BACKGROUND: Diagnosing supraventricular arrhythmias by conventional long-term ECG can be cumbersome because of poor p-waves. Esophageal long-term electrocardiography (eECG) has an excellent sensitivity for atrial signals and may overcome this limitation. However, the optimal lead insertion depth (OLID) is not known. METHODS: We registered eECGs at different lead insertion depths in 27 patients and analyzed 199,716 atrial complexes with respect to signal amplitude and slope. Correlation and regression analyses were used to find a criterion for OLID. RESULTS: Atrial signal amplitudes and slopes significantly depend on lead insertion depth. OLID correlates with body height (rSpearman=0.71) and can be estimated by OLID [cm]=0.25*body height[cm]-7cm. At this insertion depth, we recorded the largest esophageal atrial signal amplitudes (1.27±0.86mV), which were much larger compared to conventional surface lead II (0.19±0.10mV, p<0.0001). CONCLUSION: The OLID depends on body height and can be calculated by a simple regression formula.
BACKGROUND: Diagnosing supraventricular arrhythmias by conventional long-term ECG can be cumbersome because of poor p-waves. Esophageal long-term electrocardiography (eECG) has an excellent sensitivity for atrial signals and may overcome this limitation. However, the optimal lead insertion depth (OLID) is not known. METHODS: We registered eECGs at different lead insertion depths in 27 patients and analyzed 199,716 atrial complexes with respect to signal amplitude and slope. Correlation and regression analyses were used to find a criterion for OLID. RESULTS:Atrial signal amplitudes and slopes significantly depend on lead insertion depth. OLID correlates with body height (rSpearman=0.71) and can be estimated by OLID [cm]=0.25*body height[cm]-7cm. At this insertion depth, we recorded the largest esophageal atrial signal amplitudes (1.27±0.86mV), which were much larger compared to conventional surface lead II (0.19±0.10mV, p<0.0001). CONCLUSION: The OLID depends on body height and can be calculated by a simple regression formula.