Abstract
BackgroundPrehospital ECGs (phECGs) are the main screening tool used by paramedics to identify ST elevation myocardial infarction (STEMI). In the absence of telemetry or personnel trained in ECG interpretation, paramedics must rely on computerized interpretation of phECGs, which suffer from an elevated false-positive (FP) rate, impairing reliable early activation of reperfusion centers by Emergency Medical Services. ObjectiveDevelop a clinical prediction rule to reduce the frequency of FPs for STEMI in prehospital patients. MethodsThis was a retrospective analysis of prehospital patients with a computer interpretation of ‘***ACUTE MI***’ on phECG. We used logistic regression analysis to identify the independent variables for derivation of the rule. Once derived, we validated the rule on a distinct cohort of consecutive phECGs. ResultsAmong the 654 cases in the derivation cohort, 46.2% were FP STEMIs. Four elements emerged as independent FP predictors: HR ≥ 120, no ongoing chest pain, no interpretable ST-segments in a lead, and presence of baseline wander or pacemaker spikes. In the derivation cohort this rule decreased FPs to 15.1% of the total cohort, while labelling 13.8% of STEMI cases as false-negatives (FNs). In the validation cohort (386 phECGs, 41.7% FPs), the rule decreased FPs down to 8.0%, while 25.9% were FN. ConclusionUse of computer interpretation alone leads to a high STEMI FP rate. A clinical prediction rule based upon four elements available to paramedics can substantially lower the proportion of FPs. This clinical prediction rule should be incorporated into the decision for prehospital activation of the cardiac catheterization laboratory.
Published Version
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