Risk factors for the first and second inappropriate implantable cardioverter-defibrillator therapy

Introduction: Various risk factors for the first inappropriate implantable cardioverter-defibrillator (ICD) therapy event have been reported, including a history of atrial fibrillation/atrial flutter (AF/AFL), younger age, and multiple zones. Nonetheless, which factors are concordant with real-world data has not been clarified, and risk factors for the second inappropriate ICD therapy event have not been well examined. This study aimed to clarify the risk factors for the first and second inappropriate ICD therapy events. Methods: We conducted a post-hoc secondary analysis of data from a multicenter, prospective observational study (the Nippon Storm Study) designed to clarify the risk factors for electrical storm. Results: The analysis included data from 1549 patients who received ICD or cardiac resynchronization therapy with defibrillator (CRT-D). Over a median follow-up of 28 months, 293 inappropriate ICD therapy events occurred in 153 (10.0%) patients. On multivariate Cox regression analysis, the risk factors for the first inappropriate ICD therapy event were younger age (hazard ratio [HR], 0.986; p = 0.028), AF/AFL (HR, 2.324; p = 0.002), ICD without CRT implantation (HR, 2.377; p = 0.004), and multiple zones (HR, 1.852; p = 0.010). "No-intervention" after the first inappropriate ICD therapy event was the sole risk factor for the second inappropriate ICD therapy event. Conclusions: Risk factors for the first inappropriate ICD therapy event were similar to those previously reported. Immediate intervention after the first inappropriate ICD therapy event could reduce the risk of the second inappropriate event

Fabrication and characterization of an L3 nanocavity designed by an iterative machine-learning method

Optical nanocavities formed by defects in a two-dimensional photonic crystal (PC) slab can simultaneously realize a very small modal volume and an ultrahigh quality factor (Q). Therefore, such nanocavities are expected to be useful for the enhancement of light-matter interaction and slowdown of light in devices. In the past, it was difficult to design a PC hole pattern that makes sufficient use of the high degree of structural freedom of this type of optical nanocavity, but very recently, an iterative optimization method based on machine learning was proposed that efficiently explores a wide parameter space. Here, we fabricate and characterize an L3 nanocavity that was designed by using this method and has a theoretical Q value of 29 x 10(6) and a modal volume of 0.7 cubic wavelength in the material. The highest unloaded Q value of the fabricated cavities is 4.3 x 10(6); this value significantly exceeds those reported previously for an L3 cavity, i.e., approximate to 2.1 x 10(6). The experimental result shows that the iterative optimization method based on machine learning is effective in improving cavity Q values