Which QT Correction Formulae to Use for QT Monitoring?

Abstract

BackgroundDrug safety precautions recommend monitoring of the corrected QT interval. To determine which QT correction formula to use in an automated QT‐monitoring algorithm in our electronic medical record, we studied rate correction performance of different QT correction formulae and their impact on risk assessment for mortality. Methods and ResultsAll electrocardiograms (ECGs) in patients >18 years with sinus rhythm, normal QRS duration and rate <90 beats per minute (bpm) in the University Hospitals of Leuven (Leuven, Belgium) during a 2‐month period were included. QT correction was performed with Bazett, Fridericia, Framingham, Hodges, and Rautaharju formulae. In total, 6609 patients were included (age, 59.8±16.2 years; 53.6% male and heart rate 68.8±10.6 bpm). Optimal rate correction was observed using Fridericia and Framingham; Bazett performed worst. A healthy subset showed 99% upper limits of normal for Bazett above current clinical standards: men 472 ms (95% CI, 464–478 ms) and women 482 ms (95% CI 474–490 ms). Multivariate Cox regression, including age, heart rate, and prolonged QTc, identified Framingham (hazard ratio [HR], 7.31; 95% CI, 4.10–13.05) and Fridericia (HR, 5.95; 95% CI, 3.34–10.60) as significantly better predictors of 30‐day all‐cause mortality than Bazett (HR, 4.49; 95% CI, 2.31–8.74). In a point‐prevalence study with haloperidol, the number of patients classified to be at risk for possibly harmful QT prolongation could be reduced by 50% using optimal QT rate correction. ConclusionsFridericia and Framingham correction formulae showed the best rate correction and significantly improved prediction of 30‐day and 1‐year mortality. With current clinical standards, Bazett overestimated the number of patients with potential dangerous QTc prolongation, which could lead to unnecessary safety measurements as withholding the patient of first‐choice medication.

Keywords

• electrocardiography
• mortality
• population
• QT interval electrocardiography
• risk factors
• risk prediction