Key result
QTcAd achieves ~92% sensitivity for detecting congenital LQTS vs QTcB while maintaining high specificity.
Why the study?
Traditional heart rate-adjusted QT correction formulae often fail to eliminate the inverse heart rate-QT relationship in pediatric patients, risking erroneous congenital long QT syndrome classification.
Does an enhanced demographically adaptive QT correction (QTcAd) formula improve congenital long QT syndrome detection performance compared to traditional QTcB in pediatric patients?
Observational (n=9,089)
Yes
Does an enhanced demographically adaptive QT correction (QTcAd) formula improve congenital long QT syndrome detection performance compared to traditional QTcB in pediatric patients?
Absolute Event Rate: 92% vs 46.7%
An enhanced demographically adaptive QT correction formula significantly improves the sensitivity of congenital long QT syndrome screening in pediatric patients while reducing false-positive classifications compared to traditional Bazett's correction.
QTcAd may boost pediatric LQTS screening sensitivity with preserved specificity; hypothesis-generating and requires prospective validation before practice change.
Background: Traditional heart rate (HR) adjusted QT correction (QTc) formulae often fail to eliminate the inverse HR-QT interval relationship, particularly in pediatric patients. In this study, we optimized our previously published adaptive QTc (QTcAd) formula by including additional demographic variables and broadening the pediatric age range. We tested the hypothesis that QTcAd improves congenital long QT syndrome (congenital LQTS) detection performance and reduces erroneous classifications across pediatric cohorts. Methods: We retrospectively analyzed 8,306 ECGs from 4,556 cardiovascular disease (CVD)-free pediatric patients. For neonatal patients (1-30 days old), we derived daily QTcAd parameter values. For older patients, we developed regression models to estimate QTcAd parameters (mean Heart Rate (HR) =-15.9ln(days) + 219; |m| = 0.0001(days) + 1, where |m|=absolute HR-QT regression slope). To support LQTS screening, we constructed dynamic QTcAd thresholds by estimating age-specific reference limits. Diagnostic performance was tested in a clinically confirmed LQTS cohort (n=137), and further evaluated in the Pediatric Heart Network (PHN; n=2,394) and Emergency Department (ED; n=2,002) cohorts. Results: Using the confirmed LQTS cohort as the event population and the CVD-free cohort as the non-event population, QTcAd demonstrated higher sensitivity than QTcB (92% vs 46.7%). QTcAd maintained high specificity (96.9% vs 98.9%), which resulted in a higher Youden index (0.889 vs 0.456). In the PHN healthy cohort, both QTc formulae classified the majority of individuals as normal (QTcAd 95%; QTcB 98.2%) indicating few false-positives. In the ED cohort, QTcAd reduced borderline/prolonged QTc classifications requiring follow-up, yielding 270 fewer repeat-testing triggers than QTcB. We developed a publicly accessible calculator to compute QTcAd and classify congenital LQTS risk. Conclusion: We developed and validated an enhanced QTcAd formula for pediatric patients. QTcAd-based-age-adjusted dynamic thresholding improved performance for congenital LQTS screening, while maintaining high specificity. This reduces false-positive LQTS classifications and repeat ECGs, thereby decreasing unnecessary downstream clinical evaluation.
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Haq et al. (2026) conducted an observational in Congenital Long QT Syndrome (n=9,089). Adaptive QTc (QTcAd) formula vs. Bazett's QTc (QTcB) formula was evaluated on Sensitivity for congenital LQTS detection. The adaptive QTc (QTcAd) formula demonstrated higher sensitivity (92% vs 46.7%) and maintained high specificity (96.9% vs 98.9%) compared to QTcB for detecting congenital long QT syndrome.
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