LOW RISK CHEST PAIN SEMINAR - henryfordem.comPE is usually normal in uncomplicated ACS . May point...
Transcript of LOW RISK CHEST PAIN SEMINAR - henryfordem.comPE is usually normal in uncomplicated ACS . May point...
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LOW RISK CHEST PAIN SEMINAR
Emily McLaren, PGY 3 7 February 2013
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What are the history and physical characteristics of
patients presenting to an ED with chest pain that is low risk
for ACS?
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Objectives
What is the role of the H&P in identifying LRCPPTS?
What is the role of classic cardiac risk factors in risk stratification of ACS?
What clinical decision tools are available to aid in risk stratification of LRCPPTS?
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What is low risk chest pain?
Typical chest pain Heberden 1768 A painful sensation in the breast accompanied
by a strangling sensation, anxiety, and occasional radiation of pain to the L arm
Associated with exertion, relieved with rest Atypical or low risk chest pain
Everything else?
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Why do we care?
We miss about 2-5% of ACS Most CP admissions are for non-cardiac
chest pain
H+P, RF, and decision tools are available to aid in our decision making
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Chest Pain History
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JAMA 2005 Literature review of prospective and
retrospective observational studies and systematic reviews
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Chest Pain Characteristics
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Chest Pain Radiation
Typical CP: radiation to L neck, shoulder or arm
ACS To R arm, shoulder (PLR 4.7) To both arms (PLR 4.1) To L arm, shoulder (PLR 2.3)
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Chest Pain Quality
Typical CP: pressure, ache
ACS Same as prior MI (PLR 1.8) Pressure (PLR 1.3)
ACS Sharp, stabbing (PLR 0.3)
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Chest Pain Location
Typical CP: substernal, L chest Poorly studied Poor predictive value
Substernal CP Region of infarction (exception: inferior AMI)
ACS: Inframammary (PLR 0.8)
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Area of Chest Pain
Typical CP: diffuse
ACS: < size of coin (PRL 0.6 with CI 0.3-1) Everts et al, 822 pts Non-AMI 11% vs AMI 7%
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Chest Pain Severity
×
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Time Course ACS: crescendo pattern Non-ACS: maximal intensity at onset
Duration Seconds – non-ACS 2-10 min – angina 10-30 min – unstable angina > 30 min – AMI vs non-ACS (GI) Recurrent, hrs-days – non-ACS
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Palliative/Provocative Factors and Associated Symptoms
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Palliative Factors
Nitro GI Cocktail Rest ×
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Provocative Factors
ACS Exertion (PLR 2.4)
Equivocal Emotion Stress
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Provocative Factors ACS
Pleuritic (PLR 0.2) Positional (PLR 0.3) Reproducible (PLR 0.3) Non-exertional (PLR 0.8)
Lee et al (1985) – 22% of pts with sharp pain dx with ACS (13% pleuritic, 7% reproducible)
Lee et al (1987) – 3 Ps + no hx of CAD, none dx with MI
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Associated Symptoms
ACS Diaphoresis (PLR 2) Nausea/vomiting (PLR 1.9)
Disappears with multivariable testing
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Conclusions
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Conclusions
Individual elements are assoc with increased or decreased risk of ACS
No element of chest pain quality alone or in combination identify patients that can be safely discharged without further diagnostic testing
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Limitations
Characteristics treated as independent, rather than interdependent variables
Quality is subjective Only addresses CP, not other anginal
equivalents
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Physical Exam
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HIGH LIKELIHOOD
INTERMEDIATE LIKELIHOOD
LOW LIKELIHOOD
• Pulmonary edema • New or worsening MR • S3 • Hypotension • Brady or tachycardia
• Extracardiac vascular disease (bruit)
Reproducible CP
PE is usually normal in uncomplicated ACS
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May point to non-ACS Dx
Unequal pulses - dissection Murmurs - endocarditis Friction rub - pericarditis Fever, rhonchi - pneumonia Reproducible CP - MSK
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Cardiac Risk Factors
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Risk Factors
Age, Male Gender, HTN, HLP, DM, smoking, and family history
Framingham study: 2+ risk factors = higher lifetime risk of CAD
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Jayes et al, 1992 1743 pts What to RF add to hx and EKG when
diagnosing ACS?
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Jayes et al
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Han et al, 2007 Retrospective analysis of 10,806 patients
with suspected ACS 8.1% met end point: ACS within 30 days
(PCI, biomarkers, death)
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Conclusions
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Conclusions Cardiac RF have limited value in diagnosing ACS in ED patients older than 40
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Conclusions -LR 0 RF +LR 4+ RF
< 40 0.17 (0.04-0.66) 7.39 (3.09-17.67)
40-65 0.53 (0.4-0.71) 2.13 (1.66-2.73)
> 65 0.96 (0.74-1.23) 1.09 (0.64-1.62)
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Limitations
RF given equal weight Verification bias
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Clinical Decision Tools
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Early Risk Scores
Pozen et al, 1980: created a ‘mathematical predictive instrument’ to decrease CCU admissions
Selker et al, 1998: ACI-TIPI Goldman et al, 1988: < 7% risk of AMI Limkakeng et al, 2001: < 4.9% risk of AMI
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TIMI Risk Score
Developed to categorize risk of death or ischemic events in pts with NSTEMI or UA
Used as basis for MDM
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Chase et al, 2006 First prospective observational cohort to
validate TIMI in ED pts 1458 pts
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Chase et al, 2006
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Chase et al, 2006
TIMI Score 0 = 1.7% event rate
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Chase et al
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Similar Studies
Pollack et al, 2006 3929 patients TIMI 0 = 2.1% risk
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Conclusions
TIMI risk score does correlate with outcome Identified large group of pts that are low risk
for primary outcome at 30 days Cannot be used in isolation to determine
dispo
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“Manchester” Modified TIMI
Body et al, 2009 Pts with positive troponin or EKG changes
may only have TIMI = 1 Prospective cohort 796 pts
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Body et al
TIMI < 3 = sensitivity of 96%
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Hess et al, 2010 Prospective observational study 1017 pts
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Hess et al, 2010
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Than et al, 2011 3582 pts in 14 EDs, 9 countries TIMI + biomarker panel at 0 and 2 hrs 2 hr TIMI 0 = 0.9% risk (9.8% of pts)
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Than et al
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Aldous et al, 2012 1000 from ASPECT Primary outcome in 36.2% Also included high sensitivity Troponin T 2 hr TIMI 0 = 0.8% risk (12.3% pts)
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GRACE Global Registry of Acute Coronary Events Prospective multinational observational study
of hospitalized pts with ACS 8 variables
Looks at in-hospital and 6 month all-cause mortality
Age HR SBP Cr Killup score
ST segment depression
Elevated biomarkers
Cardiac arrest
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Lyon et al, 2006 Retrospective cohort 1000 pts TIMI = GRACE
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Lee et al 2011 TIMI vs GRACE vs PURSUIT Prospective cohort study 4723 pts
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PURSUIT
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Lee et al
TIMI = 0 in 39%
GRACE < 41 in 4.5%
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Lee et al
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Kline et al, 2005 Prospective database of 8 variables from
14,796 pts Attribute matching vs ACI-TIPI
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Attributes matching
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Kline et al
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Mitchell et al, 2006 1114 pts Attributes matching vs. ACI-TIPI vs.
physician estimate
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Mitchell et al
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Sanchis Rule
Sanchis et al, 2005 646 pts Focuses on clinical history Excludes EKG changes and (+) troponin Primary end point at 1 year, secondary at 14
days
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Chest Pain Score
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Hospital Course and Results
322 had exercise ST: (-) 190, (+) 52 216 pts early D/C 430 pts hospitalized
227 cardiac cath 68 PCI 31 CABG
Primary end point: 1 yr (6.7%), 14 days (5.4%)
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Calculated risk score
CP score > 10 1 point > 2 pain episodes in 24 hrs 1 point Age > 67 1 point IDDM 2 points Prior PCI 1 point
In pts with negative troponin and no EKG changes
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Calculated Risk Score
Score 0 1 2 3 > 4
Event Rate 0% 3.1% 5.4% 17.6% 29.6%
Stress Results Event Rate
Negative Inconclusive Positive Not done
1.6% 3.9% 9.6% 10%
Score of 0 = 17.2% of pts
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Limitations
Complicated CP score Subjective
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Vancouver Rule
Christenson et al, 2006 Prospective cohort, 769 pts Screened 123 potential predictor variables Clinical decision tool that is 98.8% sensitive
and allows for D/C of VLRCP pts within 2-3 hrs (32.5%)
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Other similar studies
Marsan et al (2005): age < 40, no CAD hx, normal EKG OR no CAD RF, normal initial biomarkers = ACS rate 0.14%, no CV events at 30 days
Collin et al (2011): no events for same patients at 1 year
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Limitations
Outdated biomarkers Detroit ≠ Vancouver
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Six et al, 2008 120 pts Clinical questions
Why do we admit to CCU? Predictors of 90 day events?
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Six et al
0-3: 2.5% risk (32.5% of pts)
4-6: 20.3% risk
7-10: 72.7% risk
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Six et al
Conclusion – can use HEART to determine early D/C vs. early intervention
Limitations Small study Use CP hx
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PURSUIT vs TIMI vs GRACE vs FRISC vs HEART
Uses c-statistic to claim HEART superiority
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Mahler et al, 2011 Prospective cohort 1070 CP Obs pts (TIMI < 2 and clinically low
risk) Outcome
HEART < 3: 0.6% events HEART < 3 + 4-6 hr troponin: 0 events
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Fesmire et al, 2012 Retrospective study 2148 pts Weighted HEART + 3 S’s
Sex Serial troponin and EKG Decreased weight of RF, age and CAD hx Increased weight on chest pain hx
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Fesmire et al
HEARTS3 < 2 = 0 events
(14% vs 8%)
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Fesmire et al
Older troponin Retrospective study
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Hess et al, 2012 Prospective observational cohort of 2,718
patients 12% met primary outcome (ACS,
revascularization, death) within 30 days Identified patients with zero risk for 30 day ACS
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Conclusions
Developed a highly sensitive clinical decision tool to identify very low risk patients for ACS
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Limitations
Does not include pts at risk for ACS with non-chest pain CC
Evaluation bias: not all patients underwent definitive testing
What is typical chest pain? Needs prospective multicenter validation
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Aldous et al, 2012 Post hoc analysis of ASPECT trial Primary endpoint in 36.2%
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Study Population
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Results
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Results
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Conclusions
Several elements of CP hx and multiple decision tools available to aid in dx of ACS
Classic CAD risk factors less impt in acute setting
Ultimately unlikely to change our clinical practice
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References 1. Swap and Nagurney. Value and Limitations of Chest Pain History in the Evaluation of Patient With Suspected Acute Coronary Syndrome.
JAMA. November 23/30. Vol 294. pp 2623-2629.
2. Fesmire et al. Improving risk stratification in patients with chest pain: the Erlander HEARTS3 score. American Journal of Emergency Medicine. 2012. pp 1829-1837.
3. Sanchis et al. New risk score for patients with acute chest pain, non-ST- segment deviation, and normal troponin concentrations: a comparison with the TIMI risk score. J Am Coll Cardiology 2005;46:443-449.
4. Christenson et al. A clinical prediction rule for early discharge of patients with chest pain. Annals of Emergency Medicine. 2006;47:1-10.
5. Backus et al. Chest pain in the emergency department: a multicenter validation of the HEART score. Crit Pathw Cardiol 2010;9:164-9.
6. Mahler et al. Can the HEART score safely reduce stress testing and cardiac imaging in patients at low risk for major adverse cardiac events. Crit Pathw Cardiol 2011;10:128-33.
7. Six et al. Chest pain in the emergency room: value of the HEART score. Neth Heart J 2008;16:191-6.
8. Chase et al. Prospective validation of the thrombolysis in myocardial infarction risk score in emergency department chest pain population. Annals of Emergency Medicine 2006;48:252-9.
9. Hess et al. Prospective validation of a modified thrombolysis in myocardial risk score in emergency department patients with chest pain and possible acute coronary syndrome. Acad Emergency Med 2010;17:368-75.
10. Lee et al. Comparison of cardiac risk scores in ED patients with potential acute coronary syndrome. Crit Pathw Cardiol 2011;10:64-8.
11. Lee et al. Clinical characteristics and natural history of patients with acute myocardial infarction sent home from the emergency room. Am J Cardiol. 1987;60:219-224.
12. Hess et l. Development of a Clinical Prediction Rule for 30-Day Cardiac Events in Emergency Department Patients With Chest Pain And Possible Acute Coronary Syndrome. Annals of Emergency Medicine. Vol 59, N0 2. Feb 2012. pp 115-125
13. Han et al. The Role of Cardiac Risk Factor Burden in Diagnosing Acute Coronary Syndromes in the Emergency Department Setting. Annals of Emergency Medicine. Vol 49, No 2. pp 145-152.
14. Amsterdam et al. Testing of Low-Risk Patients Presenting to the Emergency Department With Chest Pain: A Scientific Statement From the American Heart Association. Circulation. 2010;122:1756-1776.
15. Kline et al. Randomized Trial of Computerized Quantitative Pretest Probability in Low-Risk Chest Pain Patients: Effect on Safety and Resource Use. Annals of Emergency Medicine, June 2009. Vol 53, No 6. pp 727-735.
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References 1. Kline et al. Pretest probability assessment derived from attribute matching. BioMed Central. August 2005.
2. Mitchell et al. Prospective Multicenter Study of Quantitative Pretest Probability Assessment to Exclude Acute Coronary Syndrome for Patients Evaluated in Emergency Department Chest Pain Units. Annals of Emergency Medicine. 2006;47:438-447.
3. Selker et al. Use of the Acute Cardiac Ischemia Time-Insensitive Predictive Instrument (ACI-TIPI) to Assist with Triage of Patients with Chest Pain or Other Symptoms Suggestive of Acute Cardiac Ischemia: A Multicenter Clinical Trial. Annals of Internal Medicine, Dec 1998. Vol 129, No 11.
4. Marsan et a. Evaluation of a clinical decision rule for young adult patients with chest pain. Acad Emergency Medicine. 2005;12:26-31.
5. Collin et al. Young patients with chest pain: 1-year outcomes. Am J Emerg Med. 2011;29:265-270.
6. Goldman et al. A computer protocol to predict myocardial infarction in emergency department patients with chest pain. N Engl J Med. 1988;318:797-803.
7. Limkakeng et al. Combination of Goldman risk and initial cardiac troponin I for emergency department chest pain patient risk stratification. Acad Emerg Med. 2001;8:696-702.
8. Pollack et al. Application of the TIMI Risk Score for Unstable Angina and Non-ST elevation Acute Coronary Syndrome to an Unselected Emergency Department Chest Pain Population. Academic Emergency Medicine. 2006;13:13-18.
9. Aldous et al. A 2-hour thrombolysis in myocardial infarction score outperforms other risk stratification tools in patients presenting with possible acute coronary syndromes: Comparison of chest pain risk stratification tools. American Heart Journal. 2012. Vol 164, No 4. pp 516-523.
10. Than et al. A 2-h diagnostic protocol to assess patients with chest pain symptoms in the Asia-Pacific region (ASPECT): a prospective observational validation study. Lancet 2011;377:1077-84.
11. Aldous et al. A new improved accelerated diagnostic protocol safely identifies low risk patients with chest pain in the emergency department. Academic Emergency Medicine. 2012;19:510-6.
12. Eagle et al. A Validated Prediction Model for all Forms of Acute Coronary Syndrome: Estimating the Risk of 6-month Postdischarge Death in an International Registry. JAMA. June 9, 2004. Vol 291, No 22. pp 2727-2733.
13. Pozen et al. The usefulness of a predictive instrument to reduce inappropriate admissions to the coronary care unit. Annals of Internal Medicine. 1980; 92:238-242.
14. Body et al. Can a modified thrombolysis in myocardial infarction risk score outperform the original for risk stratifying emergency department patients with chest pain? Emerg Med J. 2009;26:95-99.
15. Jayes et al. Do Patients’ Coronary Risk Factor Reports Predict Acute Ischemia in the Emergency Department? A multicenter study. J Clin Epidemiol. 1992. Vol 45, No 6. pp 612-626.