The study objective is to investigate whether vitamin D is associated with the cognitive function of geriatric patients. This cross-sectional study involved 357 patients hospitalized in the geriatric ward who complained of memory problems (mean age: 82.3 years). The level of cognitive function was measured with the Mini-Mental State Examination (MMSE) and the clinical diagnosis of dementia was established according to the International Classification of Diseases (ICD-10) criteria. The serum 25-hydroxy vitamin D was measured with liquid chromatography-tandem mass spectrometry. The iterative Bayesian model averaging (BMA) procedure was applied to linear and logistic regression models in order to identify the best set of factors describing cognitive dysfunction and dementia, respectively. According to BMA, there is strong evidence that higher vitamin D levels, higher body mass index (BMI), and higher mobility function measured with the Timed Up and Go (TUG) test are independently associated with better cognitive performance and lower risk of dementia. Additionally, there is strong evidence that fewer years of education and lower vitamin B12 plasma levels independently describe worse cognitive performance. However, vitamin B12 levels higher than 800 pg/mL is negatively associated with the MMSE performance. Hypovitaminosis D in geriatric patients is an underrated marker of cognitive dysfunction and dementia.

Identification of optimal predictors of the 5.5-year survival in former geriatric inpatients.Investigation of the direction and shape of the relationship between mortality risk and its predictors. Retrospective survival analysis with the application of the Cox proportional hazards model. Teaching geriatric unit. 478 inpatients (mean age 77.9; +6.8) discharged from geriatric ward during year 2008, without any exclusion criteria. Comprehensive geriatric assessment of numerous health variables, body mass index (BMI), clinical and biochemical findings, and outcomes of the final diagnosis. Records on the dates of deaths were obtained from the Provincial Office of Population Register. During the 5.5-year follow-up 209 (43.7%) patients died. In the multivariate setup, six risk factors with an independent impact on mortality were identified: age (p=0.036), cognitive functioning on the Blessed test (p=0.005), score on instrumental ADL (p<0.0001), score on Charlson comorbidity index (p<0.0001), cholesterol level (p<0.0001), BMI (p<0.0001), and hemoglobin level (p=0.02). The latter two predictors exhibited a significant inverted J-shaped association with mortality, i.e., considerably higher risk of death corresponds to the lower values of these variables in comparison to their higher levels. Older age, worse IADL and cognitive functioning, and higher comorbidity were recognized as endangering one’s long-term survival. On the other hand, moderate obesity (BMI 36), higher cholesterol and the absence of anemia (hemoglobin 13.6 g/dL) are associated with longer survival. Therefore, irrespective of the individualized treatment and physical exercise, nutrient-dense food seems to be a key recommendation to prevent frailty or malnutrition in the oldest and comorbid population.

Purpose Identification of optimal predictors for different indicators of subjective well-being (SWB) in geriatric inpatients: (1) self-evaluated health status (SEH), (2) feeling of loneliness (FoL), and (3) severity of depression symptoms (SoDS). Investigation of the relationship between response categories of the SWB indicators and their predictors. Methods The data were collected retrospectively from hospital records. All 555 geriatric inpatients underwent a comprehensive geriatric assessment, including the Timed Up and Go (TUG) test. The Bayesian information criterion was applied in ordinal logistic regression models to identify optimal predictors of SEH, FoL, and SoDS among different objective factors. Results After controlling for high-stress situations in the recent past, motor slowness measured with the TUG test, and a level of education were jointly selected as the best predictors of all three SWB indicators. The speed of performing the TUG test improved SEH (OR = 2.08) and decreased both FoL (OR = 0.41) and SoDS (OR = 0.41). A higher level of education improved SEH (OR = 1.05) and alleviated both FoL (OR = 0.96) and SoDS (OR = 0.92). Additionally, a higher level of SEH was positively correlated with a lower BMI, improved instrumental activities of daily living (I-ADL), and higher hemoglobin level. FoL was reinforced by the level of comorbidity, and SoDS was increased by impaired basic ADL. Conclusion Although SWB in geriatric inpatients can be explained by objective comorbidities and disabilities, the good motor function (i.e., a TUG test outcome of less than about 20 s) and a higher level of education were the general predictors that exert an independent beneficial impact on all three SWB indicators.

In this paper we develop a model for the conditional inflated multivariate density of integer count variables with domain ℤⁿ, n ∈ ℕ. Our modelling framework is based on a copula approach and can be used for a broad set of applications where the primary characteristics of the data are: (i) discrete domain; (ii) the tendency to cluster at certain outcome values; and (iii) contemporaneous dependence. These kinds of properties can be found for high‐ or ultra‐high‐frequency data describing the trading process on financial markets. We present a straightforward sampling method for such an inflated multivariate density through the application of an independence Metropolis–Hastings sampling algorithm. We demonstrate the power of our approach by modelling the conditional bivariate density of bid and ask quote changes in a high‐frequency setup. We show how to derive the implied conditional discrete density of the bid–ask spread, taking quote clusterings (at multiples of 5 ticks) into account. Copyright © 2009 John Wiley & Sons, Ltd.

Forecasting market risk lies at the core of modern empirical finance. We propose a new self-exciting probability peaks-over-threshold (SEP-POT) model for forecasting the extreme loss probability and the value at risk. The model draws from the point-process approach to the POT methodology but is built under a discrete-time framework. Thus, time is treated as an integer value and the days of extreme loss could occur upon a sequence of indivisible time units. The SEP-POT model can capture the self-exciting nature of extreme event arrival, and hence, the strong clustering of large drops in financial prices. The triggering effect of recent events on the probability of extreme losses is specified using a discrete weighting function based on the at-zero-truncated Negative Binomial (NegBin) distribution. The serial correlation in the magnitudes of extreme losses is also taken into consideration using the generalized Pareto distribution enriched with the time-varying scale parameter. In this way, recent events affect the size of extreme losses more than distant events. The accuracy of SEP-POT value at risk (VaR) forecasts is backtested on seven stock indexes and three currency pairs and is compared with existing well-recognized methods. The results remain in favor of our model, showing that it constitutes a real alternative for forecasting extreme quantiles of financial returns.

Objectives: The aim of this article was to identify the best predictors of distress suffered by family carers (FCs) of geriatric patients. Methods: A cross-sectional study of 100 FC-geriatric patient dyads was conducted. The negative impact of care (NIoC) subscale of the COPE index was dichotomized to identify lower stress (score of ≤15 on the scale) and higher stress (score of ≥16 on the scale) exerted on FCs by the process of providing care. The set of explanatory variables comprised a wide range of sociodemographic and care-related attributes, including patient-related results from comprehensive geriatric assessments and disease profiles. The best combination of explanatory variables that provided the highest predictive power for distress among FCs in the multiple logistic regression (LR) model was determined according to statistical information criteria. The statistical robustness of the observed relationships and the discriminative power of the model were verified with the cross-validation method. Results: The mean age of FCs was 57.2 (±10.6) years, whereas that of geriatric patients was 81.7 (±6.4) years. Despite the broad initial set of potential explanatory variables, only five predictors were jointly selected for the best statistical model. A higher level of distress was independently predicted by lower self-evaluation of health; worse self-appraisal of coping well as a caregiver; lower sense of general support; more hours of care per week; and the motor retardation of the cared-for person measured with the speed of the Timed Up and Go (TUG) test. Conclusion: Worse performance on the TUG test was only the patient-related predictor of distress among the variables examined as contributors to the higher NIoC. Enhancing the mobility of geriatric patients through suitably tailored kinesitherapeutic methods during their hospital stay may mitigate the burden endured by FCs.