A 0/1h-algorithm using cardiac myosin-binding protein C for early diagnosis of myocardial infarction

European Heart Journal - Acute CardioVascular Care

12 February 2022

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Abstract

AbstractAims

Cardiac myosin-binding protein C (cMyC) demonstrated high diagnostic accuracy for the early detection of non-ST-elevation myocardial infarction (NSTEMI). Its dynamic release kinetics may enable a 0/1h-decision algorithm that is even more effective than the ESC hs-cTnT/I 0/1 h rule-in/rule-out algorithm.

Methods and results

In a prospective international diagnostic study enrolling patients presenting with suspected NSTEMI to the emergency department, cMyC was measured at presentation and after 1 h in a blinded fashion. Modelled on the ESC hs-cTnT/I 0/1h-algorithms, we derived a 0/1h-cMyC-algorithm. Final diagnosis of NSTEMI was centrally adjudicated according to the 4th Universal Definition of Myocardial Infarction. Among 1495 patients, the prevalence of NSTEMI was 17%. The optimal derived 0/1h-algorithm ruled-out NSTEMI with cMyC 0 h concentration below 10 ng/L (irrespective of chest pain onset) or 0 h cMyC concentrations below 18 ng/L and 0/1 h increase <4 ng/L. Rule-in occurred with 0 h cMyC concentrations of at least 140 ng/L or 0/1 h increase ≥15 ng/L. In the validation cohort (n = 663), the 0/1h-cMyC-algorithm classified 347 patients (52.3%) as ‘rule-out’, 122 (18.4%) as ‘rule-in’, and 194 (29.3%) as ‘observe’. Negative predictive value for NSTEMI was 99.6% [95% confidence interval (CI) 98.9–100%]; positive predictive value 71.1% (95% CI 63.1–79%). Direct comparison with the ESC hs-cTnT/I 0/1h-algorithms demonstrated comparable safety and even higher triage efficacy using the 0h-sample alone (48.1% vs. 21.2% for ESC hs-cTnT-0/1 h and 29.9% for ESC hs-cTnI-0/1 h; P < 0.001).

Conclusion

The cMyC 0/1h-algorithm provided excellent safety and identified a greater proportion of patients suitable for direct rule-out or rule-in based on a single measurement than the ESC 0/1h-algorithm using hs-cTnT/I.

Trial registration

ClinicalTrials.gov number, NCT00470587.

Contributors

ESC 365 is supported by

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