Cardiac Troponin Assays With Improved Analytical Quality: A Trade-Off Between Enhanced Diagnostic Performance and Reduced Long-Term Prognostic Value.

Background Cardiac troponin (cTn) permits early rule-out/rule-in of patients admitted with possible non-ST-segment-elevation myocardial infarction. In this study, we developed an admission and a 0/1 hour rule-out/rule-in algorithm for a troponin assay with measurable results in >99% of healthy individuals. We then compared its diagnostic and long-term prognostic properties with other protocols. Methods and Results Blood samples were collected at 0, 1, 3, and 8 to 12 hours from patients admitted with possible non-ST-segment-elevation myocardial infarction. cTnT (Roche Diagnostics), cTnI (Abbott Diagnostics), and cTnI (Singulex Clarity System) were measured in 971 admission and 465 1-hour samples. An admission and a 0/1 hour rule-out/rule-in algorithm were developed for the cTnI assay and its diagnostic properties were compared with cTnT (European Society of Cardiology), cTnI, and 2 earlier cTnI algorithms. The prognostic composite end point was all-cause mortality and future nonfatal myocardial infarction during a median follow-up of 723 days. non-ST-segment-elevation myocardial infarction prevalence was 13%. The novel cTnI algorithms showed similar performance regardless of time from symptom onset, and area under the curve was significantly better than comparators. The cTnI algorithm classified 92% of patients to rule-in or rule-out compared with ≤78% of comparators. Patients allocated to rule-out by the prior published 0/1 hour algorithms had significantly fewer long-term events compared with the rule-in and observation groups. The novel cTnI algorithm used a higher troponin baseline concentration for rule-out and did not allow for prognostication. Conclusions Increasingly sensitive troponin assays may improve identification of non-ST-segment-elevation myocardial infarction but could rule-out patients with subclinical chronic myocardial injury. Separate protocols for diagnosis and risk prediction seem appropriate.