Make the Diagnosis: Myocardial Infarction
Approximately 25% of patients with symptoms suggesting ACI will prove to have an MI.
Population for Whom Acute Myocardial Infarction Should Be Considered
Focus primarily on the symptoms associated with the presenting complaints, rather than the risk factors.
Detecting the Likelihood of Acute Myocardial Infarction
The ECG is by far the most useful finding available at the patient's bedside. For patients with an abnormal ECG results suggesting acute MI (ST-segment elevation or Q waves, new conduction defects, diagnostic T-wave abnormalities), the symptoms and signs of MI become less important (Table 35-13). For patients with chest discomfort and normal or nondiagnostic
Table 35-13Multivariate and Univariate Predictors of Myocardial Infarction ||Download (.pdf) Table 35-13 Multivariate and Univariate Predictors of Myocardial Infarction
| ||MI |
|LR+ (95% CI) or Range ||LR– (95% CI) or Range |
|Multivariate Predictors |
|ACI-TIPI with clinical decision (n = 4 studies)3 ||3.9-12 ||0.05-0.18 |
|Wang logistic model (n = 1 study)11 ||This model provides a probability estimate for MI for patients with chest discomfort independent of the ECG result and coronary history. |
|Goodacre et al8 logistic model (n = 1 study) ||This model provides a probability estimate for MI for patients with chest discomfort and a normal or nondiagnostic ECG result, no history of coronary heart disease with similar pain, and low suspicion of pulmonary embolus. The model should not be applied to other patient populations. |
|Univariate Predictors |
|Univariate findings for acute MI in patients with normal or nondiagnostic ECG results without known coronary heart disease with prolonged or recurrent chest pain typical of their angina |
|Pain radiation to the shoulder OR both arms8 ||4.1 (2.5-6.5) ||0.68 (0.52-0.89) |
|Pain radiation to the right arm9 ||3.8 (2.2-6.6) ||0.86 (0.77-0.96) |
|Vomiting9 ||3.5 (2.0-6.2) ||0.87 (0.79-0.97) |
|Ex-smoker9 ||2.5 (1.6-4.0) ||0.85 (0.76-0.96) |
ECG results, some of the symptoms are diagnostically useful. Perhaps the most important finding for clinicians is the realization that a few of the important risk factors for coronary heart disease do not help in the acute setting for identifying patients with chest pain who are having an acute MI. The presence of diabetes, hypertension, and hyperlipidemia does identify patients at higher risk of coronary heart disease, but the presenting symptoms are more important for determining whether the current episode represents ACI.
The availability of the ACI-TIPI probability estimate requires integration of the computerized implementation protocol into an ECG reading. Consequently, physicians may not have access to the results. In the absence of the estimates, ...