Written by Kimiko Dunbar
Spoon Feed
A clinical prediction rule for myocarditis dubbed C-FAST: 1) chest pain, 2) fever, 3) AV/ST (any atrioventricular conduction delays/ST segment changes) has 99% sensitivity and 14% specificity for myocarditis.
Fever, chest pain, and EKG changes walk into a bar…
Myocarditis is a rare condition with sometimes subtle presentation and frequently a nonspecific viral prodrome, as we covered yesterday. The gold standard for diagnosis is endomyocardial biopsy (obviously invasive), with limited data on how to predict those who are at lower risk. This retrospective case-control study aimed to derive a clinical prediction rule to identify children and young adults at low risk for myocarditis, potentially avoiding troponin testing or imaging. Among 93 myocarditis cases and 202 controls, three predictors – chest pain, fever, and AV/ST changes (C-FAST) – had a combined sensitivity of 99% and specificity of 14%. Troponin T showed strong diagnostic performance (AUC 0.96). Limitations include single-center design, retrospective data, and limited generalizability to younger children and low-risk populations. Also, this decision tool has not been validated.
How does this change my practice?
The sensitivity and negative prediction value of this rule is promising, but the specificity is quite low. Put simply, you probably won’t miss a kid with myocarditis with this combo, but only 14% of kids without myocarditis would be screened out by this rule. More research is needed to validate this rule in a broader population of patients, but I think it’s worth considering in an informal way when evaluating a kid with concern for myocarditis.
Editor’s note: This decision tool is not ready for clinical use, but the handy mnemonic (C-FAST) helps me remember what to look for and to keep myocarditis on my differential. ~Clay Smith
Source
A Prediction Rule to Identify Children and Young Adults at Low Risk for Myocarditis. Pediatr Emerg Care. 2025 Feb 20. doi: 10.1097/PEC.0000000000003354. Epub ahead of print. PMID: 39976221
