Po-02-087 novel device-based discriminators improve differentiation of polymorphic vt and vf from monomorphic vt in implantable cardiac defibrillators

ICDs rely upon programmable rate cutoffs to direct therapy delivery. Studies showing reduced mortality when high voltage therapy (HVT) is avoided have led to programming that promotes longer detection times and higher detection rates. However, such programming can also result in delayed therapy for hemodynamically compromising polymorphic VT (PVT) or ventricular fibrillation (VF). We aim to characterize ventricular tachyarrhythmia (VTA) features and develop an algorithm to improve discriminating power for PVT/VF versus MVT to enable tailored HVT. Dataset of de-identified episodes of VTA from Abbott’s Merlin.net database were adjudicated as PVT/VF or MVT by three blinded Electrophysiologists independently. Cohen’s Kappa score measured inter-observer agreement. Four discriminators from near-field ventricular channel during VTA were evaluated. 1) Mean cycle length (CL), 2) Rate-adjusted interval instability (RAII), defined as range of RR intervals divided by mean CL, 3) Mean peak amplitude, and 4) Mean peak amplitude instability, defined as mean difference of consecutive peak amplitudes. Receiver operating characteristic (ROC) curves and area under curve (AUC) scores were computed for each discriminator. The predictive performance of discriminators was assessed via multiple linear regression. Eighty VTA episodes (34 PVT/VF and 46 MVT) were adjudicated with excellent inter-observer agreement (kappa ≥ 0.9). All four discriminators showed significant difference between groups and each had good predictive ability to classify PVT/VF (Table 1). Multiple linear regression showed all discriminators reliably predicted PVT/VF (each p<0.001). The combination of all 4 discriminators best predicted PVT/VF (sum of squared errors =3.7 vs 12.0 for Mean CL alone). An algorithm for PVT/VF vs MVT discrimination incorporating all 4 individual discriminators achieved diagnostic sensitivity of 94% and specificity of 96%. Tachycardia rate cutoff sub-optimally differentiates PVT/VF from MVT. Discriminators based on variability and magnitude of intervals and peak amplitudes accurately identifies PVT/VF. Incorporating these discriminators in a device-based algorithm could tailor therapy ensuring prompt treatment in the highest risk arrhythmias while safely extending time to therapy to reduce unnecessary HVT.Tabled 1Table 1 - Characteristics of discriminators in PVT/VF and MVT groupsDiscriminatorPVT/VFMVTp-valueROC-AUCMean cycle length (ms)314±43423±83<0.0010.87Rate-adjusted interval instability (ms/ms)0.52±0.380.08±0.08<0.0010.90Mean peak amplitude (mV)3.1±1.85.8±1.3<0.0010.89Mean peak amplitude instability (mV)0.63±0.460.16±0.34<0.0010.87 Open table in a new tab