CardioExchange Archive

More than three-quarters of people with chest pain can be triaged within an hour of arrival at the emergency department with a novel strategy utilizing high-sensitivity cardiac troponin (hs-cTnT), according to a study from Switzerland published in the Archives of Internal Medicine. The strategy is promising, according to an accompanying editorial, but much work remains before it can be implemented in clinical practice.

Tobias Reichlin and colleagues first studied 436 patients and developed a treatment algorithm utilizing hs-cTnT baseline changes and absolute changes over the initial hour. The algorithm was then tested in a second validation cohort of 436 patients, with the following results:

• 60% were classified as “rule-out”
• 17% were classified as “rule-in”
• 23% required further observation
• Overall sensitivity and negative predictive value: 100% for rule-out
• Specificity for rule-in: 97%
• Positive predictive value for rule-in: 84%
• Prevalence of MI in the observational group:  8%
• 30-day survival: 99.8% in the rule-out group, 98.6% in the observational group, and 95.3% in the rule-in group

The authors claim that their strategy “may obviate the need for prolonged monitoring and serial blood sampling in 3 of 4 patients.”

In an accompanying comment, L. Kristin Newby writes that the Swiss study “is a major advance in understanding the application of hsTn testing that with continued development could substantially improve evaluation of ED patients with suspected MI.” However, she notes that the excellent results obtained in this initial study will probably not be equalled in the real world. In addition, she writes, “although touted as ‘simple’ by the authors, the need for multicomponent algorithms that are different for rule-in and rule-out and that vary by age group or other parameters will challenge application by busy clinicians unlikely to remember or accurately process the proposed algorithm. As such, it will be imperative that hsTn algorithms, if validated, are built into clinical decision support layered onto electronic health records so that testing results are provided electronically to physicians along with the algorithmic interpretation to allow systematic application in triage and treatment.”