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HEART Score and Stress Test Emergency Department Bayesian Decision Scheme: Results from the Acute Care Diagnostic
Naureen Farook1, L Cochon2, A D Bode3
1Department of Internal Medicine/Emergency Medicine, Henry Ford Health System, Detroit, Michigan.
Insights
This study compared stress echocardiograms (ECHO) and exercise treadmill tests (ETT) for predicting major adverse cardiac events (MACE) in low- to intermediate-risk patients. Stress ECHO showed a slight superiority over ETT in ruling out MACE.
Area of Science:
- Cardiology
- Medical Diagnostics
- Bayesian Statistics
Background:
- Accurate risk stratification for major adverse cardiac events (MACE) is crucial for emergency physicians.
- Bayesian nomograms have not been previously investigated for risk stratification in cardiovascular patients with low- to intermediate-risk profiles.
Purpose of the Study:
- To develop a comparative diagnostic model using Bayesian statistics to assess the post-test risk of MACE.
- To compare the diagnostic accuracy of exercise treadmill testing (ETT) and stress echocardiography (ECHO).
- To utilize the HEART (history, electrocardiogram, age, risk factors, and troponin) score for pretest probability estimation.
Main Methods:
- Stratification of patients based on HEART scores for MACE prediction.
- Calculation of pooled sensitivity and specificity for ETT and ECHO to determine likelihood ratios (LR).
- Application of Bayesian nomograms with HEART scores and LRs to compute post-test probabilities.
Main Results:
- Negative likelihood ratios (LR-) for ECHO (0.15) were more effective in ruling out MACE than ETT (0.27).
- For low-risk patients, ECHO yielded a post-test probability of 0.26% (LR-) compared to ETT's 0.46% (LR-).
- For intermediate-risk patients, ECHO yielded a post-test probability of 2.49% (LR-) compared to ETT's 4.48% (LR-).
Conclusions:
- Bayesian analysis indicates stress ECHO is slightly superior to ETT in ruling out MACE for low- and intermediate-risk patients.
- The negative LR of ECHO was statistically significant in excluding MACE.
- This model provides a valuable tool for risk stratification in cardiovascular patient assessment.
Background:
Accurate identification of patients at risk of major adverse cardiac events (MACE) places a substantial burden on emergency physicians (EPs). Bayesian nomogram for risk stratification in low- to intermediate-risk cardiovascular patients has not been investigated previously.
Objective:
The objective of this study was to develop a comparative diagnostic model using Bayesian statistics for exercise treadmill test (ETT) and stress echocardiogram (ECHO) to calculate post-test diagnostic risk of MACE using HEART (history, electrocardiogram, age, risk factors, and troponin) risk score as predictor of pretest probability.
Methods:
Stratification was made by applying HEART scores for the prediction of MACE. Likelihood ratios (LR) were calculated using pooled sensitivity and specificity of ETT and ECHO from the American College of Cardiology Foundation/American Heart Association systematic review. Post-test probabilities were obtained after inserting HEART score and LR into Bayesian nomogram. Analysis of variance was used to assess statistical association.
Results:
Positive LR (LR+) for ETT was 4.56 and negative LR (LR-) was 0.27; for ECHO, LR+ 5.65 and LR- 0.15. Bayesian statistical modeling post-test probabilities for LR+ and low HEART risk yielded a post-test probability for ETT of 7.75% and 9.09% for ECHO; intermediate risk gave 47.62% and 52.63%, respectively. For LR-, low HEART risk post-test probability for ETT was 0.46% and for ECHO 0.26%; intermediate risk probabilities were 4.48% and 2.49%, respectively. LR- was statistically significant in ruling out MACE with ECHO (p < 0.001), but no significant differences were seen for LR+ (p = 0.64).
Conclusions:
This Bayesian analysis demonstrated slight superiority of stress ECHO over ETT in low- and intermediate-risk patients in ruling out MACE.
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