14 research outputs found

    Impact of ganglionated plexi ablation on high-frequency stimulation-induced changes in atrial fibrillation cycle length in the pulmonary vein

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    AbstractBackgroundWe assessed high-frequency stimulation (HFS)-induced changes in the atrial fibrillation (AF) cycle length (AFCL) in the pulmonary vein (PV) after ganglionated plexi (GP) ablation.MethodsTwenty-two patients undergoing catheter ablation for AF were retrospectively enrolled. Sites showing a vagal response (VR) to HFS were defined as GP-positive sites. AFCL was determined in the adjacent PV, distant PV, coronary sinus, and right atrium. Twenty cycles were counted before and after each HFS. After radiofrequency application to the GP site, HFS was repeated.ResultsAt GP-positive sites (n=57), significant shortening of the AFCL was detected in the adjacent PV (17% shortening, 165Ā±38 to 137Ā±27ms, p<0.001) and distant PV (4.8% shortening, p<0.001), but not in the coronary sinus (0.8% shortening, p=0.27) or right atrium (1.8% shortening, p=0.06). However, no significant shortening was observed at GP-negative sites (n=25). At 41 of the 57 sites where VR disappeared after a single radiofrequency application, no significant shortening was observed in the adjacent PV (2.1% shortening, p=0.25). At 16 of the 57 sites where VR was still present, significant shortening was observed in the adjacent PV (16% shortening, p<0.001).ConclusionsHFS of the GP has a strong influence on AFCL in the PV

    Inappropriate implantable cardioverter defibrillator shocksā€”incidence, effect, and implications for driver licensing

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    PurposePatients with implantable cardioverter defibrillators (ICDs) have an ongoing risk of sudden incapacitation that may cause traffic accidents. However, there are limited data on the magnitude of this risk after inappropriate ICD therapies. We studied the rate of syncope associated with inappropriate ICD therapies to provide a scientific basis for formulating driving restrictions.MethodsInappropriate ICD therapy event data between 1997 and 2014 from 50 Japanese institutions were analyzed retrospectively. The annual risk of harm (RH) to others posed by a driver with an ICD was calculated for private driving habits. We used a commonly employed annual RH to others of 5 in 100,000 (0.005%) as an acceptable risk threshold.ResultsOf the 4089 patients, 772 inappropriate ICD therapies occurred in 417 patients (age 61 Ā± 15 years, 74% male, and 65% secondary prevention). Patients experiencing inappropriate therapies had a mean number of 1.8 Ā± 1.5 therapy episodes during a median follow-up period of 3.9 years. No significant differences were found in the age, sex, or number of inappropriate therapies between patients receiving ICDs for primary or secondary prevention. Only three patients (0.7%) experienced syncope associated with inappropriate therapies. The maximum annual RH to others after the first therapy in primary and secondary prevention patients was calculated to be 0.11 in 100,000 and 0.12 in 100,000, respectively.ConclusionsWe found that the annual RH from driving was far below the commonly cited acceptable risk threshold. Our data provide useful information to supplement current recommendations on driving restrictions in ICD patients with private driving habits

    Tissue clearing method in visualization of cancer progression and metastasis

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    Since various imaging modalities have been developed, cancer metastasis can be detected from an early stage. However, limitations still exist, especially in terms of spatial resolution. Tissue-clearing technology has emerged as a new imaging modality in cancer research, which has been developed and utilized for a long time mainly in neuroscience field. This method enables us to detect cancer metastatic foci with single-cell resolution at whole mouse body/organ level. On top of that, 3D images of cancer metastasis of whole mouse organs make it easy to understand their characteristics. Recently, further applications of tissue clearing methods were reported in combination with reporter systems, labeling, and machine learning. In this review, we would like to provide an overview of this technique and current applications in cancer research and discuss their potentials and limitations
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