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The best QT correction formula in a non-hospitalized population: the Fasa PERSIAN cohort study

BACKGROUND: QT 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 corr...

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Autores principales: Yazdanpanah, Mohammad Hosein, Naghizadeh, Mohammad Mehdi, Sayyadipoor, Sepideh, Farjam, Mojtaba
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8851728/
https://www.ncbi.nlm.nih.gov/pubmed/35172723
http://dx.doi.org/10.1186/s12872-022-02502-2
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author Yazdanpanah, Mohammad Hosein
Naghizadeh, Mohammad Mehdi
Sayyadipoor, Sepideh
Farjam, Mojtaba
author_facet Yazdanpanah, Mohammad Hosein
Naghizadeh, Mohammad Mehdi
Sayyadipoor, Sepideh
Farjam, Mojtaba
author_sort Yazdanpanah, Mohammad Hosein
collection PubMed
description BACKGROUND: QT 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. METHODS: Using 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. RESULTS: In 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). CONCLUSION: Fridericia 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. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12872-022-02502-2.
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spelling pubmed-88517282022-02-22 The best QT correction formula in a non-hospitalized population: the Fasa PERSIAN cohort study Yazdanpanah, Mohammad Hosein Naghizadeh, Mohammad Mehdi Sayyadipoor, Sepideh Farjam, Mojtaba BMC Cardiovasc Disord Research Article BACKGROUND: QT 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. METHODS: Using 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. RESULTS: In 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). CONCLUSION: Fridericia 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. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12872-022-02502-2. BioMed Central 2022-02-16 /pmc/articles/PMC8851728/ /pubmed/35172723 http://dx.doi.org/10.1186/s12872-022-02502-2 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research Article
Yazdanpanah, Mohammad Hosein
Naghizadeh, Mohammad Mehdi
Sayyadipoor, Sepideh
Farjam, Mojtaba
The best QT correction formula in a non-hospitalized population: the Fasa PERSIAN cohort study
title The best QT correction formula in a non-hospitalized population: the Fasa PERSIAN cohort study
title_full The best QT correction formula in a non-hospitalized population: the Fasa PERSIAN cohort study
title_fullStr The best QT correction formula in a non-hospitalized population: the Fasa PERSIAN cohort study
title_full_unstemmed The best QT correction formula in a non-hospitalized population: the Fasa PERSIAN cohort study
title_short The best QT correction formula in a non-hospitalized population: the Fasa PERSIAN cohort study
title_sort best qt correction formula in a non-hospitalized population: the fasa persian cohort study
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8851728/
https://www.ncbi.nlm.nih.gov/pubmed/35172723
http://dx.doi.org/10.1186/s12872-022-02502-2
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