Published in:
18-08-2022 | Editorial
A novel cardiovascular risk assessment tool for the prediction of myocardial ischemia on imaging
Published in: Journal of Nuclear Cardiology | Issue 1/2023
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Cardiovascular risk assessment tools are model-based algorithms used to estimate the risk of various cardiovascular conditions over a defined period of time. These tools use population-level cohort data to predict cardiovascular risk for an individual and are often validated in multiple diverse populations independent from the derivation cohorts. Use of these tools can identify both low and high risk patient populations and can facilitate earlier interventions, whether by lifestyle modification, targeted pharmacological therapy, or invasive procedures. They have been used clinically to help guide cost-effective decision-making by reserving the use of more expensive tests, such as advanced imaging, to individuals that would derive the most benefit from them. These cardiovascular risk assessment tools are patient-centered as they allow for individualization of care and can help patients to understand their individual-level risk, thus engaging patients in their care plan. Several of these tools have been developed for different indications including primary prevention, chest pain, acute coronary syndrome, heart failure, and atrial fibrillation, among others (Table 1). Historically, using simple algorithms that can be calculated mentally at the bedside have provided convenience and ease of use. However, the increased utilization of electronic medical records and handheld devices at the bedside has allowed for the increasing use of more complex algorithms available on multiple electronic platforms (see for the example the available Mobile Apps on acc.org or mdcalc.com).1,2 In utilizing these risk assessment tools in clinical practice, it is imperative that clinicians have an intimate understanding of the applicability of the tool in specific clinical settings. Understanding tool’s limitations and its implications for clinical practice can help to avoid becoming overwhelmed by the sheer volume of applicable clinical risk assessment tools available and aide in the accurate application and use of existing tools. Ultimately, these tools are meant to supplement the clinical reasoning of the medical provider rather than a replacement for clinical judgment.
Table 1
A sample of risk calculators and algorithms with their intended function
|
Title of risk calculator/algorithm
|
Indication of risk algorithm calculator
|
Variables
|
Calculates
|
Indications
|
|---|---|---|---|---|
|
Framingham Risk Score
|
Prognosis
|
Sex, Age, Total Cholesterol (TC), High-density Lipoprotein (HDL), Systolic Blood Pressure (SBP), Smoking, Hypertension
|
10-year risk of developing coronary heart disease
|
For use in non-diabetic patients aged 30–79 years with no prior history of coronary heart disease
|
|
ASCVD (Atherosclerotic Cardiovascular Disease) Risk Calculator
|
Prognosis
|
Age, Diabetes Mellitus, Sex, Smoker, TC, HDL. SBP, Treatment for Hypertension, Race
|
10-year risk of cardiovascular event (coronary or stroke death or nonfatal MI or stroke)
|
For use in primary prevention of cardiovascular disease in all adult patients. Also, for use to determine starting statin therapy
|
|
CHADsVASC
|
Prognosis
|
Age, Sex, Congestive Heart Failure (CHF), Hypertension, Stroke/Transient Ischemic Attack, Vascular Disease, Diabetes Mellitus
|
Stroke risk for patients with atrial fibrillation
|
For use in patients with non-valvular atrial fibrillation to determine the risk for an ischemic stroke and the need to start anticoagulation
|
|
HAS-BLED Score for Major Bleeding Risk
|
Prognosis
|
Hypertension, Renal Disease, Liver Disease, Stroke History, Prior major bleeding or predisposition to bleeding, Labile INR, Age > 65, Medication usage predisposing to bleeding, Alcohol use
|
Estimates the risk of major bleeding for patients on anticoagulation
|
To help assess the risk–benefit of starting anticoagulation in patients with atrial fibrillation
|
|
Killip Classification for Heart Failure
|
Prognosis
|
Classification: No signs of congestion, S3 and basal rales on auscultation, acute pulmonary edema, cardiogenic shock
|
Estimated 30-day mortality in a patient presenting with acute coronary syndrome
|
To both quantify severity of heart failure in a patient presenting with acute coronary syndrome and predict 30-day mortality
|
|
GRACE ACS Risk and Mortality Calculator
|
Prognosis
|
Age, Heart Rate (HR), SBP, Creatinine, Cardiac Arrest on Admission, ST-segment deviation on EKG, Abnormal cardiac enzymes, Killip Class (signs/symptoms)
|
The probability of death in acute coronary syndrome patients
|
For use in patients presenting with acute coronary syndrome to determine likelihood of mortality from admission to six months after the index event
|
|
TIMI Risk Score for Unstable Angina or NSTEMI
|
Prognosis
|
Age, Coronary Artery Disease (CAD) Risk Factors, Known CAD, Aspirin use in past 7 days, Severe Angina, ST Changes on EKG, Positive Troponin
|
Estimates risk for mortality for a patient presenting with unstable angina or NSTEMI
|
Indicated to risk stratify patients presenting with acute coronary syndrome (unstable angina or NSTEMI)
|
|
Simplified Pulmonary Embolism Severity Index (SPESI)
|
Prognosis
|
Age, history of cancer, history of chronic cardiopulmonary disease, HR, SBP, O2 saturation
|
Calculates risk for death within 30 days of having a confirmed pulmonary embolism (PE)
|
In a patient diagnosed with a PE, the sPESI can be utilized to determine if the patient is a candidate for outpatient management
|
|
Diamond-Forrester Classification of Acute Chest Pain
|
Ruling out can’t miss diagnosis
|
Substernal Chest Pain, Exertional Chest Pain, Chest Pain relieved with rest
|
Calculates probability patient is experiencing true cardiac chest pain
|
For use in stratifying patients with features concerning for angina and determining the next step in diagnosis including either stress test or coronary angiogram
|
|
CAD Consortium Model
|
Ruling out can’t miss diagnosis
|
Age, Sex, Chest Pain (typical vs atypical vs noncardiac), Diabetes Mellitus, Hypertension, Dyslipidemia, Smoking History, Coronary Calcium Score (if available)
|
Determine pre-test probability of coronary artery disease in patients with chest pain
|
Currently used in Europe to help stratify the risk of patients presenting with stable chest pain having underlying coronary artery disease
|
|
Juarez-Orozco et al. diagnostic technique selection tool for significant CAD
|
Ruling out can’t miss diagnosis
|
Chest Pain (typical vs atypical vs noncardiac), Dyspnea, Age, Sex
|
Likelihood of a patient having obstructive coronary artery disease
|
Referenced in 2021 Guideline for the Evaluation and Diagnosis of Chest Pain. Used to help rule out functionally obstructive coronary artery disease and aid in determining if further stress or anatomic tests are indicated
|
|
Winther et al. diagnostic technique selection tool to provide estimation of the likelihood of obstructive CAD
|
Ruling out can’t miss diagnosis
|
Chest Pain (typical vs atypical vs noncardiac), Number of Risk Factors (family history, smoking, dyslipidemia, hypertension, diabetes), Age, Sex Coronary Artery Calcium Score
|
Likelihood of a patient having obstructive coronary artery disease
|
Referenced in 2021 Guideline for the Evaluation and Diagnosis of Chest Pain. Used to estimate clinical likelihood of obstructive coronary artery disease
|
|
HEART Score for Major Cardiac Events
|
Ruling out can’t miss diagnosis
|
History, EKG, Age, Risk Factors, Initial Troponin
|
Calculates six-week risk of a major adverse cardiac event
|
For use in patients presenting to the emergency department with chest pain concerning for acute coronary syndrome
|
|
Brugada Criteria for Ventricular Tachycardia
|
Diagnosis
|
Absence of RS complex in all precordial leads, R to S interval > 100 ms in one precordial lead, atrioventricular dissociation, Morphology criteria for Ventricular Tachycardia present in both precordial leads V1-2 and V6
|
Distinguishes ventricular tachycardia from supraventricular tachycardia
|
The algorithm is indicated for patients presenting with a wide-QRS complex tachycardia to differentiate ventricular tachycardia from supraventricular tachycardia with aberrancy
|
|
Duke Criteria for Infective Endocarditis
|
Diagnosis
|
Blood cultures positive for typical microorganisms seen in infective endocarditis, Echocardiogram showing valvular vegetation, predisposing heart condition or intravenous drug use, fever, vascular phenomena, immunologic phenomena, or positive blood culture not typically seen in infective endocarditis
|
Likelihood of a patient having infective endocarditis
|
Indicated as set of clinical criteria to diagnose infective endocarditis
|
|
Sgarbossa’s Criteria for Myocardial Infarction in Left Bundle Branch Block
|
Diagnosis
|
Concordant ST elevation > 1 mm in leads with a positive QRS complex, Concordant ST depression > 1 mm in V1-V3, or excessively discordant ST elevation (or depression) in leads with a negative QRS
|
Likelihood of a patient having an acute myocardial infarction with a prior left bundle branch block
|
Indicated in determining if a patient is having an acute myocardial infarction in the setting of a prior myocardial infarction
|