ArticleBMC cardiovascular disorders2022
The best QT correction formula in a non-hospitalized population: the Fasa PERSIAN cohort study.
Article in BMC cardiovascular disorders, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed.
- From Molecules to Machines: An Integrative Framework Linking Molecular Pathogenesis, Multi-Factorial Risk, Risk Stratification, Clinical Management, and Artificial Intelligence in QT Prolongation and Sudden Cardiac Death.Clinical cardiology · 2026Review
- Prognostic Value of QT and QTc Interval Dispersion in Acute Pulmonary Embolism: A Retrospective Single-Center Study.Journal of multidisciplinary healthcare · 2026Article
- Is anaemia associated with QTc prolongation? A retrospective cross-sectional analysis from a rural population-based cohort.BMJ open · 2025Observational
- Effects of Prediabetes on Ventricular Repolarization Markers in Electrocardiography.Reviews in cardiovascular medicine · 2025Article
- Transient ischemic attack and acute ischemic stroke: evidence of altered corrected index of cardiac electrophysiological balance.Frontiers in neurology · 2025Article
- Article
- Association between QT prolongation and cardiovascular mortality in cancer patients.Cardio-oncology (London, England) · 2024Article
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Abstract
backgroundQT interval as an indicator of ventricular repolarization is a clinically important parameter on an electrocardiogram (ECG). QT prolongation predisposes individuals to different ventricular arrhythmias and sudden cardiac death. The current study aimed to identify the best heart rate corrected QT interval for a non-hospitalized Iranian population based on cardiovascular mortality.
methodsUsing Fasa PERSIAN cohort study data, this study enrolled 7071 subjects aged 35-70 years. Corrected QT intervals (QTc) were calculated by the QT interval measured by Cardiax® software from ECGs and 6 different correction formulas (Bazett, Fridericia, Dmitrienko, Framingham, Hodges, and Rautaharju). Mortality status was checked using an annual telephone-based follow-up and a minimum 3-year follow-up for each participant. Bland-Altman, QTc/RR regression, sensitivity analysis, and Cox regression were performed in IBM SPSS Statistics v23 to find the best QT. Also, for calculating the upper and lower limits of normal of different QT correction formulas, 3952 healthy subjects were selected.
resultsIn this study, 56.4% of participants were female, and the mean age was 48.60 ± 9.35 years. Age, heart rate in females, and QT interval in males were significantly higher. The smallest slopes of QTc/RR analysis were related to Fridericia in males and Rautaharju followed by Fridericia in females. Thus, Fridericia's formula was identified as the best mathematical formula and Bazett's as the worst in males. In the sensitivity analysis, however, Bazett's formula had the highest sensitivity (23.07%) among all others in cardiac mortality. Also, in the Cox regression analysis, Bazett's formula was better than Fridericia's and was identified as the best significant cardiac mortality predictor (Hazard ratio: 4.31, 95% CI 1.73-10.74, p value = 0.002).
conclusionFridericia was the best correction formula based on mathematical methods. Bazett's formula despite its poorest performance in mathematical methods, was the best one for cardiac mortality prediction. Practically, it is suggested that physicians use QTcB for a better evaluation of cardiac mortality risk. However, in population-based studies, QTcFri might be the one to be used by researchers.
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