Direct comparison of a novel antitachycardia pacing algorithm against present methods using virtual patient modeling.

BACKGROUND: Antitachycardia pacing (ATP) success rates as low as 50% for fast ventricular tachycardias (VTs) have been reported providing an opportunity for improved ATP to decrease shocks. OBJECTIVE: The purpose of this study was to determine how a new automated antitachycardia pacing (AATP) therapy would perform compared with traditional burst ATP using computer modeling to conduct a virtual study. METHODS: Virtual patient scenarios were constructed from magnetic resonance imaging and electrophysiological (EP) data. Cardiac EP simulation software (CARPEntry) was used to generate reentrant VT. Simulated VT exit sites were physician adjudicated against corresponding clinical 12-lead electrocardiograms. Burst ATP comprised 3 sequences of 8 pulses at 88% of VT cycle length, with each sequence decremented by 10 ms. AATP was limited to 3 sequences, with each sequence learning from the previous sequences. RESULTS: Two hundred fifty-nine unique ATP scenarios were generated from 7 unique scarred hearts. Burst ATP terminated 145 of 259 VTs (56%) and accelerated 2.0%. AATP terminated 189 of 259 VTs (73%) with the same acceleration rate. The 2 dominant ATP failure mechanisms were identified as (1) insufficient prematurity to close the excitable gap; and (2) failure to reach the critical isthmus of the VT. AATP reduced failures in these categories from 101 to 63 (44% reduction) without increasing acceleration. CONCLUSION: AATP successfully adapted ATP sequences to terminate VT episodes that burst ATP failed to terminate. AATP was successful with complex scar geometries and EP heterogeneity as seen in the real world.

Hemodynamic factors associated with acute decompensated heart failure: part 2--use in automated detection.

BACKGROUND: The purpose of this study was to develop an automated surveillance system, using pressure-based hemodynamic factors that would detect which patients were making the transition from compensated to decompensated heart failure before they developed worsening symptoms and required acute medical care. METHODS AND RESULTS: Intracardiac pressures in 274 patients with heart failure were measured using an implantable hemodynamic monitor (IHM) and were analyzed in a retrospective manner. An automated pressure change detection (PCD) algorithm was developed using the cumulative sum method. The performance characteristics of the PCD algorithm were defined in all patients who developed a heart failure-related event (HFRE); patients without HFRE served as controls. Optimal PCD threshold values were chosen using a receiver operator curve analysis. Each of the pressures measured with the IHM were evaluated using the PCD analysis. All had sensitivities ≥80% and false-positive rates <4.7/patient-year; however, estimated pulmonary artery diastolic pressure (ePAD) had the best performance. An ePAD based on the optimized PCD threshold of 6.0 yielded a sensitivity of 83% and a false-positive rate of 4.1/patient-year for detecting patients making the transition from compensated to decompensated heart failure. These performance characteristics were not significantly different for patients with an ejection fraction > vs. <50%, estimated glomerular filtration rate > vs. <60 mL/min/1.73 m(2), or age > vs. <60 years. CONCLUSIONS: The automated PCD algorithm had high sensitivity and acceptable false-positive rates in detecting the development of decompensated heart failure before the patient developed worsening symptoms and required acute medical care. These data support the development of a prospective study to examine the utility of adding an automated PCD algorithm to IHM-based management strategies to prevent decompensated heart failure.