Abstract 160: Impact of ECG to Decision Time and Sex Differences on False Positive STEMI Diagnosis Rate in a Large Rural Healthcare Center

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Objectives: A false positive diagnosis of STEMI may lead to unnecessary treatments and increased costs. Little data are published on the unique care performance metric of electrocardiogram-to-decision time (E2Decide) for the diagnosis of STEMI. The objective of this quality improvement analysis was to determine the association between E2Decide time and sex differences on false positive diagnosis rates for STEMI

Methods: A retrospective analysis was conducted of consecutive STEMI diagnoses treated at a rural tertiary care hospital, located in Duluth, Minnesota, USA, between May 2013 to December 2017, originating from 4 different settings: (1) non-PCI facilities, (2) in the field by emergency medical services, (3) tertiary hospital emergency department, or (4) tertiary hospital in-patient. A false positive STEMI diagnosis was defined as no culprit lesion or multi-vessel disease found during angiography, or if the cardiologist rejected the initial diagnosis of STEMI and cancelled angiography. Multivariate logistic regression modeling was used for parameter estimates.

Results: There were 1278 consecutive STEMI diagnoses in our analysis, of which there were 429 (33.6%) females. A total of 215 (16.8%) were false positives. Females had a 45.2% increased odds of a false positive diagnosis compared to males [estimated odds ratio (OR) 1.452 (95% CI: 1.062- 1.984)]. E2Decide time was positively associated with an increase in odds of a false positive (OR 1.007; 95% CI: 1.001-1.012). For every 5 minutes of increase in E2Decide time, there was a 3.6% increase in the odds of a false positive STEMI diagnosis.

Conclusions: We observed a higher false positive STEMI diagnosis rate with females compared to males. Longer E2Decide times were significantly associated with higher false positive STEMI diagnosis rates. In addition to demonstrating the impact of sex differences on false positive STEMI diagnosis rate, this analysis demonstrates the potential value of the metric E2Decide time.

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