Contribution of cardio-ankle vascular index to prediction of cardiovascular events in the adult urban population: data from the ESSE-RF study (Tomsk)

Aim. To determine the role of cardio-ankle vascular index (CAVI) in predicting cardiovascular events (CVEs) in adult Russian population using model of the Epidemiology of Cardiovascular Diseases and their Risk Factors in Regions of Russian Federation (ESSE-RF) study (Tomsk).Material and methods. We analyzed the data of 1342 people aged 25-64 (4,3±11,6) years, in whom arterial stiffness was assessed as part of the ESSE-RF study using the vascular screening system VaSeraVS-1500, followed by phone contacts, on average, 4,7 years later. We studied the prognostic role of CAVI in relation to primary composite (cardiovascular death, nonfatal myocardial infarction (MI) or stroke) and secondary composite (all CVEs) endpoints.Results. We revealed that prior myocardial infarction or stroke (n=52) is associated with an increase in CVE incidence from 2,3 to 11,5% (p=0,0003) and from 5% to 23% (p<0,001) for primary and secondary composite endpoints, respectively. In a group of 1290 people (without prior MI or stroke), CAVI was significantly higher in men than in women: 7,4±1,4 vs 7,1±1,3 (p=0,002), despite more young age: 45,4±11,8 vs 48,0±11,3 years (p<0,001). The risk criterion for CVE was CAVI >7,8 (relative risk (RR): 5,06; 95% confidence interval (CI): 2,32-11,06) (p<0,001) and (RR: 3,95; 95% CI: 2,37-6,58) (p<0,001), which retains its predictive value when adjusted for conventional risk factors (RR: 3,13; 95% CI: 1,26-7,75) (p=0,014) and (RR: 2,16; 95% CI: 1,18-3,98) (p=0,013) — primary and secondary composite endpoints, respectively.Conclusion. CAVI has a significant independent value in predicting CVEs in Tomsk adult urban population aged 25-64 years. To clarify the cardiovascular risk, vascular screening with identifying CAVI should be carried out during preventive and screening examinations for men over 35 and women over 45.

Risk assessment and its influencing factors of involuntary admission in patients with mental disorders in Shanghai, China

Background: The ‘risk criterion’ for involuntary admission (IA) has been adopted by Mental Health Law of the People’s Republic of China since 2013. How the new legal regulation influences daily practices in psychiatric institutes are still unclear. Aims: The present study sought to explore the application of risk criterion in IA cases; especially risk assessed by psychiatrists at admission and its influencing factors. Method: Socio-demographic and clinical data including risk assessment for admission of 3,529 involuntary admitted patients from two typical hospitals in Shanghai from 2013 to 2014 were consecutively collected. Personal information of psychiatrists who made admission assessment was collected separately. Results: Among the 3,529 cases, 1,890 (53.6%) were admitted because of actual harmful behaviors to self or others, while 1,639 (46.4%) were admitted with some kinds of risk, but 265 (7.5%) were admitted without any records on risk assessment checklists. Patients who were unemployed, of younger age, single status, diagnosed with schizophrenia were more likely to be admitted without any records on the checklist. Male gender, older age, and lower professional title are influencing factors that psychiatrists made no risk assessment records. Conclusions: The vast majority (92.5%) of risk assessment in IA patients were qualified in our study. In order to protect the legal rights of patients better, operational and reasonable procedures of risk assessment should be developed, such include more detailed rules to IA, systematic training of psychiatrists on IA assessment, mechanism improving doctor-patient relationship, and alternative mental health services for patients and so on.

USING METHODS FOR ASSESSING ECONOMIC RISKS TO MAKE INVESTMENT DECISIONS

The article uses methods of quantitative evaluation of economic risks that allow in conditions of uncertainty to provide an industrial enterprise with information on a less risky investment project for the adoption of a managerial decision. Several methods for assessing the risk of investing are used: the size of the dispersion, the value of the coefficient variation, the size of the semivariation, the size of the coefficient of semivariation, the value of the coefficient of asymmetry. Dispersion is a statistical term that describes the value range values expected for a particular variable. Dispersion is used in studying the variability of profits from a specific trading strategy or investment portfolio. This is often interpreted as a degree of uncertainty and, therefore, the risk associated with a certain portfolio of securities or investments. Semiivariation is an indicator of data that can be used to assess potential investment risks. Semivarianity is calculated by measuring the dispersion of all observations that fall below the middle or target data set. Neoclassical theory goes out for understanding that risks are just unfavorable scenarios for an investor company. Therefore, it is necessary to take into account the unfavorable deviations. When the management subject is loyal to risk, then it is necessary to use the coefficient of semivariation, which can also be determined which of the projects. If the company wants to successfully investigate the project, it is important to identify situations where the probability and magnitude of a positive (or negative) result is much larger than the opposite result. Understanding asymmetric risk is crucial for making correct decisions. The ability to identify asymmetric risk helps to avoid potentially dangerous situations where there are not enough errors. It also allows you to use the opportunities for investments where there are several ways to win. The criterion of maximum asymmetry is the minimum risk criterion. The results of the quantitative assessment of economic risks enable to substantiate the economic efficiency of investment projects.

PORTFOLIO MODEL UNDER FRACTAL MARKET BASED ON MEAN-DCCA

Under the realistic background that the capital market nowadays is a fractal market, this paper embeds the detrended cross-correlation analysis (DCCA) into the return-risk criterion to construct a Mean-DCCA portfolio model, and gives an analytical solution. Based on this, the validity of Mean-DCCA portfolio model is verified by empirical analysis. Compared to the mean-variance portfolio model, the Mean-DCCA portfolio model is more conducive for investors to build a sophisticated investment portfolio under multi-time-scale, improve the performance of portfolios, and overcome the defect that the mean-variance portfolio model has not considered the existence of fractal correlation characteristics between assets.

Estimation of Short Circuit Duration for the Assessment of Dynamic Effects in Distribution Substations with Flexible Conductors

The paper focuses on finding short circuit duration for computing the dynamic effects in Extra High Voltage (EHV) distribution substations with flexible conductors with the use of probabilistic method. To find fault duration for selected substation points, a risk criterion was involved, namely the expected annual frequency of exceeding the calculated values of dynamic forces. A dedicated simulation model based on the Monte Carlo method was used to analyze the dynamic effects of short circuit current flow in the substation during faults within it and in its vicinity. The short circuit duration model is the key part of the simulation model. Due to the discussion of how the selected factors affect the estimated short circuit duration, indications helpful to find the values of the latter were formulated and some examples for the 220 kV distribution substation were given.