Beyond chest pain: Incremental value of other variables to identify patients for an early ECG
Gabrielle Bunney1, Vandana Sundaram2, Anna Graber-Naidich2
1Department of Emergency Medicine, Stanford University, Palo Alto, CA, United States of America.
Insights
Chest pain is not always present in acute coronary syndrome (ACS), especially STEMI. Combining chest pain with other symptoms improves diagnosis, but identifying all STEMI cases remains challenging.
Area of Science:
- Emergency Medicine
- Cardiology
- Diagnostic Accuracy
Background:
- Chest pain is a primary symptom of acute coronary syndrome (ACS).
- However, 20-30% of patients, particularly women, elderly, and non-white individuals, may not report chest pain during ST-segment elevation myocardial infarction (STEMI).
Purpose of the Study:
- To evaluate the predictive value of chest pain alone and in combination with other factors for identifying ACS and STEMI in emergency department patients.
- To assess the trade-offs between sensitivity, specificity, and the number of patients requiring electrocardiograms (ECGs).
Main Methods:
- Retrospective analysis of a 5-year adult emergency department database (279,132 patients).
- Development and evaluation of multivariable logistic regression models incorporating chest pain, other ACS chief complaints, age, and sex.
- Assessment of model performance in identifying ACS and STEMI.
Main Results:
- Chest pain alone had high specificity (92%) but low sensitivity (61%), missing 28.4% of STEMIs.
- A model including all variables improved sensitivity (82%) but identified more patients for ECGs (22%).
- The model combining chest pain and other ACS chief complaints demonstrated the highest sensitivity (93%) and specificity (55%), missing only 4.4% of STEMIs while identifying 45.1% of patients for ECGs.
Conclusions:
- Chest pain alone is insufficient for sensitive STEMI detection.
- Incorporating other ACS chief complaints significantly enhances diagnostic sensitivity but increases the number of patients needing ECGs.
- Accurate and timely STEMI identification requires more sophisticated risk assessment tools beyond simple symptom checklists.
Background:
Chest pain (CP) is the hallmark symptom for acute coronary syndrome (ACS) but is not reported in 20-30% of patients, especially women, elderly, non-white patients, presenting to the emergency department (ED) with an ST-segment elevation myocardial infarction (STEMI).
Methods:
We used a retrospective 5-year adult ED sample of 279,132 patients to explore using CP alone to predict ACS, then we incrementally added other ACS chief complaints, age, and sex in a series of multivariable logistic regression models. We evaluated each model's identification of ACS and STEMI.
Results:
Using CP alone would recommend ECGs for 8% of patients (sensitivity, 61%; specificity, 92%) but missed 28.4% of STEMIs. The model with all variables identified ECGs for 22% of patients (sensitivity, 82%; specificity, 78%) but missed 14.7% of STEMIs. The model with CP and other ACS chief complaints had the highest sensitivity (93%) and specificity (55%), identified 45.1% of patients for ECG, and only missed 4.4% of STEMIs.
Conclusion:
CP alone had highest specificity but lacked sensitivity. Adding other ACS chief complaints increased sensitivity but identified 2.2-fold more patients for ECGs. Achieving an ECG in 10 min for patients with ACS to identify all STEMIs will be challenging without introducing more complex risk calculation into clinical care.
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