Efficacy and safety of intracoronary pro-urokinase combined with low-pressure balloon pre-dilatation during percutaneous coronary intervention in patients with anterior ST-segment elevation myocardial infarction.

BACKGROUND: The efficacy and safety of low-pressure balloon pre-dilatation before intracoronary pro-urokinase (pro-UK) in preventing no-reflow during percutaneous coronary intervention (PCI) remains unknown. This study aimed to evaluate the clinical outcomes of intracoronary pro-UK combined with low-pressure balloon pre-dilatation in patients with anterior ST-segment-elevation myocardial infarction (STEMI). METHODS: This was a randomized, single-blind, investigator-initiated trial that included 179 patients diagnosed with acute anterior STEMI. All patients were eligible for PCI and were randomized into two groups: intracoronary pro-UK combined with (ICPpD group, n = 90) or without (ICP group, n = 89) low-pressure balloon pre-dilatation. The main efficacy endpoint was complete epicardial and myocardial reperfusion. The safety endpoints were major adverse cardiovascular events (MACEs), which were analyzed at 12 months follow-up. RESULTS: Patients in the ICPpD group presented significantly higher TIMI myocardial perfusion grade 3 (TMPG3) compared to those in the ICP group (77.78% versus 68.54%, P = 0.013), and STR ≥ 70% after PCI 30 min (34.44% versus 26.97%, P = 0.047) or after PCI 90 min (40.0% versus 31.46%, P = 0.044). MACEs occurred in 23 patients (25.56%) in the ICPpD group and in 32 patients (35.96%) in the ICP group. There was no difference in hemorrhagic complications during hospitalization between the groups. CONCLUSION: Patients with acute anterior STEMI presented more complete epicardial and myocardial reperfusion with adjunctive low-pressure balloon pre-dilatation before intracoronary pro-UK during PCI. TRIAL REGISTRATION: 2019xkj213.

Multivariate weighted recurrence network analysis of EEG signals from ERP-based smart home system.

Smart home has been widely used to improve the living quality of people. Recently, the brain-computer interface (BCI) contributes greatly to the smart home system. We design a BCI-based smart home system, in which the event-related potentials (ERP) are induced by the image interface based on the oddball paradigm. Then, we investigate the influence of mental fatigue on the ERP classification by the Fisher linear discriminant analysis. The results indicate that the classification accuracy of ERP decreases as the brain evolves from the normal stage to the mental fatigue stage. In order to probe into the difference of the brain, cognitive process between mental fatigue and normal states, we construct multivariate weighted recurrence networks and analyze the variation of the weighted clustering coefficient and weighted global efficiency corresponding to these two brain states. The findings suggest that these two network metrics allow distinguishing normal and mental fatigue states and yield novel insights into the brain fatigue behavior resulting from a long use of the ERP-based smart home system. These properties render the multivariate recurrence network, particularly useful for analyzing electroencephalographic recordings from the ERP-based smart home system.