The reliability of cardiogenic impedance and correlation with echocardiographic and plethysmographic parameters for predicting CRT time intervals post implantation.

AIMS

Encouraging data have been reported on the use of cardiogenic impedance (CI) in cardiac resynchronization therapy (CRT) optimization. The purposes of this study were to: evaluate the stability of certain CI vectors 24 h postimplantation, study the correlation between these CI signals and selected echocardiographic parameters, and examine the possibility of non-invasive calibration of the patient-specific impedance-based prediction model.

METHODS AND RESULTS

Thirteen patients received a CRT-defibrillator device with monitor capability of the dynamic impedance between several electrodes. At implantation, a patient-specific impedance-based prediction model was created for identification of optimal atrioventricular and interventricular (VV) delays and calibrated on invasive measurements of left ventricular contractility (LV dP/dtmax). Simultaneously, non-invasive measurements of LV dP/dtmax and stroke volume (SV) were obtained using a finger plethysmograph. Patients were re-evaluated with echocardiography and new CI measurements the day after implantation. The hemodynamic benefit achieved by optimal VV setting according to the patient-specific impedance-based prediction model at follow-up was not as large as the one obtained at implantation. In a multivariate partial least square regression analysis, a correlation was found between aortic velocity time integral (VTI) and a generic linear combination of CI features (P < 0,005). No correlation was found between the patient-specific impedance-based prediction models and the non-invasive measurements of LV dP/dtmax and SV.

CONCLUSION

Cardiogenic impedance signals can be used to optimize CRT settings but seem less feasible as an ambulatory tool since calibration is required. The positive correlation between aortic VTI and CI measurements seems promising, although a larger cohort is required to create an echocardiography-based patient-specific model.