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Objective:Rapid assessment of the outcome after percutaneous coronary intervention (PCI) in patients with acute coronary syndrome (ACS) is an important clinical issue. In this study, an electrocardiogram (ECG) analysis method based on dynamic learning was proposed.Methods:A total of 203 patients with ACS after successful PCI were enrolled for prospective analysis at the Emergency Department of Qilu Hospital of Shandong University from April 2019 to December 2020. All patients were divided into group without ≥70% postoperative stenosis ( n=72) and group with ≥ 70% postoperative stenosis ( n=131) according to the presence of 70% or more stenosis after PCI. The clinical data of ACS patients were collected and analyzed by χ2 test, t-test, or Mann-Whitney test. ECGs were recorded before and 2 h after PCI, and were dynamically analyzed to generate cardiodynamicsgram (CDG) using dynamic learning. In the group without ≥ 70% postoperative stenosis, the model and CDG index for evaluating myocardial ischemia were obtained by training support vector machine (SVM) using 10 times 10-fold cross-validation. Results:There was no significant difference in clinical data between the two groups. The prediction accuracy and sensitivity of the support vector machine model for myocardial ischemia in group without≥70% postoperative stenosis were 73.61%, and 84.72% respectively. CDG transformed from disorderly to regular after PCI, and CDG index decreased significantly ( P<0.001): 90.28% (65) patients in group without≥70% postoperative stenosis, and 79.39% (104) patients in group with≥70% postoperative stenosis had lower CDG indexes than before PCI. Conclusions:In this study, CDG obtained by dynamic learning can intuitively and effectively evaluate the changes of myocardial ischemia before and after PCI, which is helpful to assist clinicians to formulate the next treatment plan.
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【Objective】 To explore the promote and deter factors of blood donation among street blood donors in Nanjing, in order to improve the accuracy of street blood donors recruitment. 【Methods】 A questionnaire with high confidence was designed based on the theory of planned behavior(TPB). The multi-stage hierarchical sampling method was adopted according to the geographical location and economic development level of 11 districts(regions) in Nanjing, and the street blood donors were divided into three groups according to the history of blood donation: one donation(n=361), donation numbers ≥ 2(n=417)and non-donation (n=241). The blood donation behavior was investigated from four aspects as external promote factors (such as seeking a free blood examination, self-interest factors, etc.), internal promote factors(such as altruistic, self-interest factors, blood donation can help others, etc.), external deter factors (too busy to donate blood, opposition from my family, etc.) and internal deter actors ( worry about dizziness after blood donation, fear of needles, ect.). The database was established using Epidata software, and chi-square test was applied for statistical analysis between groups. 【Results】 The groups mainly affected by the promote factors (altruistic and self-interest factors) of Nanjing street population in blood donation were unmarried, 18~24 years old, childless, below bachelor degree, and have barely no income. The main groups less affected by the deter factors were students, male, unmarried, 18~24 years old, childless and have barely no income.Promote factors increases with the number of blood donations, while deter factors decreases with the number of blood donation. 【Conclusion】 TBP can better analyze and explain the promote and deter factors affecting blood donation behavior among street blood donors in Nanjing, which is helpful for blood stations to formulate targeted measures to improve the availability of street blood donors.
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【Objective】 To analyze the influencing factors of blood re-donation among street voluntary blood donors in Nanjing, and to provide basis for increasing the proportion of blood donation/donors. 【Methods】 29 650 street voluntary blood donors in Nanjing from May 21, 2017 to May 21, 2018 in the information management system of Nanjing Red Cross Blood Center were taken as the sampling population, and 2 965 (10%) were randomly selected to ask whether they donated again and reasons by telephone calls. They were divided into re-donation group and lapsed group.The demographic variables and donation frequency of street blood donors in the two groups were analyzed and compared by Chi-square test, and multivariate logistic regression was used to analyze the influencing factors of re-donation of blood donors. 【Results】 The response rate of this survey was 63.37% (1 879/2 965), and the re-donation rate of street blood donors in Nanjing from May 2017 to May 2018 was 40.34% (758/1 879), which was lower than the re-donation rate of global blood donors as 50%. The primary motivation for street blood donors in Nanjing to donate blood again was "help others", accounted for 62.27% (472/758), and the primary deterrent to redonate blood again was "too busy to donate blood", accounted for 49.15% (551/1 121). 【Conclusion】 There is a certain gap between the rate of blood re-donation in Nanjing and worldwide, therefore, further incentive measures are needed and flexible recruitment and blood donation methods should be adopted to facilitate blood donation for donors.
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<p><b>OBJECTIVE</b>To analyze the present situation and influencing factors of discrimination against hepatitis B patients and carriers among rural adults in three eastern provinces in China.</p><p><b>METHODS</b>By using the method of probability proportionate to size (PPS), we involved a sample of 9 269 rural adults aged above 18 years old from 22 villages of 7 counties in Beijing, Hebei, Shandong in 2011 and 2012. We used a self-designed interview questionnaire with questions about the individual and household characteristics, attitudes toward hepatitis B patients and carriers, individual HBV vaccination history, etc. We analyzed the hepatitis B discrimination score and its distribution, and we also created a multinomial logistic regression model to analyze the influencing factors of discrimination.</p><p><b>RESULTS</b>Of all the participants, 51.15% (4 741) were afraid of being infected with HBV when getting on with hepatitis B patients or carriers; 51.29% (4 754), 61.14% (5 667) and 52.22% (4 841) of them were not willing to accept gifts from hepatitis B patients or carriers, have dinner with them, or hug and shake hands with them, respectively; 73.92% (6 852) were unwilling to their children's playing with kids whose parents were hepatitis B patients or carriers, and 86.68% (8 034) were unwilling to their children's marrying hepatitis B patients or carriers. Of all the participants, only 0.88% (82) were totally discrimination-free (discrimination score = 0); mild or without discrimination (< 0 discrimination score ≤ 5) accounted for 23.70% (2 197/9 269); severe discrimination (discrimination score ≥ 6) accounted for 76.30% (7 072). The multiple multinomial logistic regression showed that migratory workers, other occupations like technician, civil servants and village doctors were less likely to show severe HBV-related discrimination compared with farmers, with OR (95% CI) 0.86 (0.75-0.98), 0.77 (0.67-0.87), 0.57 (0.41-0.79), respectively. Compared with the lowest income group (< 10 000 RMB/year per person), and the highest income group (> 40 000 RMB/year per person) had an OR (95% CI) of 0.57 (0.46-0.70). People with higher education tended to show less severe discrimination. The high education group had an OR (95% CI) of 0.64 (0.51-0.80) based on the low education group. And compared with people whose self-assessment of health status was very good, those who assessed their health status as very poor showed less severe discrimination, with an OR (95% CI) of 0.41 (0.25-0.67).</p><p><b>CONCLUSION</b>The situation of discrimination against hepatitis B patients and carriers among rural adults in three eastern provinces was serious. It is of great urgency to eliminate the discrimination. Work on eliminating hepatitis B discrimination should focus on farmers, people with low incomes, and people with low educational level.</p>