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Background Early identification of the occurrence of arrhythmia in patients with acute myocardial infarction plays an essential role in clinical decision-making. The present study attempted to use machine learning (ML) methods to build predictive models of arrhythmia after acute myocardial infarction (AMI). Methods A total of 2084 patients with acute myocardial infarction were enrolled in this study. (All data is available on Github: https://github.com/wangsuhuai/AMI-database1.git). The primary outcome is whether tachyarrhythmia occurred during admission containing atrial arrhythmia, ventricular arrhythmia, and supraventricular tachycardia. All data is randomly divided into a training set (80%) and an internal testing set (20%). Apply three machine learning algorithms: decision tree, random forest (RF), and artificial neural network (ANN) to learn the training set to build a model, then use the testing set to evaluate the prediction performance, and compare it with the model built by the Global Registry of Acute Coronary Events (GRACE) risk variable set. Results Three ML models predict the occurrence of tachyarrhythmias after AMI. After variable selection, the artificial neural network (ANN) model has reached the highest accuracy rate, which is better than the model constructed using the Grace variable set. After applying SHapley Additive exPlanations (SHAP) to make the model interpretable, the most important features are abnormal wall motion, lesion location, bundle branch block, age, and heart rate. Among them, RBBB (odds ratio [OR]: 4.21; 95% confidence interval [CI]: 2.42–7.02), ≥ 2 ventricular walls motion abnormal (OR: 3.26; 95% CI: 2.01–4.36) and right coronary artery occlusion (OR: 3.00; 95% CI: 1.98–4.56) are significant factors related to arrhythmia after AMI. Conclusions We used advanced machine learning methods to build prediction models for tachyarrhythmia after AMI for the first time (especially the ANN model that has the best performance). The current study can supplement the current AMI risk score, provide a reliable evaluation method for the clinic, and broaden the new horizons of ML and clinical research. Trial registration Clinical Trial Registry No.: ChiCTR2100041960.

Background: The clinical use of angiotensin-converting enzyme inhibitors (ACEI) and angiotensin-receptor blockers (ARB) in patients with COVID-19 infection remains controversial. Therefore, we performed a meta-analysis on the effects of ACEI/ARB on disease symptoms and laboratory tests in hypertensive patients infected with COVID-19 virus and those who did not use ACEI/ARB. Methods: We systematically searched the relevant literatures from Pubmed, Embase, EuropePMC, CNKI, and other databases during the study period of 31 December 2019 (solstice, 15 March 2020), and analyzed the differences in symptoms and laboratory tests between patients with COVID-19 and hypertension who used ACEI/ARB drugs and those who did not. All statistical analyses were performed with REVMAN5.3. Results: We included a total of 1808 patients with hypertension diagnosed with COVID-19 in six studies. Analysis results show that ACEI/ARB drugs group D-dimer is lower (SMD = −0.22, 95%CI: −0.36 to −0.06), and the chances of getting fever is lower (OR = 0.74, 95%CI: 0.55 to 0.98). Meanwhile, laboratory data and symptoms were not statistical difference, but creatinine tends to rise (SMD = 0.22, 95% CI: 0.04 to 0.41). Conclusion: We found that the administration of ACEI/ARB drugs had positive effect on reducing D-dimer and the number of people with fever. Meanwhile it had no significant effect on other laboratory tests (creatinine excepted) or symptoms in patients with COVID-19, while special attention was still needed in patients with renal insufficiency.

Objectives Cardiac injury is associated with poor prognosis of 2019 novel coronavirus disease 2019 (COVID-19), but the risk factors for cardiac injury have not been fully studied. In this study, we carried out a systematic analysis of clinical characteristics in COVID-19 patients to determine potential risk factors for cardiac injury complicated COVID-19 virus infection. Methods We systematically searched relevant literature published in Pubmed, Embase, Europe PMC, CNKI and other databases. All statistical analyses were performed using STATA 16.0. Results We analysed 5726 confirmed cases from 17 studies. The results indicated that compared with non-cardiac-injured patients, patients with cardiac injury are older, with a greater proportion of male patients, with higher possibilities of existing comorbidities, with higher risks of clinical complications, need for mechanical ventilation, ICU transfer and mortality. Moreover, C-reactive protein, procalcitonin, D-dimer, NT-proBNP and blood creatinine in patients with cardiac injury are also higher while lymphocyte counts and platelet counts decreased. However, we fortuitously found that patients with cardiac injury did not present higher clinical specificity for chest distress (P = 0.304), chest pain (P = 0.334), palpitations (P = 0.793) and smoking (P = 0.234). Similarly, the risk of concomitant arrhythmia (P = 0.103) did not increase observably either. Conclusion Age, male gender and comorbidities are risk factors for cardiac injury complicated COVID-19 infection. Such patients are susceptible to complications and usually have abnormal results of laboratory tests, leading to poor outcomes. Contrary to common cardiac diseases, cardiac injury complicated COVID-19 infection did not significantly induce chest distress, chest pain, palpitations or arrhythmias. Our study indicates that early prevention should be applied to COVID-19 patients with cardiac injury to reduce adverse outcomes.

Supplemental material, sj-pdf-1-jra-10.1177_1470320320981321 for Effects of ACEI and ARB on COVID-19 patients: A meta-analysis by Yang Xue, Shaoqing Sun, Jianing Cai, Linwen Zeng, Shihui Wang, Suhuai Wang, Jingjie Li, Lin Sun and Jianmin Huo in Journal of the Renin-Angiotensin-Aldosterone System

Aqueous biphasic systems (ABS) based on the surfactant (triton x-100, Tr) and cholinium ionic liquids were developed for the extraction of three herbicides (simetryn, prometryn, and atrazine). The influence of the phase compositions and temperature on the formation of the ABS was investigated. The biphasic region of the ABS decreased with the longer carbon chain of the anions in ILs, while increased with the higher temperature. The partitioning behaviour of the selected herbicides using the (Tr + choline acetate [Ch][Ac] + water) ABS was studied, and the analytes mainly concentrated the surfactant-rich phase. The partition coefficients of the herbicides decreased with increasing mass fractions of Tr, while increased with the higher concentrations of [Ch][Ac], which means that salting-out ability of the IL played the important role on the system formation. The developed ABS is a promising method considering its simple operation, mild condition and biocompatibility without using any organic solvent during the extraction process.

A space harmonic leaky-wave antenna based on half mode substrate integrated waveguide (HMSIW) is proposed. This antenna operates in the first negative Floquet mode which is a space harmonic wave using transverse slots. Continuous backward beam scanning is acquired within scanning region from −55° to −10° operating in 16 − 20 GHz. This antenna miniaturizes the transverse size using HMSIW. The simulated gain of the antenna uniformly changed from 9.4dB to 15.9dB.

This paper displays a feed network, by changing the value of current amplitude, phase can make different radiation pattern in antenna array system. By means of those principles, the Wilkinson power divider can provide the power of equal phase to apply to the antenna array. The Wilkinson Power Divider has changed the original three ports into five ports which four output ports can be termed as the output ports which can work at frequency from 2 GHz to 11 GHz which can be regarded as the broadband with the value of return loss under the - 10dB. Theoretically, the maximum value insertion loss should be amounted to -6 dB because of the power divider working by dividing power into $1:4$ ratio. Due to the loss of the material, the result of simulation is about -7.3 dB that is smaller than -6dB. Otherwise, the isolation which value is under the -25 dB behaves well at a frequency of 6–11 GHz.

In this paper, a leaky wave antenna based on Composite Right/Left-handed Structure(CRLH) is proposed. The equivalent series capacitance in the CRLH is realized by the ring slot on the microstrip and the metal vias realizes the equivalent shunt inductance. The special structure of CRLH makes the propagation constant in the region of lower frequency negative, showing the left-handed characteristics, and the phase velocity and the group velocity have the opposite direction. In the higher frequency region, the phase velocity and group velocity have the same direction, showing the right-handed characteristics. The structure achieves a frequency scanning angle of −60 degrees to 30 degrees and it achieves high gain in the working band of the antenna.

Abstuact: By means of the multivariate statistical analysis , we research the level of psychological health of undergraduates in the North China Institute of Science and Technology(Abbr. NCIST).Firstly, the status of the college students’ psychological health are compared with that of the norm of domestic students and normal adults, then the differences of the psychological health are explored from the aspects of gender, grade, discipline and so on. The result shows that the status of the college students’ psychological health is better than the status of domestic students,similaring to normal adults. Male and female college students are not significantly different in the level of psychological health, but the second and third grade students are in the relatively poor mental health, and liberal students are significantly worse than that of science students.For the existence of psychological problems, the recommendations are given, which can provide the necessary theoretical basis for exploring college students , mental health education model. Keyword: college Students, psychological health, SCL-90, factor