Background Studies have shown that staged percutaneous coronary intervention （PCI） for non-culprit lesions is beneficial for prog- nosis of ST-segment elevation myocardial infarction （STEMI） patients with multives...Background Studies have shown that staged percutaneous coronary intervention （PCI） for non-culprit lesions is beneficial for prog- nosis of ST-segment elevation myocardial infarction （STEMI） patients with multivessel disease. However, the optimal timing of staged re- vascularization is still controversial. This study aimed to find the optimal timing of staged revascularization. Methods A total of 428 STEMI patients with multivessel disease who underwent primary PCI and staged PCI were included. According to the time interval between primary and staged PCI, patients were divided into three groups （〈 1 week, 1- weeks, and 2-12 weeks after primary PCI）. The primary endpoint was major adverse cardiovascular events （MACE）, a composite of all-cause death, non-fatal re-infarction, repeat revascularization, and stroke. Cox regression model was used to assess the association between staged PCI timing and risk of MACE. Results During the follow-up, 119 participants had MACEs. There was statistical difference in MACE incidence among the three groups （〈 1 week： 23.0%; 1-2 weeks： 33.0%; 2-12 weeks： 40.0%; P = 0.001）. In the multivariable adjustment model, the timing interval of staged PCI ≤ 1 week and l-2 weeks were both significantly associated with a lower risk of MACE [hazard ratio （HR）： 0.40, 95% confidence intervals （CI）： 0.24-4）.65; HR： 0.54, 95% CI： 0.3 lq3.93, respectively], mainly attributed to a lower risk of repeat revascularization （HR： 0.41, 95% CI： 0.24-0.70; HR： 0.36, 95% CI： 0.18-0.7）, compared with a strategy of 2-12 weeks later of primary PCI. Conclusions The optimal timing of staged PCI for non-culprit vessels should be within two weeks after primary PCI for STEMI patients.展开更多
Estimating the intensity of outbursts of coal and gas is important as the intensity and frequency of outbursts of coal and gas tend to increase in deep mining. Fully understanding the major factors contributing to coa...Estimating the intensity of outbursts of coal and gas is important as the intensity and frequency of outbursts of coal and gas tend to increase in deep mining. Fully understanding the major factors contributing to coal and gas outbursts is significant in the evaluation of the intensity of the outburst. In this paper, we discuss the correlation between these major factors and the intensity of the outburst using Analysis of Variance(ANOVA) and Contingency Table Analysis(CTA). Regression analysis is used to evaluate the impact of these major factors on the intensity of outbursts based on physical experiments. Based on the evaluation, two simple models in terms of multiple linear and nonlinear regression were constructed for the prediction of the intensity of the outburst. The results show that the gas pressure and initial moisture in the coal mass could be the most significant factors compared to the weakest factor-porosity. The P values from Fisher's exact test in CTA are: moisture(0.019), geostress(0.290), porosity(0.650), and gas pressure(0.031). P values from ANOVA are moisture(0.094), geostress(0.077), porosity(0.420), and gas pressure(0.051). Furthermore, the multiple nonlinear regression model(RMSE: 3.870) is more accurate than the linear regression model(RMSE: 4.091).展开更多
文摘Background Studies have shown that staged percutaneous coronary intervention （PCI） for non-culprit lesions is beneficial for prog- nosis of ST-segment elevation myocardial infarction （STEMI） patients with multivessel disease. However, the optimal timing of staged re- vascularization is still controversial. This study aimed to find the optimal timing of staged revascularization. Methods A total of 428 STEMI patients with multivessel disease who underwent primary PCI and staged PCI were included. According to the time interval between primary and staged PCI, patients were divided into three groups （〈 1 week, 1- weeks, and 2-12 weeks after primary PCI）. The primary endpoint was major adverse cardiovascular events （MACE）, a composite of all-cause death, non-fatal re-infarction, repeat revascularization, and stroke. Cox regression model was used to assess the association between staged PCI timing and risk of MACE. Results During the follow-up, 119 participants had MACEs. There was statistical difference in MACE incidence among the three groups （〈 1 week： 23.0%; 1-2 weeks： 33.0%; 2-12 weeks： 40.0%; P = 0.001）. In the multivariable adjustment model, the timing interval of staged PCI ≤ 1 week and l-2 weeks were both significantly associated with a lower risk of MACE [hazard ratio （HR）： 0.40, 95% confidence intervals （CI）： 0.24-4）.65; HR： 0.54, 95% CI： 0.3 lq3.93, respectively], mainly attributed to a lower risk of repeat revascularization （HR： 0.41, 95% CI： 0.24-0.70; HR： 0.36, 95% CI： 0.18-0.7）, compared with a strategy of 2-12 weeks later of primary PCI. Conclusions The optimal timing of staged PCI for non-culprit vessels should be within two weeks after primary PCI for STEMI patients.
基金provided by the Natural Science Foundation Project(Key)of Chongqing(No.cstc2013jjB0012)the National Natural Science Foundation of China(No.51434003)the National Natural Science Foundation of China(No.51474040)
文摘Estimating the intensity of outbursts of coal and gas is important as the intensity and frequency of outbursts of coal and gas tend to increase in deep mining. Fully understanding the major factors contributing to coal and gas outbursts is significant in the evaluation of the intensity of the outburst. In this paper, we discuss the correlation between these major factors and the intensity of the outburst using Analysis of Variance(ANOVA) and Contingency Table Analysis(CTA). Regression analysis is used to evaluate the impact of these major factors on the intensity of outbursts based on physical experiments. Based on the evaluation, two simple models in terms of multiple linear and nonlinear regression were constructed for the prediction of the intensity of the outburst. The results show that the gas pressure and initial moisture in the coal mass could be the most significant factors compared to the weakest factor-porosity. The P values from Fisher's exact test in CTA are: moisture(0.019), geostress(0.290), porosity(0.650), and gas pressure(0.031). P values from ANOVA are moisture(0.094), geostress(0.077), porosity(0.420), and gas pressure(0.051). Furthermore, the multiple nonlinear regression model(RMSE: 3.870) is more accurate than the linear regression model(RMSE: 4.091).
