Development of a risk model for adverse drug events in the elderly

The aim of this study was to develop a predictive model for adverse drug events (ADEs) in elderly patients. Socio-demographic and medical data were collected from chart reviews, computerised information and a patient interview, for a population of 929 elderly patients (aged greater than or equal to 65 years) whose admission to the Waveney/B raid Valley Hospital in Northern Ireland was not scheduled. A further 204 patients formed a validation group. An ADE score was assigned to each patient using a modified Naranjo algorithm scoring system. The ADE scores ranged from 0 to 8. For the purposes of developing a risk model, scores of 4 or more were considered to constitute a high risk of an ADE.

External validation of the OHTS-EGPS model for predicting the 5-year risk of open-angle glaucoma in ocular hypertensives

To independently evaluate and compare the performance of the Ocular Hypertension Treatment Study-European Glaucoma Prevention Study (OHTS-EGPS) prediction equation for estimating the 5-year risk of open-angle glaucoma (OAG) in four cohorts of adults with ocular hypertension.

Incorporating Severity and Risk as Factors to the Fardal Cost-Effectiveness Model to Create a Cost-Benefit Model for Periodontal Treatment

Background: A previously described economic model was based on average values for patients diagnosed with chronic periodontitis (CP). However, tooth loss varies among treated patients and factors for tooth loss include CP severity and risk. The model was refined to incorporate CP severity and risk to determine the cost of treating a specific level of CP severity and risk that is associated with the benefit of tooth preservation.

Methods: A population that received and another that did not receive periodontal treatment were used to determine treatment costs and tooth loss. The number of teeth preserved was the difference of the number of teeth lost between the two populations. The cost of periodontal treatment was divided by the number of teeth preserved for combinations of CP severity and risk.

Results: The cost of periodontal treatment divided by the number of teeth preserved ranged from (US) $ 1,405 to $ 4,895 for high or moderate risk combined with any severity of CP and was more than $ 8,639 for low risk combined with mild CP. The cost of a three-unit bridge was $ 3,416, and the cost of a single-tooth replacement was $ 4,787.

Conclusion: Periodontal treatment could be justified on the sole basis of tooth preservation when CP risk is moderate or high regardless of disease severity.

HDAC1 and HDAC2 independently predict mortality in hepatocellular carcinoma by a competing risk regression model in a Southeast Asian population

Histone deacetylases (HDACs) are enzymes involved in transcriptional repression. We aimed to examine the significance of HDAC1 and HDAC2 gene expression in the prediction of recurrence and survival in 156 patients with hepatocellular carcinoma (HCC) among a South East Asian population who underwent curative surgical resection in Singapore. We found that HDAC1 and HDAC2 were upregulated in the majority of HCC tissues. The presence of HDAC1 in tumor tissues was correlated with poor tumor differentiation. Notably, HDAC1 expression in adjacent non-tumor hepatic tissues was correlated with the presence of satellite nodules and multiple lesions, suggesting that HDAC1 upregulation within the field of HCC may contribute to tumor spread. Using competing risk regression analysis, we found that increased cancer-specific mortality was significantly associated with HDAC2 expression. Mortality was also increased with high HDAC1 expression. In the liver cancer cell lines, HEP3B, HEPG2, PLC5, and a colorectal cancer cell line, HCT116, the combined knockdown of HDAC1 and HDAC2 increased cell death and reduced cell proliferation as well as colony formation. In contrast, knockdown of either HDAC1 or HDAC2 alone had minimal effects on cell death and proliferation. Taken together, our study suggests that both HDAC1 and HDAC2 exert pro-survival effects in HCC cells, and the combination of isoform-specific HDAC inhibitors against both HDACs may be effective in targeting HCC to reduce mortality.

Comparison of excess radiological risk of building materials and industrial by-products according to I-index (EU-BSS) and revised room model (IAEA SSG-32)

To get a better insight into the radiological features of industrial by-products that can be reused in building materials a review of the reported scientific data can be very useful. The current study is based on the continuously growing database of the By-BM (H2020-MSCA-IF-2015) project (By-products for Building Materials). Currently, the By-BM database contains individual data of about 431 by-products and 1095 building and raw materials. It was found that in case of the building materials the natural radionuclide content varied widely (Ra-226: <DL-27851 Bq/kg; Th-232: <DL-906 Bq/kg, K-40: <DL-17922 Bq/kg), more so than for the by-products (Ra-226: 7-3152 Bq/kg; Th-232: <DL-1350 Bq/kg, K-40: <DL-3001 Bq/kg). The average Ra-226, Th-232 and K-40 contents of the reported by-products were respectively 2.52, 2.35 and 0.39 times higher than the building materials. The gamma exposure of bulk building products was calculated according to IAEA Specific Safety Guide No. SSG-32 and the European Commission Radiation Protection 112 based I-index (EU BSS). It was found that in most cases the I-index without density consideration provides a significant overestimation in excess effective dose.

Risk adjustment for hospital use using social security data: cross sectional small area analysis

Objectives: To identify demographic and socioeconomic determinants of need for acute hospital treatment at small area level. To establish whether there is a relation between poverty and use of inpatient services. To devise a risk adjustment formula for distributing public funds for hospital services using, as far as possible, variables that can be updated between censuses. Design: Cross sectional analysis. Spatial interactive modelling was used to quantify the proximity of the population to health service facilities. Two stage weighted least squares regression was used to model use against supply of hospital and community services and a wide range of potential needs drivers including health, socioeconomic census variables, uptake of income support and family credit, and religious denomination. Setting: Northern Ireland. Main outcome measure: Intensity of use of inpatient services. Results: After endogeneity of supply and use was taken into account, a statistical model was produced that predicted use based on five variables: income support, family credit, elderly people living alone, all ages standardised mortality ratio, and low birth weight. The main effect of the formula produced is to move resources from urban to rural areas. Conclusions: This work has produced a population risk adjustment formula for acute hospital treatment in which four of the five variables can be updated annually rather than relying on census derived data. Inclusion of the social security data makes a substantial difference to the model and to the results produced by the formula.

Neovascular age-related macular degeneration risk based on CFH, LOC387715/HTRA1, and smoking

Age-related macular degeneration (AMD) is the major cause of blindness in the elderly. Those with the neovascular end-stage of disease have irreversible loss of central vision. AMD is a complex disorder in which genetic and environmental factors play a role. Polymorphisms in the complement factor H (CFH) gene, LOC387715, and the HTRA1 promoter are strongly associated with AMD. Smoking also contributes to the etiology. We aimed to provide a model of disease risk based on these factors.

Maternal appraisals of risk, coping and prenatal attachment among women hospitalised with pregnancy complications

One goal of pregnancy is the development of maternal emotional attachment to
the unborn baby, and this attachment has been shown to be related to later
relationships and development. There are many factors which may hinder the
development of prenatal attachment, including the presence of complications,
hospitalisation, and anxiety. However, women’s appraisals of risk may not be
congruent with medical assessments of risk. The current study sought to model
the relationships between risk (maternal perceptions and medical ratings), coping, psychological well-being, and maternal–foetal attachment among 87 women hospitalised for pregnancy-related complications. Analysis indicated that positive appraisal as a coping strategy mediates the relationship between maternal appraisals of risk and maternal–foetal attachment, and that medical ratings of risk were not predictive of maternal–foetal attachment. Awareness of the potential incongruence between patients’ and health professionals’ perceptions of risk is important within the clinical environment. The potential benefits of promoting positive appraisal in high-risk pregnancy merit further research.

Model selection approaches for non-linear system identification: a review

The identification of non-linear systems using only observed finite datasets has become a mature research area over the last two decades. A class of linear-in-the-parameter models with universal approximation capabilities have been intensively studied and widely used due to the availability of many linear-learning algorithms and their inherent convergence conditions. This article presents a systematic overview of basic research on model selection approaches for linear-in-the-parameter models. One of the fundamental problems in non-linear system identification is to find the minimal model with the best model generalisation performance from observational data only. The important concepts in achieving good model generalisation used in various non-linear system-identification algorithms are first reviewed, including Bayesian parameter regularisation and models selective criteria based on the cross validation and experimental design. A significant advance in machine learning has been the development of the support vector machine as a means for identifying kernel models based on the structural risk minimisation principle. The developments on the convex optimisation-based model construction algorithms including the support vector regression algorithms are outlined. Input selection algorithms and on-line system identification algorithms are also included in this review. Finally, some industrial applications of non-linear models are discussed.

Building on IUCN regional red lists to produce lists of species of conservation priority: a model with Irish bees

A World Conservation Union (IUCN) regional red list is an objective assessment of regional extinction risk and is not the same as a list of conservation priority species. Recent research reveals the widespread, but incorrect, assumption that IUCN Red List categories represent a hierarchical list of priorities for conservation action. We developed a simple eight-step priority-setting process and applied it to the conservation of bees in Ireland. Our model is based on the national red list but also considers the global significance of the national population; the conservation status at global, continental, and regional levels; key biological, economic, and societal factors; and is compatible with existing conservation agreements and legislation. Throughout Ireland, almost one-third of the bee fauna is threatened (30 of 100 species), but our methodology resulted in a reduced list of only 17 priority species. We did not use the priority species list to broadly categorize species to the conservation action required; instead, we indicated the individual action required for all threatened, near-threatened, and data-deficient species on the national red list based on the IUCN's conservation-actions template file. Priority species lists will strongly influence prioritization of conservation actions at national levels, but action should not be exclusive to listed species. In addition, all species on this list will not necessarily require immediate action. Our method is transparent, reproducible, and readily applicable to other taxa and regions.

Individual trade-offs between nutrition and risk of interspecific transmission of disease by grazing: cows, badger latrines and bovine tuberculosis

1. We examine whether various measures of herbivore current physiological state (age, breeding and immune status) and genetic potential can be used as indicators of exposure to and risk from disease. We use dairy cattle and the risks of tuberculosis (TB) transmission posed to them by pasture contaminated with badger excreta (via the fecal-oral route) as a model system to address our aim.

Dietary glycaemic index, glycaemic load and breast cancer risk: a systematic review and meta-analysis

This systematic review aimed to examine if an association exists between dietary glycaemic index (GI) and glycaemic load (GL) intake and breast cancer risk. A systematic search was conducted in Medline and Embase and identified 14 relevant studies up to May 2008. Adjusted relative risk estimates comparing breast cancer risk for the highest versus the lowest category of GI/GL intake were extracted from relevant studies and combined in meta-analyses using a random-effects model. Combined estimates from six cohort studies show non-significant increased breast cancer risks for premenopausal women (relative risk (RR) 1.14, 95% CI 0.95-1.38) and postmenopausal women (RR 1.11, 95% CI 0.99-1.25) consuming the highest versus the lowest category of GI intake. Evidence of heterogeneity hindered analyses of GL and premenopausal risk, although most studies did not observe any significant association. Pooled cohort study results indicated no association between postmenopausal risk and GL intake (RR 1.03, 95% CI 0.94-1.12). Our findings do not provide strong support of an association between dietary GI and GL and breast cancer risk. © 2008 Cancer Research UK.


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