Abstract Background QT interval measurement in the presence of right ventricular pacing (RVP) represents a clinical challenge due to altered ventricular activation resulting in a prolonged QT-interval. The aim of this study is to compare the QT interval in patients before and after ventricular pacing to develop a new formula for QT interval assessment in patients with RVP. Methods and results All patients presenting to our pacemaker clinic with single- or dual chamber device were included in this prospective observational study. Inclusion criteria were no permanent right ventricular stimulation, an intrinsic QRS interval of <120 ms, and ventricular rate >35 bpm and <150 bpm. Three 12-lead electrocardiograms were recorded for each patient: during intrinsic rhythm and 2 following an atrial paced and a ventricular paced QRS at the same rate. The intrinsic QRS and QT time/JT time (QTi/JTi) were measured during intrinsic and subsequent RVP. To obtain the formula, all measurements were performed on 100 patients (mean age 74 ± 11.3, male 33%) (RV apical lead 30% and non-apical lead 70%). Based on our measurements, a new formula QT (non-paced) = 139.23 + 0.55 xQT (paced) was derived. A population of 482 individuals (mean age 75.5±13.2 years (SD), 64% male) with permanent RV pacing were used as a validation group. The intrinsic QRS and QT time were measured during SR and subsequent RVP. To assess the relationship between the predicted QT with RVP and the measured QT without RVP, linear correlations analyses were performed. Our formula had a strong correlation with the irrespective QT without RVP (r=0.50) Conclusion We proposed a new simple formula to accurately estimate QT during RVP. This formula can be easily utilized in clinical practice. Figure 1: MAD characteristic value via plots stands for Median Absolute Difference (i.e. by how many ms the prediction is estimated on average). Figure 2: "Forest Plot" illustrates the correlation coefficients in the form of a forest plot. The dot r represents r and the bars the 95% confidence intervalsMAD characteristic value via plots standForest Plot" illustrates the correlation