Corrected QT Interval Calculator

You can use this QTc calculator to determine the corrected QT interval (QTc) in seconds in accordance with someone's heart rate (beats per minute). The QTc calculator relies on the formulas that are most commonly used to determine a QTc interval.

How to use the corrected QT interval calculator:

  1. Input the QT interval data provided by the ECG (msec or sec).
  2. Input the patient's heart rate in beats per minute.
  3. Choose QTc Formula and then click on the "Calculate" button to generate the corrected QT interval (QTc) figure*.
QTc Calculator

bpm

Reference

The QTc calculator is designed to compute the corrected QT interval, which is an estimation of the QT interval when a heart is beating at a rate of 60 bpm. Determining the corrected QT interval can allow practitioners to compare QT values over time at a variety of heart rates. It can also help doctors to better identify which patients are at a higher risk of developing arrhythmias.

The standard QT values are below 0.45 seconds for men and 0.46 seconds for women. If levels deviate significantly from these values, there is a risk the patient is suffering from ventricular tachyarrhythmias.

Multiple formulas can be employed to determine QTc. Some of these are as follows:

Bazett's formula (logarithmic correction): QTc = QT × RR -1/2

Fredericia's formula (logarithmic correction): QTc = QT × RR -1/3

Hodges formula (linear correction): QTc = QT + 105 / RR - 105

Framingham formula (linear correction): QTc = QT + 0.154 × (1 - RR)

Where, RR Interval = 60 / Heart Rate (expressed in seconds)

The Bazett formula was first presented by Henry Cuthbert Bazett in 1920. It is commonly used because it offers a simple approach to determining QTc. It under-corrects at heart rates below 60 bpm and over-corrects at heart rates above 100 bpm. However, it provides an acceptable correction for heart rates that fall within the range of 60-100 bpm.

*All of the information presented on this page is given for educational purposes only. This data should not be used to diagnosis or treat any diseases or health problems.

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