Key result
MACS-ECG and paramedic interpretation fail to reliably rule in or out pre-hospital NSTEMI.
Why the study?
The accuracy of the Manchester Acute Coronary Syndromes ECG (MACS-ECG) prediction model in the pre-hospital setting was unknown despite good performance in the emergency department.
Does the MACS-ECG prediction model improve the diagnosis of acute myocardial infarction compared to paramedic ECG interpretation in patients with suspected acute coronary syndrome in a pre-hospital setting?
Observational (n=691)
Yes
Does the MACS-ECG prediction model improve the diagnosis of acute myocardial infarction compared to paramedic ECG interpretation in patients with suspected acute coronary syndrome in a pre-hospital setting?
Effect estimate: C-index 0.68 (95% CI 0.61-0.75)
Neither the MACS-ECG prediction model nor paramedic ECG interpretation has sufficient predictive value to independently rule in or rule out NSTEMI in the pre-hospital setting.
Neither MACS-ECG nor paramedic ECG suffices for pre-hospital NSTEMI rule-out; leaves open need for superior tools.
OBJECTIVES: The Manchester Acute Coronary Syndromes ECG (MACS-ECG) prediction model calculates a score based on objective ECG measurements to give the probability of a non-ST elevation myocardial infarction (NSTEMI). The model showed good performance in the emergency department (ED), but its accuracy in the pre-hospital setting is unknown. We aimed to externally validate MACS-ECG in the pre-hospital environment. METHODS: We undertook a secondary analysis from the Pre-hospital Evaluation of Sensitive Troponin (PRESTO) study, a multi-centre prospective study to validate decision aids in the pre-hospital setting (26 February 2019 to 23 March 2020). Patients with chest pain where the treating paramedic suspected acute coronary syndrome were included. Paramedics collected demographic and historical data and interpreted ECGs contemporaneously (as 'normal' or 'abnormal'). After completing recruitment, we analysed ECGs to calculate the MACS-ECG score, using both a pre-defined threshold and a novel threshold that optimises sensitivity to differentiate AMI from non-AMI. This was compared with subjective ECG interpretation by paramedics. The diagnosis of AMI was adjudicated by two investigators based on serial troponin testing in hospital. RESULTS: Of 691 participants, 87 had type 1 AMI and 687 had complete data for paramedic ECG interpretation. The MACS-ECG model had a C-index of 0.68 (95% CI: 0.61 to 0.75). At the pre-determined cut-off, MACS-ECG had 2.3% (95% CI: 0.3% to 8.1%) sensitivity, 99.5% (95% CI: 98.6% to 99.9%) specificity, 40.0% (95% CI: 10.2% to 79.3%) positive predictive value (PPV) and 87.6% (87.3% to 88.0%) negative predictive value (NPV). At the optimal threshold for sensitivity, MACS-ECG had 50.6% sensitivity (39.6% to 61.5%), 83.1% specificity (79.9% to 86.0%), 30.1% PPV (24.7% to 36.2%) and 92.1% NPV (90.4% to 93.5%). In comparison, paramedics had a sensitivity of 71.3% (95% CI: 60.8% to 80.5%) with 53.8% (95% CI: 53.8% to 61.8%) specificity, 19.7% (17.2% to 22.45%) PPV and 93.3% (90.8% to 95.1%) NPV. CONCLUSION: Neither MACS-ECG nor paramedic ECG interpretation had a sufficiently high PPV or NPV to 'rule in' or 'rule out' NSTEMI alone.
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Alotaibi et al. (2023) conducted an observational in Suspected acute coronary syndrome (n=691). MACS-ECG prediction model vs. Subjective ECG interpretation by paramedics was evaluated on Diagnosis of acute myocardial infarction (AMI) (C-index 0.68, 95% CI 0.61-0.75). Neither the MACS-ECG model (C-index 0.68; 95% CI 0.61-0.75) nor paramedic ECG interpretation had sufficiently high predictive values to rule in or rule out NSTEMI in the pre-hospital setting.
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