scholarly journals Stochastic modeling of mortality rates and Mortality-at-Risk forecast by taking conditional heteroscedasticity effect into account

Heliyon ◽  
2021 ◽  
Vol 7 (10) ◽  
pp. e08083
Author(s):  
Khreshna Syuhada ◽  
Arief Hakim
Keyword(s):  
At Risk ◽  
Stochastic Modeling ◽  
Mortality Rates ◽  
Conditional Heteroscedasticity ◽  
Risk Forecast

scholarly journals Biomarkers and clinical scores to identify patient populations at risk of delayed antibiotic administration or intensive care admission

Critical Care ◽  
2019 ◽  
Vol 23 (1) ◽  
Author(s):  
Juan Gonzalez del Castillo ◽  
◽  
Darius Cameron Wilson ◽  
Carlota Clemente-Callejo ◽  
Francisco Román ◽  
...  
Keyword(s):  
At Risk ◽  
Intensive Care ◽  
Disease Progression ◽  
Hospital Readmission ◽  
Mortality Rates ◽  
Antibiotic Administration ◽  
News Values ◽  
Icu Admission ◽  
Clinical Scores ◽  
Populations At Risk

Abstract Background The performance of blood biomarkers (mid-regional proadrenomedullin (MR-proADM), procalcitonin (PCT), C-reactive protein (CRP), and lactate) and clinical scores (Sequential Organ Failure Assessment (SOFA), National Early Warning Score (NEWS), and quick SOFA) was compared to identify patient populations at risk of delayed treatment initiation and disease progression after presenting to the emergency department (ED) with a suspected infection. Methods A prospective observational study across three EDs. Biomarker and clinical score values were calculated upon presentation and 72 h, and logistic and Cox regression used to assess the strength of association. Primary outcomes comprised of 28-day mortality prediction and delayed antibiotic administration or intensive care (ICU) admission, whilst secondary outcomes identified subsequent disease progression. Results Six hundred eighty-four patients were enrolled with hospitalisation, ICU admission, and infection-related 28-day mortality rates of 72.8%, 3.4%, and 4.4%, respectively. MR-proADM and NEWS had the strongest association with hospitalisation and the requirement for antibiotic administration, whereas MR-proADM alone had the strongest association with ICU admission (OR [95% CI]: 5.8 [3.1 - 10.8]) and mortality (HR [95% CI]: 3.8 [2.2 - 6.5]). Patient subgroups with high MR-proADM concentrations (≥ 1.77 nmol/L) and low NEWS (< 5 points) values had significantly higher rates of ICU admission (8.1% vs 1.6%; p < 0.001), hospital readmission (18.9% vs. 5.9%; p < 0.001), infection-related mortality (13.5% vs. 0.2%; p < 0.001), and disease progression (29.7% vs. 4.9%; p < 0.001) than corresponding patients with low MR-proADM concentrations. ICU admission was delayed by 1.5 [0.25 – 5.0] days in patients with high MR-proADM and low NEWS values compared to corresponding patients with high NEWS values, despite similar 28-day mortality rates (13.5% vs. 16.5%). Antibiotics were withheld in 17.4% of patients with high MR-proADM and low NEWS values, with higher subsequent rates of ICU admission (27.3% vs. 4.8%) and infection-related hospital readmission (54.5% vs. 14.3%) compared to those administered antibiotics during ED treatment. Conclusions Patients with low severity signs of infection but high MR-proADM concentrations had an increased likelihood of subsequent disease progression, delayed antibiotic administration or ICU admission. Appropriate triage decisions and the rapid use of antibiotics in patients with high MR-proADM concentrations may constitute initial steps in escalating or intensifying early treatment strategies.

scholarly journals Improving a method for determining the maneuvering intensity of the executive element of a special-purpose system

2021 ◽  
Vol 5 (3 (113)) ◽  
pp. 75-83
Author(s):  
Spartak Hohoniants ◽  
Iurii Repilo ◽  
Oleksandr Tytarenko ◽  
Andrii Kokoiko ◽  
Oleg Golovchenko
Keyword(s):  
At Risk ◽  
Initial Data ◽  
Stochastic Modeling ◽  
Mutual Influence ◽  
Improved Method ◽  
Executive Element ◽  
Favorable Conditions ◽  
The Impact ◽  
Executive Elements ◽  
Significant Factors

The purpose of improving a method is to devise a tool for resolving contradictions in the practice of conflict events related to increasing the survivability and effectiveness of participation in a conflict event. A method for forecasting the survivability indicators of a special-purpose system based on the method of analytical-stochastic modeling of a conflict event was chosen as the basis for improvement. The improved method is intended to find a compromise between the need to increase the duration of participation in the conflict and minimize the time of being at risk of loss of ability to function. The use of the improved method, unlike the existing ones, provides an assessment of the impact of maneuver on the effectiveness of the implementation of tasks and the survivability of SPS. The method implies justifying the techniques for the executive elements to maneuver in order to create favorable conditions and effectively perform tasks in a conflict event. The method involves the procedure for the formation of initial data; determining the maneuvering intensity of executive elements; comparing the parameters for expedient (rational) and implemented maneuvering techniques; the generalization of the research results. The accepted indicators of the effectiveness and survivability of a special-purpose system in a conflict event are the mathematical expectations of the number of destructive influences and the number of preserved executive elements as a function of the intensity of maneuvering. The criteria defined for assessing the maneuvering techniques are the greatest values of the increase in efficiency and survivability with the change in the intensity of maneuvering and taking the favorable position by an executive element in a conflict event. The specified method has helped investigate the peculiarities of changing performance and survivability indicators dependent on the intensity of maneuvering and determine the criteria signs for selecting maneuvering techniques. Based on the signs of informativeness and the nature of the mutual influence of the relevant indicators, the advantage of the method is 30 % while the objectivity of taking into consideration significant factors increases by 15 %. Practice needs to predict the consequences of processes of conflicting nature on the grounds of the effectiveness and survivability of its participants

scholarly journals ESTIMASI VALUE AT RISK PORTOFOLIO SAHAM MENGGUNAKAN METODE GARCH-COPULA (Studi Kasus : Harga Penutupan Saham Harian Unilever Indonesia dan Kimia Farma Periode 1 Januari 2013- 31 Desember 2016)

2018 ◽  
Vol 7 (4) ◽  
pp. 397-407
Author(s):  
Lingga Bayu Prasetya ◽  
Dwi Ispriyanti ◽  
Alan Prahutama
Keyword(s):  
At Risk ◽  
Value At Risk ◽  
Tail Dependence ◽  
Conditional Heteroscedasticity ◽  
Mutual Correlation ◽  
Copula Method ◽  
Stock Portfolio ◽  
Autoregressive Conditional Heteroscedasticity ◽  
Return Value ◽  
Return Data

Any investment in the stock market will earn returns accompanied by risks. Return and risk has a mutual correlation that equilibrium. The formation of a portfolio is intended to provide a lower risk or with the same risk but provide a higher return. Value at Risk (VaR) is a instrument to analyze risk management. Time series model used in stock return data that it has not normal distribution and heteroscedastisicity is Generalized Autoregressive Conditional Heteroscedasticity (GARCH). GARCH-Copula is a combined method of GARCH and Copula. The Copula method is used in joint distribution modeling because it does not require the assumption of normality of the data and can capture tail dependence between each variable. This research uses return data from stock closing prices of Unilever Indonesia and Kimia Farma period January 1, 2013 until December 31, 2016. Copula model is selected based on the highest likelihood log value is Copula Clayton. Value at Risk estimates of Unilever Indonesia and Kimia Farma's stock portfolio on the same weight were performed using Monte Carlo simulation with backtesting of 30 days period data at 95% confidence level. Keywords : Stock, Risk, Generalized Autoregressive Conditional Heteroscedasticity (GARCH), Copula, Value at Risk

scholarly journals A Population-Based Analysis of Pneumococcal Disease Mortality in California, 1989–1998

2005 ◽  
Vol 120 (2) ◽  
pp. 157-164 ◽  
Author(s):  
Matthew D. Redelings ◽  
Frank Sorvillo ◽  
Paul Simon
Keyword(s):  
At Risk ◽  
Pneumococcal Disease ◽  
Risk Groups ◽  
Mortality Rates ◽  
Population Based ◽  
California Department ◽  
Demographic Groups ◽  
Risk Of Death ◽  
Disease Mortality ◽  
Preventable Mortality

Objectives. Pneumococcal disease is an important cause of vaccine-preventable mortality. It is important to understand the burden and distribution of mortality so that prevention efforts can be targeted appropriately. This study evaluated pneumococcal disease mortality and its demographic correlates in California from 1989 to 1998. Methods. Deaths due to pneumococcal disease were identified from statewide vital records data using multiple cause-coded information. Denominator data were obtained from estimates from the California Department of Finance. Crude and age-adjusted mortality rates and 95% confidence intervals were calculated for each age, gender, and racial/ethnic group. Results. The age-adjusted pneumococcal disease mortality rate was 2.05 deaths per 100,000 population. Mortality was highest in elderly individuals (reaching 38.29 deaths per 100,000 population in individuals older than age 85). Age-adjusted mortality rates were elevated in the African American race/ethnicity group (2.96 deaths per 100,000 population) and males (2.67 deaths per 100,000 population). The majority of individuals who died of pneumococcal disease (78.9%) fell into at-risk groups indicated for vaccination. The majority of all pneumococcal deaths were caused by pneumococcal pneumonia. Mortality was seasonal, reaching a peak in the winter months. A decreasing trend in mortality was observed over the 10-year period examined. Conclusions. Pneumococcal disease remains a significant cause of vaccine-preventable mortality in the California population. Greater efforts must be made to vaccinate at-risk individuals, especially those in demographic groups at highest risk of death.

Follow-up of Infectious Lymphocytosis Cases

PEDIATRICS ◽  
1968 ◽  
Vol 42 (4) ◽  
pp. 712-713
Author(s):  
Arthur Oleinick ◽  
Andrew G. Glass
Keyword(s):  
At Risk ◽  
Sample Size ◽  
Recent Article ◽  
Mortality Rates ◽  
Expected Number ◽  
Risk Of Malignancy ◽  
The Individual

We were interested in the editorial of Clement1 which accompanied the recent article of Putnam, Moore, and Mitchell2 concerning the 19-year follow-up of patients in an epidemic of infectious lymphocytosis in 1947. Although no instance of leukemia or lymphoma was detected, the size of the study sample seemed to us too small to assess properly the risk of malignancy in these patients. To evaluate the adequacy of the sample size, we computed the expected number of cases of leukemia and lymphoma using the person years at risk of the individual cases and the 1964 U.S. mortality rates for leukemia and lymphoma.

scholarly journals Space-Time Analysis to Identify Areas at Risk of Mortality from Cardiovascular Disease

2015 ◽  
Vol 2015 ◽  
pp. 1-9 ◽  
Author(s):  
Poliany C. O. Rodrigues ◽  
Emerson S. Santos ◽  
Eliane Ignotti ◽  
Sandra S. Hacon
Keyword(s):  
Cardiovascular Disease ◽  
At Risk ◽  
High Risk ◽  
Empirical Bayes ◽  
Mortality Rates ◽  
Space Time ◽  
Low Risk ◽  
Atmospheric Particulate Matter ◽  
Eastern Region ◽  
Risk Of Mortality

This study aimed at identifying areas that were at risk of mortality due to cardiovascular disease in residents aged 45 years or older of the cities of Cuiabá and Várzea Grande between 2009 and 2011. We conducted an ecological study of mortality rates related to cardiovascular disease. Mortality rates were calculated for each census tract by the Local Empirical Bayes estimator. High- and low-risk clusters were identified by retrospective space-time scans for each year using the Poisson probability model. We defined the year and month as the temporal analysis unit and the census tracts as the spatial analysis units adjusted by age and sex. The Mann-WhitneyUtest was used to compare the socioeconomic and environmental variables by risk classification. High-risk clusters showed higher income ratios than low-risk clusters, as did temperature range and atmospheric particulate matter. Low-risk clusters showed higher humidity than high-risk clusters. The Eastern region of Várzea Grande and the central region of Cuiabá were identified as areas at risk of mortality due to cardiovascular disease in individuals aged 45 years or older. High mortality risk was associated with socioeconomic and environmental factors. More high-risk clusters were observed at the end of the dry season.

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