding the numbers assigned to the different criteria shown below. The total possible score is 14.[11]

Risk Factor Points
Demographic data and medical history
Age ≥75 years 3
Age 65–74 years 2
History of diabetes mellitus or hypertension or angina 1
Physical examination
Systolic blood pressure <100 3
Heart rate >100 2
Killip class II–IV 2
Weight <67 kg 1
Evaluation at presentation
Anterior ST elevation or left bundle branch block 1
Time to therapy >4 hours 1

Interpretation of TIMI Risk Score for STEMI

Score 30 Day Mortality (%)[11]
0 0.8%
1 1.6%
2 2.2%
3 4.4%
4 7.3%
5 12.4%
6 16.1%
7 23.4%
8 26.8%
>8 35.9%

The TIMI Risk Index incorporates age, HR and SBP (HR x [age/10] x 2/SBP), and has been validated in unselected patients [15], registries [16] and population-based cohorts [17]

GRACE Risk Score

Calculation of Grace Risk Score for In-Hospital Mortality

The total GRACE risk score is calculated by adding the points assigned to the different variable shown below. The highest total possible score 363.[18]

Variable Points
Age (years)
<30 0
30–39 8
40–49 25
50–59 41
60–69 58
70–79 75
80–89 91
≥90 100
Heart rate (beats/minute)
<50 0
50–69 3
70–89 9
90–109 15
110–149 24
150–199 38
≥200 46
Systolic blood pressure (mmHg)
<80 58
80–99 53
100–119 43
120–139 34
140–159 24
160–199 10
≥200 0
Initial serum creatinine (mg/dL)
0.0–0.39 1
0.4–0.79 4
0.8–1.19 7
1.2–1.59 10
1.6–1.99 13
0.2–3.99 21
≥4 28
Killip class
I 0
II 20
III 39
IV 59
Cardiac arrest at admission 39
Elevated cardiac markers 14
ST segment deviation 28

Interpretation of Grace Risk Score for In-Hospital Mortality

A nomogram for the probability in-hospital mortality has been developed based on the GRACE score. Shown below is the probability of in-hospital mortality by the corresponding GRACE score value.[18]

Score Probability of in-hospital mortality (%)
≤60 ≤0.2%
70 0.3%
80 0.4%
90 0.6%
100 0.8%
110 1.1%
120 1.6%
130 2.1%
140 2.9%
150 3.9%
160 5.4%
170 7.3%
180 9.8%
190 13%
200 18%
210 23%
220 29%
230 36%
240 44%
≥250 ≥52%

Grace Risk Score for All-Cause Mortality From Discharge to 6 Months

Calculation of the GRACE Score for All-Cause Mortality From Discharge to 6 Months

The total GRACE risk score is calculated by adding the points assigned to the different variable shown below.[19] The highest total possible score 263.

Variable Points
Age (years)
<40 0
40–49 18
50–59 36
60–69 55
70–79 73
80–89 91
≥90 100
Heart rate (beats/minute)
≤49.9 0
50–69.9 3
70–89.9 9
90–109.9 14
110–149.9 23
150–199.9 35
≥200 43
Systolic blood pressure (mmHg)
<80 24
80–99.9 22
100–119.9 18
120–139.9 14
140–159.9 10
160–199.9 4
≥200 0
Initial serum creatinine (mg/dL)
0.0–0.39 1
0.4–0.79 3
0.8–1.19 5
1.2–1.59 7
1.6–1.99 9
0.2–3.99 15
≥4 20
History of congestive heart failure 24
History of myocardial infarction 12
Elevated cardiac markers 15
ST segment depression 11
No in-hospital PCI 14

References

  1. Lee KL, Woodlief LH, Topol EJ; et al. (1995). "Predictors of 30-day mortality in the era of reperfusion for acute myocardial infarction. Results from an international trial of 41,021 patients. GUSTO-I Investigators". Circulation. 91 (6): 1659–68. PMID 7882472.  Unknown parameter |month= ignored (help)
  2. Gibson CM, Pinto DS, Murphy SA; et al. (2003). "Association of creatinine and creatinine clearance on presentation in acute myocardial infarction with subsequent mortality". J. Am. Coll. Cardiol. 42 (9): 1535–43. PMID 14607434.  Unknown parameter |month= ignored (help)
  3. Fox KA, Dabbous OH, Goldberg RJ; et al. (2006). "Prediction of risk of death and myocardial infarction in the six months after presentation with acute coronary syndrome: prospective multinational observational study (GRACE)". BMJ. 333 (7578): 1091. PMC 1661748Freely accessible. PMID 17032691. doi:10.1136/bmj.38985.646481.55.  Unknown parameter |month= ignored (help)
  4. Weir RA, McMurray JJ, Velazquez EJ. (2006). "Epidemiology of heart failure and left ventricular systolic dysfunction after acute myocardial infarction: prevalence, clinical characteristics, and prognostic importance.". Am J Cardiol. 97 (10A): 13F–25F. PMID 16698331. 
  5. Bosch X, Theroux P. (2005). "Left ventricular ejection fraction to predict early mortality in patients with non-ST-segment elevation acute coronary syndromes.". Am Heart J. 150 (2): 215–20. PMID 16086920. 
  6. Nicod P, Gilpin E, Dittrich H, Polikar R, Hjalmarson A, Blacky A, Henning H, Ross J (1989). "Short- and long-term clinical outcome after Q wave and non-Q wave myocardial infarction in a large patient population.". Circulation. 79 (3): 528–36. PMID 2645061. 
  7. Liew R, Sulfi S, Ranjadayalan K, Cooper J, Timmis AD. (2006). "Declining case fatality rates for acute myocardial infarction in South Asian and white patients in the past 15 years.". Heart. 92 (8): 1030–4. PMID 16387823. 
  8. Gourlay SG, Rundle AC, Barron HV (2002). "Smoking and mortality following acute myocardial infarction: results from the National Registry of Myocardial Infarction 2 (NRMI 2)". Nicotine Tob. Res. 4 (1): 101–7. PMID 11906686. doi:10.1080/14622200110103205.  Unknown parameter |month= ignored (help)
  9. Weisz G, Cox DA, Garcia E; et al. (2005). "Impact of smoking status on outcomes of primary coronary intervention for acute myocardial infarction--the smoker's paradox revisited". Am. Heart J. 150 (2): 358–64. PMID 16086943. doi:10.1016/j.ahj.2004.01.032.  Unknown parameter |month= ignored (help)
  10. Kirtane AJ, Martinezclark P, Rahman AM; et al. (2005). "Association of smoking with improved myocardial perfusion and the angiographic characterization of myocardial tissue perfusion after fibrinolytic therapy for ST-segment elevation myocardial infarction". J. Am. Coll. Cardiol. 45 (2): 321–3. PMID 15653037. doi:10.1016/j.jacc.2004.10.018.  Unknown parameter |month= ignored (help)
  11. 11.0 11.1 11.2 Morrow DA, Antman EM, Charlesworth A; et al. (2000). "TIMI risk score for ST-elevation myocardial infarction: A convenient, bedside, clinical score for risk assessment at presentation: An intravenous nPA for treatment of infarcting myocardium early II trial substudy". Circulation. 102 (17): 2031–7. PMID 11044416.  Unknown parameter |month= ignored (help)
  12. Morrow DA, Antman EM, Giugliano RP; et al. (2001). "A simple risk index for rapid initial triage of patients with ST-elevation myocardial infarction: an InTIME II substudy". Lancet. 358 (9293): 1571–5. PMID 11716882. doi:10.1016/S0140-6736(01)06649-1.  Unknown parameter |month= ignored (help)
  13. Morrow DA, Antman EM, Parsons L; et al. (2001). "Application of the TIMI risk score for ST-elevation MI in the National Registry of Myocardial Infarction 3". JAMA. 286 (11): 1356–9. PMID 11560541.  Unknown parameter |month= ignored (help)
  14. Rathore SS, Weinfurt KP, Foody JM, Krumholz HM (2005). "Performance of the Thrombolysis in Myocardial Infarction (TIMI) ST-elevation myocardial infarction risk score in a national cohort of elderly patients". Am. Heart J. 150 (3): 402–10. PMID 16169316. doi:10.1016/j.ahj.2005.03.069.  Unknown parameter |month= ignored (help)
  15. Ilkhanoff L, O'Donnell CJ, Camargo CA, O'Halloran TD, Giugliano RP, Lloyd-Jones DM (2005). "Usefulness of the TIMI Risk Index in predicting short- and long-term mortality in patients with acute coronary syndromes". Am. J. Cardiol. 96 (6): 773–7. PMID 16169358. doi:10.1016/j.amjcard.2005.04.059.  Unknown parameter |month= ignored (help)
  16. Wiviott SD, Morrow DA, Frederick PD; et al. (2004). "Performance of the thrombolysis in myocardial infarction risk index in the National Registry of Myocardial Infarction-3 and -4: a simple index that predicts mortality in ST-segment elevation myocardial infarction". J. Am. Coll. Cardiol. 44 (4): 783–9. PMID 15312859. doi:10.1016/j.jacc.2004.05.045.  Unknown parameter |month= ignored (help)
  17. Bradshaw PJ, Ko DT, Newman AM, Donovan LR, Tu JV (2007). "Validation of the Thrombolysis In Myocardial Infarction (TIMI) risk index for predicting early mortality in a population-based cohort of STEMI and non-STEMI patients". Can J Cardiol. 23 (1): 51–6. PMID 17245483.  Unknown parameter |month= ignored (help)
  18. 18.0 18.1 Granger CB, Goldberg RJ, Dabbous O, Pieper KS, Eagle KA, Cannon CP; et al. (2003). "Predictors of hospital mortality in the global registry of acute coronary events.". Arch Intern Med. 163 (19): 2345–53. PMID 14581255. doi:10.1001/archinte.163.19.2345. 
  19. Eagle KA, Lim MJ, Dabbous OH, Pieper KS, Goldberg RJ, Van de Werf F; et al. (2004). "A validated prediction model for all forms of acute coronary syndrome: estimating the risk of 6-month postdischarge death in an international registry.". JAMA. 291 (22): 2727–33. PMID 15187054. doi:10.1001/jama.291.22.2727.  Review in: ACP J Club. 2004 Nov-Dec;141(3):80

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