Background The vasovagal reflex syndrome （VVRS） is common in the patiems undergoing percutaneous coronary intervemion （PCI） However, prediction and prevention of the risk for the VVRS have not been completely fulf...Background The vasovagal reflex syndrome （VVRS） is common in the patiems undergoing percutaneous coronary intervemion （PCI） However, prediction and prevention of the risk for the VVRS have not been completely fulfilled. This study was conducted to develop a Risk Prediction Score Model to identify the determinants of VVRS in a large Chinese population cohort receiving PCI. Methods From the hos- pital electronic medical database, we idemified 3550 patients who received PCI （78.0% males, mean age 60 years） in Chinese PLA General Hospital from January 1, 2000 to August 30, 2016. The multivariate analysis and receiver operating characteristic 01OC） analysis were performed. Results The adverse events of VVRS in the patients were significantly increased after PCI procedure than before the operation （all P 〈 0.001）. The rate of VVRS [95% confidence interval （CI）] in patients receiving PCI was 4.5% （4.1%-5.6%）. Compared to the patients suffering no VVRS, incidence of VVRS involved the following factors, namely female gender, primary PCI, hypertension, over two stems im- plantation in the left anterior descending （LAD）, and the femoral puncture site. The multivariate analysis suggested that they were independ- ent risk factors for predicting the incidence of VVRS （all P 〈 0.001）. We developed a risk prediction score model for VVRS. ROC analysis showed that the risk prediction score model was effectively predictive of the incidence of VVRS in patients receiving PCI （c-statistic 0.76, 95% CI： 0.72-0.79, P 〈 0.001）. There were decreased evems of VVRS in the patients receiving PCI whose diastolic blood pressure dropped by more than 30 mmHg and heart rate reduced by 10 times per minute （AUC： 0.84, 95% CI： 0.81-0.87, P 〈 0.001）. Conclusion The risk prediction score is quite efficient in predicting the incidence of VVRS in patients receiving PCI. In which, the following factors may be in- volved, the femoral puncture site, female gender, hypertension, primary PCI, and over 2 stents implanted in LAD.展开更多
Particles,including soot,aerosol and ash,usually exist as fractal aggregates.The radiative properties of the particle fractal aggregates have a great influence on studying the light or heat radiative transfer in the p...Particles,including soot,aerosol and ash,usually exist as fractal aggregates.The radiative properties of the particle fractal aggregates have a great influence on studying the light or heat radiative transfer in the particle medium.In the present work,the performance of the single-layer inversion model and the double-layer inversion model in reconstructing the geometric structure of particle fractal aggregates is studied based on the light reflectancetransmittance measurement method.An improved artificial fish-swarm algorithm(IAFSA)is proposed to solve the inverse problem.The result reveals that the accuracy of double-layer inversion model is more satisfactory as it can provide more uncorrelated information than the single-layer inversion model.Moreover,the developed IAFSA show higher accuracy and better robustness than the original artificial fish swarm algorithm(AFSA)for avoiding local optimization problems effectively.As a whole,the present work supplies a useful kind of measurement technology for predicting geometrical morphology of particle fractal aggregates.展开更多
文摘Background The vasovagal reflex syndrome （VVRS） is common in the patiems undergoing percutaneous coronary intervemion （PCI） However, prediction and prevention of the risk for the VVRS have not been completely fulfilled. This study was conducted to develop a Risk Prediction Score Model to identify the determinants of VVRS in a large Chinese population cohort receiving PCI. Methods From the hos- pital electronic medical database, we idemified 3550 patients who received PCI （78.0% males, mean age 60 years） in Chinese PLA General Hospital from January 1, 2000 to August 30, 2016. The multivariate analysis and receiver operating characteristic 01OC） analysis were performed. Results The adverse events of VVRS in the patients were significantly increased after PCI procedure than before the operation （all P 〈 0.001）. The rate of VVRS [95% confidence interval （CI）] in patients receiving PCI was 4.5% （4.1%-5.6%）. Compared to the patients suffering no VVRS, incidence of VVRS involved the following factors, namely female gender, primary PCI, hypertension, over two stems im- plantation in the left anterior descending （LAD）, and the femoral puncture site. The multivariate analysis suggested that they were independ- ent risk factors for predicting the incidence of VVRS （all P 〈 0.001）. We developed a risk prediction score model for VVRS. ROC analysis showed that the risk prediction score model was effectively predictive of the incidence of VVRS in patients receiving PCI （c-statistic 0.76, 95% CI： 0.72-0.79, P 〈 0.001）. There were decreased evems of VVRS in the patients receiving PCI whose diastolic blood pressure dropped by more than 30 mmHg and heart rate reduced by 10 times per minute （AUC： 0.84, 95% CI： 0.81-0.87, P 〈 0.001）. Conclusion The risk prediction score is quite efficient in predicting the incidence of VVRS in patients receiving PCI. In which, the following factors may be in- volved, the femoral puncture site, female gender, hypertension, primary PCI, and over 2 stents implanted in LAD.
基金supported by the National Natural Science Foundation of China(No.51806103)the Natural Science Foundation of Jiangsu Province(No.BK20170800)Aeronautical Science Foundation of China(No.201928052002)。
文摘Particles,including soot,aerosol and ash,usually exist as fractal aggregates.The radiative properties of the particle fractal aggregates have a great influence on studying the light or heat radiative transfer in the particle medium.In the present work,the performance of the single-layer inversion model and the double-layer inversion model in reconstructing the geometric structure of particle fractal aggregates is studied based on the light reflectancetransmittance measurement method.An improved artificial fish-swarm algorithm(IAFSA)is proposed to solve the inverse problem.The result reveals that the accuracy of double-layer inversion model is more satisfactory as it can provide more uncorrelated information than the single-layer inversion model.Moreover,the developed IAFSA show higher accuracy and better robustness than the original artificial fish swarm algorithm(AFSA)for avoiding local optimization problems effectively.As a whole,the present work supplies a useful kind of measurement technology for predicting geometrical morphology of particle fractal aggregates.
