3298Prehospital assessment of the one-hour rule-in/rule-out algorithm using a high-sensitivity cardiac troponin t assay in a low-prevalence population for acute coronary syndrome (OUT-ACS)

Abstract

Abstract Background The majority of patients with chest pain in Norway initially present to the primary health care system, which serves to triage them to the specialist health care services including hospitals. In some emergency primary care institutions, patients who are not hospitalised directly undergo further diagnostic testing to rule out acute myocardial infarction (AMI). Purpose Several studies have shown the advantage of using high-sensitivity assays for fast interpretation of cardiac troponins. The majority of these studies included patient populations from hospital emergency departments. In contrast, we aimed to investigate whether the 1-hour algorithm for high-sensitivity cardiac troponin T (hs-cTnT) is safe and useful for implementation in a primary care emergency setting where the patients have a much lower pre-test probability for an acute coronary syndrome. Methods In this prospective cohort study, we included 1672 patients with acute non-specific chest pain from November 2016 to October 2018 at a primary care emergency outpatient clinic in Norway. Serial hs-cTnT samples were analysed after 0, 1 and 4 hours on the Cobas 8000 e602 analyzer. We divided the results into one of three groups (rule-out, rule-in, or further observation), according to the 0/1-hour algorithm for hs-cTn from the current ESC guidelines on non-ST-elevation myocardial infarction. In the rule-out group, the 0/1-hour results were compared to the standard 4-hour hs-cTnT. Final hospital diagnoses were collected as a gold standard for the patients in the rule-in group. Results A total of 44 (2.6%) of 1672 patients were diagnosed with AMI. By applying the algorithm, 1274 (76.2%) patients were assigned to the rule-out group. One of the rule-out patients had a significant increase in hs-cTnT in the 4-hour sample. This results in a sensitivity for AMI of 97.7% (95% confidence interval [CI] 88.0–99.9) and negative predictive value of 99.9% (95% CI 99.6–100.0). There were 50 (3.0%) patients in the rule-in group, amongst whom 35 had a verified AMI. This gives a specificity for AMI of 99.1% (95% CI 98.5–99.5) and a positive predictive value at 70.0% (95% CI 55.4–82.1). Among the 348 (20.8%) patients assigned to further observation, eight patients had an AMI. The 15 rule-in patients who did not have an AMI, had other acute illnesses that required further diagnostic work-up at the hospital. Conclusions With a negative predictive value at 99.9%, the 1-hour algorithm for hs-cTnT seems safe and applicable for a faster assessment of patients with non-specific chest pain in a primary care emergency setting. Prehospital implementation of this algorithm may reduce the need for hospitalisation of these patients and hence may probably lower the costs. ClinicalTrial.gov identifier: NCT02983123 Acknowledgement/Funding Norwegian Research Fund for General Practice, The Norwegian Physicians' Association Fund for Quality Improvement and Patient Safety