Why the study?
Does the choice of QTc correction formula impact the estimated prevalence and diagnostic probability of short QT syndrome in young adults?
Does the choice of QTc correction formula impact the estimated prevalence and diagnostic probability of short QT syndrome in young adults?
Applying different QTc correction formulae leads to significant reclassification of SQTS probability, suggesting that reliance on Bazett's formula may underestimate the number of individuals meeting diagnostic criteria.
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Highlights diagnostic variability depending on the correction formula used; leaves open which method best predicts true short.
Objective To assess the prevalence of short corrected QT (QTc) intervals and its impact on short QT syndrome (SQTS) diagnosis using different QT correction formulae. Methods Observational study. The prevalence of short QTc intervals was estimated using four different QT correction formulae in 14 662 young adults from the ‘Sudden Cardiac Death Screening of Risk FactOrS’ (SCD-SOS) cohort. Then, using data from this cohort and the pooled-cohort analysed by Gollob et al, comprising 61 patients with SQTS, we assessed the impact of the different QTc correction formulae on SQTS probability and diagnosis based on the Expert Consensus recommendations (QTc ≤330 ms or QTc 330–360 ms+1 additional risk feature). Results The prevalence of individuals with a QTc ≤330 and ≤320 ms in the SCD-SOS cohort was extremely low (≤0.07% and≤0.02%, respectively), and these were more frequently identified by the Framingham correction. The different QTc correction formulae led to a shift in SQTS probability in 5%–10% of individuals in both the SCD-SOS and Gollob cohort). Intermediate probability individuals were rare (<0.1%), and no high-SQTS probability individuals were identified in the SCD-SOS cohort. Based on Consensus criteria, instead of 12 (0.08%) individuals being diagnosed with SQTS using the Bazett equation, a different number of individuals would meet diagnostic criteria with the other formulae: 11 (0.08%) using Fridericia, 9 (0.06%) with Hodges and 16 (0.11%) using the Framingham equation. Conclusion Prevalence of SQTS in the apparently healthy adult population is low. Applying different QTc correction formulae leads to significant reclassification of SQTS probability and their impact on predicting outcomes should be assessed.
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Providência et al. (2017) studied this question.
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