Which QT Correction Formulae to Use for QT Monitoring?
Drug 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.



All 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.



Fridericia 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.
Department of Cardiovascular Sciences, University of Leuven, Belgium Department of Cardiology, University Hospitals Leuven, Leuven, Belgium bert.vandenberk@med.kuleuven.be.
Bert
B
Vandenberk
Department of Pharmaceutical and Pharmacological Sciences, University of Leuven, Belgium.
Eline
E
Vandael
Department of Cardiovascular Sciences, University of Leuven, Belgium Department of Cardiology, University Hospitals Leuven, Leuven, Belgium.
Tomas
T
Robyns
Department of Neurosciences, University of Leuven, Belgium.
Joris
J
Vandenberghe
Department of Cardiovascular Sciences, University of Leuven, Belgium Department of Cardiology, University Hospitals Leuven, Leuven, Belgium.
Christophe
C
Garweg
Department of Pharmaceutical and Pharmacological Sciences, University of Leuven, Belgium.
Veerle
V
Foulon
Department of Cardiovascular Sciences, University of Leuven, Belgium Department of Cardiology, University Hospitals Leuven, Leuven, Belgium.
Joris
J
Ector
Department of Cardiovascular Sciences, University of Leuven, Belgium Department of Cardiology, University Hospitals Leuven, Leuven, Belgium.
Rik
R
Willems
D001145:Arrhythmias, Cardiac / Q000139:chemically induced / Q000175:diagnosis* / Q000503:physiopathology; D064420:Drug-Related Side Effects and Adverse Reactions / Q000517:prevention & control*; D004562:Electrocardiography / Q000592:standards; D022062:Electrophysiologic Techniques, Cardiac / Q000592:standards; D005260:Female; D006339:Heart Rate / Q000502:physiology; D006801:Humans; D008133:Long QT Syndrome / Q000139:chemically induced / Q000175:diagnosis / Q000503:physiopathology; D008297:Male; D008875:Middle Aged; D008991:Monitoring, Physiologic / Q000379:methods; D018570:Risk Assessment
QT interval electrocardiography; electrocardiography; mortality; population; risk factors; risk prediction