Multivariate Risk Assessment Research Articles

CEEG electrode-related pressure ulcers in acutely hospitalized patients.

Pressure ulcers resulting from continuous EEG (cEEG) monitoring in hospitalized patients have gained attention as a preventable medical complication. We measured their incidence and risk factors. We performed an observational investigation of cEEG-electrode-related pressure ulcers (EERPU) among acutely ill patients over a 22-month period. Variables analyzed included age, sex, monitoring duration, hospital location, application methods, vasopressor usage, nutritional status, skin allergies, fever, and presence/severity of EERPU. We examined risk for pressure ulcers vs monitoring duration using Kaplan-Meyer survival analysis, and performed multivariate risk assessment using Cox proportional hazard model. Among 1,519 patients, EERPU occurred in 118 (7.8%). Most (n = 109, 92.3%) consisted of hyperemia only without skin breakdown. A major predictor was monitoring duration, with 3-, 5-, and 10-day risks of 16%, 32%, and 60%, respectively. Risk factors included older age (mean age 60.65 vs 50.3, p < 0.01), care in an intensive care unit (9.37% vs 5.32%, p < 0.01), lack of a head wrap (8.31% vs 27.3%, p = 0.02), use of vasopressors (16.7% vs 9.64%, p < 0.01), enteral feeding (11.7% vs 5.45%, p = 0.04), and fever (18.4% vs 9.3%, p < 0.01). Elderly patients (71-80 years) were at higher risk (hazard ratio 6.84 [1.95-24], p < 0.01), even after accounting for monitoring time and other pertinent variables in multivariate analysis. EERPU are uncommon and generally mild. Elderly patients and those with more severe illness have higher risk of developing EERPU, and the risk increases as a function of monitoring duration.

A multivariate copula‐based framework for dealing with hazard scenarios and failure probabilities

AbstractThis paper is of methodological nature, and deals with the foundations of Risk Assessment. Several international guidelines have recently recommended to select appropriate/relevant Hazard Scenarios in order to tame the consequences of (extreme) natural phenomena. In particular, the scenarios should be multivariate, i.e., they should take into account the fact that several variables, generally not independent, may be of interest. In this work, it is shown how a Hazard Scenario can be identified in terms of (i) a specific geometry and (ii) a suitable probability level. Several scenarios, as well as a Structural approach, are presented, and due comparisons are carried out. In addition, it is shown how the Hazard Scenario approach illustrated here is well suited to cope with the notion of Failure Probability, a tool traditionally used for design and risk assessment in engineering practice. All the results outlined throughout the work are based on the Copula Theory, which turns out to be a fundamental theoretical apparatus for doing multivariate risk assessment: formulas for the calculation of the probability of Hazard Scenarios in the general multidimensional case ( ) are derived, and worthy analytical relationships among the probabilities of occurrence of Hazard Scenarios are presented. In addition, the Extreme Value and Archimedean special cases are dealt with, relationships between dependence ordering and scenario levels are studied, and a counter‐example concerning Tail Dependence is shown. Suitable indications for the practical application of the techniques outlined in the work are given, and two case studies illustrate the procedures discussed in the paper.

Role of imaging in evaluation of sudden cardiac death risk in hypertrophic cardiomyopathy.

Hypertrophic cardiomyopathy (HCM) is the most common heritable cardiomyopathy and is associated with sudden cardiac death (SCD) - an uncommon but devastating clinical outcome. This review is designed to assess the role of imaging in established risk factor assessment and its role in emerging SCD risk stratification. Recent publications have highlighted the crucial role of imaging in HCM SCD risk stratification. Left ventricular hypertrophy assessment remains the key imaging determinant of risk. Data continue to emerge on the role of systolic dysfunction, apical aneurysms, left atrial enlargement and left ventricular outflow tract obstruction as markers of risk. Quantitative assessment of delayed myocardial enhancement and T1 mapping on cardiac MRI continue to evolve. Recent multicenter trials have allowed multivariate SCD risk assessment in large HCM cohorts. Given aggregate risk with presence of multiple risk factors, a single parameter should not be used in isolation to determine implantable cardiac defibrillator candidacy. Use of all available imaging data, including cardiac magnetic resonance tissue characterization, allows a comprehensive approach to SCD stratification and implantable cardiac defibrillator decision-making.

Characterization and risk assessment of PAH-contaminated river sediment by using advanced multivariate methods

This study applied advanced multivariate methods and risk assessment to evaluate the characteristics of polycyclic aromatic hydrocarbons (PAHs) in the sediment of the severely polluted Erjen River in Taiwan. High-molecular-weight PAHs (HPAHs) dominated in the rainy season. The ecological risk of PAHs in the sediment was low, whereas the total health risk through ingestion and dermal contact was considerably high. The SOM (self-organizing map) analysis clustered the datasets of PAH-contaminated sediment into five groups with similar concentration levels. Factor analysis identified major factors, namely coal combustion, traffic, petrogenic, and petrochemical industry factors, accounting for 88.67% of the variance in the original datasets. The major tributary and the downstream of the river were identified as PAH-contamination hotspots. The PMF (positive matrix factorization) was combined with toxicity assessment to estimate the possible apportionment of sources and the associated toxicity. Spills of petroleum-related products, vehicle exhaust, coal combustion, and exhaust from a petrochemical industry complex constituted respectively 12%, 6%, 74%, and 86% of PAHs in the sediment, but contributed respectively 7%, 15%, 22%, and 56% of toxicity posed by PAHs in the sediment. To improve the sediment quality, best management practices should be adopted to eliminate nonpoint sources of PAHs flushed by storm water into the major tributary and the downstream of the Erjen River. The proposed methodologies and results provide useful information on remediating river PAH-contaminated sediment and may be applicable to other basins with similar properties that are experiencing resembled river environmental issues.

PD46-03 PROSTATE CANCER DETECTION AFTER THREE NEGATIVE SCREENS WITH A 4-YEAR INTERVAL. ERSPC ROTTERDAM

You have accessJournal of UrologyProstate Cancer: Detection and Screening V1 Apr 2015PD46-03 PROSTATE CANCER DETECTION AFTER THREE NEGATIVE SCREENS WITH A 4-YEAR INTERVAL. ERSPC ROTTERDAM Monique Roobol, Daan Nieboer, and ERSPC study group Rotterdam Monique RoobolMonique Roobol More articles by this author , Daan NieboerDaan Nieboer More articles by this author , and ERSPC study group RotterdamERSPC study group Rotterdam More articles by this author View All Author Informationhttps://doi.org/10.1016/j.juro.2015.02.2734AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookTwitterLinked InEmail INTRODUCTION AND OBJECTIVES Whether or not repeated PSA based screening has an effect on reduction of advanced disease/PC mortality or merely contributes to over diagnosis is still unclear. In ERSPC Rotterdam men (55 to 74 yrs)are screened with a 4-year interval. Depending age at 1st screen 5 screens are possible. Here we report on cancer detection rate (CDR), tumor characteristics and screening history of/before 4th screening round (S-round, i.e. 12 years after 1st screening and completed 3 previous screens) and assess the possibility of selective detection of potentially aggressive PC. METHODS So far 3,253 men completed 4th screening (80%). A PSA >= 3.0 ng/ml triggered sextant biopsy (Bx). PC detected were subdivided according to d'Amico classification. Baseline age and PSA, PSA and PSA density at 4th S-round and PSA velocity ((PSA-V) from 0 – 4, 0-8 and 0-12 yr) and the risk count ( # intervals that PSA-V > 0.4 ng/ml/yr) were related to PC detection at 4th screening. RESULTS Median age at 4th screening was 70.3 (67.0-75). Eligible for Bx were 666 men (20.5%) and 566 men had a Bx (85%), 59% had a previous negative Bx. A total of 133 PC cases were detected (PPV = 133/566 = 23.5% and CDR = 133/3252 = 4.1%). 107 men (80.5%) had low, 15 (11.3%) intermediate and 11 (8.3%) high risk PC (table). PSA-density and having had a previous negative Bx were significant predictors in a multivariable regression analysis (including age at 4th screening and PSA-V4) with outcome noPC+low risk PC vs. intermediate + high risk PC (AUC 0.811). At 92% sensitivity (but including all high risk PC) 221 Bx could be avoided (39%) including the diagnosis of 24 low risk PC. Risk count did not have any added value in this screening setting. CONCLUSIONS After 3 previous S-rounds, each with an interval of 4 yr, overall PPV and CDR at 4th screening are comparable to earlier S-rounds. Most PC detected are however low risk and, considering the age of men, potentially over diagnosed. However, taking into account a life expectancy of at least 10 years selective detection of potentially aggressive PC is still warranted. Especially in a repeat screening setting a multivariate risk assessment including PSA density and previous Bx status should be used in the decision to biopsy in order to avoid unnecessary testing and potential over diagnosis. © 2015 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 193Issue 4SApril 2015Page: e957 Peer Review Report Advertisement Copyright & Permissions© 2015 by American Urological Association Education and Research, Inc.MetricsAuthor Information Monique Roobol More articles by this author Daan Nieboer More articles by this author ERSPC study group Rotterdam More articles by this author Expand All Advertisement Advertisement PDF downloadLoading ...

Predicting the risk of recurrent venous thromboembolism (VTE).

To optimize patient outcomes with anticoagulation for venous thromboembolism (VTE), it is essential to assess patients for their recurrence risk. In this article, I will review the impact of clinical and laboratory risk factors for recurrent VTE. The presence or absence of VTE risk factors at the time of the index thrombotic event provides important information regarding recurrence risk. Patients with potent situational risk factors for thrombosis (e.g., surgery) are at low risk for recurrence while patients suffering unprovoked events are at high risk for recurrence. The presence of non-surgical clinical risk factors place patients at intermediate recurrence risk. Other clinical risk factors of variable recurrence potential include age, sex, cancer, pregnancy/puerperium, hormonal therapy and obesity. Laboratory risk factors for recurrence include thrombophilia, D dimer and other global coagulation assays as well as residual venous obstruction. Several multivariate VTE risk assessment models have been developed that combine clinical and laboratory risk factors of recurrence. If validated, these risk scores may allow for personalized anticoagulation therapy tailored to patients' individual recurrence risk.

Multivariate flood risk assessment based on the secondary return period

由于洪水是一种具有多个特征属性的随机事件,频率分析成为洪水风险评估的一种有效手段,多变量重现期与设计值的定义与计算则是洪水频率分析中的重点和难点.本文通过构造洪水历时、洪峰与洪量的联合分布,介绍了一种新的多变量重现期定义——二次重现期,并探讨了或重现期、且重现期和二次重现期对安全与危险域识别的差异性,以及在洪水风险管理与工程设计中的合理性与可靠性.传统的或和且多变量重现期对安全与危险域的识别存在局限性,利用Kendall函数定义的二次重现期则提供了更加合理的安全与风险域识别,避免了对安全事件与危险事件的错误判定,更有利于指导洪水风险的管理.在给定的二次重现期条件下,依据出现概率最大原则推算的历时、洪峰与洪量设计值组合可以满足工程设计以较低成本承受较大风险的追求,相比于单变量设计值,考虑了洪水多个属性联合特征的多变量设计值提供了更加全面和可靠的参考信息.;Frequency analysis is a useful tool for flood risk assessment, but the definition and calculation of return periods and design values in a multivariate framework are difficult tasks. In this paper, by constructing the joint distribution of flood duration, peak discharge and volume, we introduced the definitions of multivariate OR, AND and secondary return periods and discuss their differences in identifying the safe and dangerous regions in a critical level. The rationality and reliability of information provided from them in flood risk management and engineering design were then analyzed, respectively. The traditional OR-AND approach in multivariate return periods definition is limited in the identification of safe and dangerous regions, while the secondary return period based on the Kendall measure would be more rational. Consequently, mistakes in the recognition of safe and dangerous event can be avoided by the use of second return period, which, obviously, is better for the flood risk management. For a given second return period, the combination of flood duration, peak discharge and volume design values calculated from the most-likely approach, may have an advantage to meet the requirement that with low cost to bear greater risks in engineering design. Furthermore, the information provided from multivariate design values would be more considerate and reliable than the univariate ones.

Correlation and Dependency in Multivariate Process Risk Assessment

Process safety and risk assessment are often multidimensional and hence require the joint modeling of several potentially correlated random variables. Any effort to address the correlation among the input variables is important and could improve the accuracy in practical applications of risk assessment models. This paper discusses the problems with correlated variables used in risk assessment and presents a copula-based technique to model dependency among variables to improve uncertainty analysis. Using the copula approach, capturing the dependence structure among different risk factors and estimating the univariate risk marginals can be separated. This advantage simplifies the overall risk estimation for systems with multiple dependent risk sources. The advantage of the copula-based framework for generalization over the traditional correlation analysis technique is demonstrated using a case study. Methods are also presented for copula selection and estimation of the copula parameters.

Multivariate Statistical Analysis and Risk Assessment of Heavy Metals Monitored in Surface Sediment of the Luan River and its Tributaries, China

ABSTRACTIn this study, a total of 84 sites in the Luan River Basin of China and its tributaries were monitored in 2012 for seven heavy metals (Cu, Ni, Pb, Zn, Cd, Cr, Hg) in the surface sediments. Cluster analysis (CA), principal component analysis (PCA), correlation analysis, and pollution indices were applied to the interpretation of the monitoring results. The results show that: (1) sampling sites in the mainstream are classified into two groups, upstream and downstream, with downstream representing higher levels of heavy metals and degrees of pollution; (2) three clusters were identified for the 10 tributaries, the downstream having the highest levels of heavy metals’ pollution; (3) the PCA suggests there are significant correlations among Zn, Cu, and Pb between Cr in the basin. Sediment pollution assessment was carried out using Pollution Index (PI) and Geo-Accumulation Index (Igeo). Mercury was the metal with the highest contamination level, followed by Cd and Cr. The results provide an overview of the current status of sediment contamination with measured data and support future policy development for the protection of water quality in the Luan River Basin.

Informal e-waste recycling: environmental risk assessment of heavy metal contamination in Mandoli industrial area, Delhi, India

Nowadays, e-waste is a major source of environmental problems and opportunities due to presence of hazardous elements and precious metals. This study was aimed to evaluate the pollution risk of heavy metal contamination by informal recycling of e-waste. Environmental risk assessment was determined using multivariate statistical analysis, index of geoaccumulation, enrichment factor, contamination factor, degree of contamination and pollution load index by analysing heavy metals in surface soils, plants and groundwater samples collected from and around informal recycling workshops in Mandoli industrial area, Delhi, India. Concentrations of heavy metals like As (17.08 mg/kg), Cd (1.29 mg/kg), Cu (115.50 mg/kg), Pb (2,645.31 mg/kg), Se (12.67 mg/kg) and Zn (776.84 mg/kg) were higher in surface soils of e-waste recycling areas compared to those in reference site. Level exceeded the values suggested by the US Environmental Protection Agency (EPA). High accumulations of heavy metals were also observed in the native plant samples (Cynodon dactylon) of e-waste recycling areas. The groundwater samples collected form recycling area had high heavy metal concentrations as compared to permissible limit of Indian Standards and maximum allowable limit of WHO guidelines for drinking water. Multivariate analysis and risk assessment studies based on total metal content explains the clear-cut differences among sampling sites and a strong evidence of heavy metal pollution because of informal recycling of e-waste. This study put forward that prolonged informal recycling of e-waste may accumulate high concentration of heavy metals in surface soils, plants and groundwater, which will be a matter of concern for both environmental and occupational hazards. This warrants an immediate need of remedial measures to reduce the heavy metal contamination of e-waste recycling sites.

Multivariate modeling of droughts using copulas and meta-heuristic methods

This study investigated the utility of two meta-heuristic algorithms to estimate parameters of copula models and for derivation of drought severity–duration–frequency (S–D–F) curves. Drought is a natural event, which has huge impact on both the society and the natural environment. Drought events are mainly characterized by their severity, duration and intensity. The study adopts standardized precipitation index for drought characterization, and copula method for multivariate risk analysis of droughts. For accurate estimation of copula model parameters, two meta-heuristic methods namely genetic algorithm and particle swarm optimization are applied. The proposed methodology is applied to a case study in Trans Pecos, an arid region in Texas, USA. First, drought severity and duration are separately modeled by various probability distribution functions and then the best fitted models are selected for copula modeling. For modeling the joint dependence of drought variables, different classes of copulas, namely, extreme value copulas, Plackett and Student’s t copulas are employed and their performance is evaluated using standard performance measures. It is found that for the study region, the Gumbel–Hougaard copula is the best fitted copula model as compared to the others and is used for the development of drought S–D–F curves. Results of the study suggest that the meta-heuristic methods have greater utility in copula-based multivariate risk assessment of droughts.

Exploring natural and anthropogenic risk for cultural heritage in Cyprus using remote sensing and GIS

On site observation is the most common way of monitoring cultural heritage sites and monuments in Cyprus. However, this procedure that includes data collection, periodical observations, and multivariate risk assessment analysis is difficult to accomplish with the traditional practices and methods since it is time consuming and expensive. Furthermore, many archaeological sites and monuments are located at inaccessible areas, far away from the main road network and urban areas. Satellite remote sensing and Geographical Information Systems (GIS) can successfully confront this problem by providing the scientists with integrated monitoring of the study areas and the unique advantage to store and manipulate a large amount of spatial and attribute data simultaneously. Actually the monitoring and identification of several natural and anthropogenic hazards in the vicinity of the cultural heritage sites in Cyprus, seems to be one of the main priorities of its governmental and municipal authorities. This study aims to integrate both satellite remote sensing techniques and GIS in a multidisciplinary approach, for monitoring anthropogenic and natural hazards with the use of archived and up-to-date multitemporal remotely sensed images in the study area, namely in areas nearby cultural heritage sites and monuments in Cyprus. In this study anthropogenic hazards include urbanisation and extended land use changes in the surroundings of archaeological sites and natural hazards concern seismicity and sea erosion.

Soluble Human Epidermal Growth Factor Receptor 2 (sHER2) as a Potential Risk Assessment, Screening, and Diagnostic Biomarker of Lung Adenocarcinoma.

Lung cancer is the leading cause of cancer-related death in the United States. Here, we evaluated the potential clinical utility of soluble human epidermal growth factor receptor 2 (sHER2) for the risk assessment, screening, and diagnosis of non-small cell lung cancer (NSCLC) using an unmatched case-control study design. Serum sHER2 concentrations were measured by immunoassay in 244 primary NSCLC cases and 218 healthy controls. Wilcoxon rank-sum tests, logistic regression models, and receiver operating characteristic plots were used to assess whether sHER2 is associated with lung cancer. Median serum sHER2 concentrations are higher in patients with adenocarcinoma than squamous cell carcinoma regardless of gender, and sHER2 is a weak, independent biomarker of adenocarcinoma, but not of squamous cell carcinoma, adjusted for age and gender. The age-adjusted relative risk (odds) of adenocarcinoma is 3.95 (95% CI: 1.22, 12.81) and 7.93 (95% CI: 2.26, 27.82) greater for women and men with high sHER2 concentrations (≥6.60 ng/mL) vs. low sHER2 concentrations (≤1.85 ng/mL), respectively. When adjusted for each other, sHER2, age, and gender discern healthy controls from patients with primary adenocarcinomas of the lung with 85.9% accuracy. We conclude that even though serum sHER2 is not a strong, stand-alone discriminatory biomarker of adenocarcinoma, sHER2 may be a useful, independent covariate in multivariate risk assessment, screening, and diagnostic models of lung cancer.

Multivariate erosion risk assessment of lateritic badlands of Birbhum (West Bengal, India): A case study

Each geomorphic hazard involves a degree of risk which incorporates quantification of the probability that a hazard will be harmful. At present, the categorization of sub-watersheds into erosion risk is considered as the fundamental step to conserve the soil loss. Development of badlands over the laterites of Birbhum district is an indicative of excessive soil loss in the monsoonal wet-dry type of climate. Slope erosion and channel erosion have generated huge amount of sediment from the small watersheds during intense monsoonal rainfall (June–September). The adjoining areas of Rampurhat I Block, Birbhum (West Bengal) and Shikaripara Block, Dumka (Jharkhand) have lost the lateritic soil cover at a rate of 20–40 ton/ha/year (Sarkar et al. 2005). In order to estimate the progressive removal of soil particles from the gully-catchments of the above-mentioned area, different morphometric parameters, soil parameters, hydrologic parameters and empirical models are employed. Side by side, the study is carried out to categorize the gully-catchments into different magnitude of erosion risk using several multivariate statistical techniques.

High-risk nonmuscle invasive bladder cancer

Nonmuscle invasive bladder cancer represents a large majority of patients diagnosed with this disease. Precise definition and risk stratification are paramount in this group as high-risk patients have higher rates of progression and mortality and may benefit from early identification and aggressive treatment. The mainstay definitions of high-risk nonmuscle invasive bladder cancer are based on grade and stage. Recently, efforts have been made to incorporate other clinical variables into multivariate risk assessment tools and nomograms to predict disease behavior and guide management. Variant histology and molecular biomarkers are being explored as tools to refine risk stratification; however, results are still preliminary and need validation. Future research should concentrate on ways to better risk-stratify patients and identify early those that are most likely to recur and progress quickly. Topics of focus should be on better multivariate risk assessment tools and nomograms providing continuous scales and incorporating molecular markers with validation in large multi-institutional cohorts.

Asymptotic Dependence for Light-Tailed Homothetic Densities

Dependence between coordinate extremes is a key factor in any multivariate risk assessment. Hence, it is of interest to know whether the components of a given multivariate random vector exhibit asymptotic independence or asymptotic dependence. In the latter case the structure of the asymptotic dependence has to be clarified. In the multivariate setting it is common to have an explicit form of the density rather than the distribution function. In this paper we therefore give criteria for asymptotic dependence in terms of the density. We consider distributions with light tails and restrict attention to continuous unimodal densities defined on the whole space or on an open convex cone. For simplicity, the density is assumed to behomothetic: all level sets have the same shape. Balkema and Nolde (2010) contains conditions on the shape which guarantee asymptotic independence. The situation for asymptotic dependence, treated in the present paper, is more delicate.

Asymptotic Dependence for Light-Tailed Homothetic Densities

Dependence between coordinate extremes is a key factor in any multivariate risk assessment. Hence, it is of interest to know whether the components of a given multivariate random vector exhibit asymptotic independence or asymptotic dependence. In the latter case the structure of the asymptotic dependence has to be clarified. In the multivariate setting it is common to have an explicit form of the density rather than the distribution function. In this paper we therefore give criteria for asymptotic dependence in terms of the density. We consider distributions with light tails and restrict attention to continuous unimodal densities defined on the whole space or on an open convex cone. For simplicity, the density is assumed to be homothetic: all level sets have the same shape. Balkema and Nolde (2010) contains conditions on the shape which guarantee asymptotic independence. The situation for asymptotic dependence, treated in the present paper, is more delicate.

Thirty-Year Multivariate Risk Assessment Is a Stronger Predictor of Cardiovascular Disease than the 10-Year Model

Identifying individuals at risk for developing coronary heart disease (CHD)1 is fundamental to the practice of primary prevention in modern cardiology because it enables clinicians to determine which patients are eligible to receive evidence-based therapies that can prevent or delay the progression of atherosclerotic disease. Several multivariable risk-prediction algorithms are available, and the most widely used in the US is the Framingham cardiovascular disease (CVD) risk profile, from which the Framingham Risk Score (FRS) is derived. The FRS estimates an individual’s risk of developing nonfatal myocardial infarction or CHD-related death (“hard events”) over a 10-year period, on the basis of what are now considered to be the traditional risk factors of age, total cholesterol concentrations, HDL cholesterol, systolic blood pressure, and cigarette smoking status; the equations are sex specific. Individuals are then stratified into low risk ( 20% risk over 10 years) based on their score (1), and this risk score then guides a clinician’s decision to institute antiplatelet or lipid-lowering therapy or advise intensive lifestyle modification. Several multivariate risk assessment algorithms in addition to the FRS have since been proposed and validated in diverse populations to estimate risk for a period of less than 10 years. The FRS has been critiqued for its relatively limited view of only a10-year timeframe, because an individual’s lifetime risk of CHD may be high, but a 10-year risk prediction model sometimes underestimates this risk and can delay efforts to modify that risk. A greater duration of exposure to untreated risk factors allows for continued progression of subclinical atherosclerosis. Examination of the Framingham cohort showed that despite younger individuals in lower risk groups having a very low 10-year CHD …

The association of the composite IL‐1 genotype with periodontitis progression and/or treatment outcomes: a systematic review

Genetically transmitted traits such as cytokine gene polymorphisms may accentuate the host inflammatory response to the bacterial challenge and influence susceptibility to periodontitis. To systematically review the evidence of an association between the interleukin-1 (IL-1) composite genotype, i.e. presence of the allele 2 in the gene clusters IL-1A-889 and in IL-1B +3953, and periodontitis progression and/or treatment outcomes. Based on the focused question, a search was conducted for longitudinal clinical trials comparing progression of periodontitis and/or treatment outcomes in IL-1 genotype-positive (carrying allele 2) and IL-1 genotype-negative (not carrying allele 2) subjects. A search in the National Library of Medicine computerized bibliographic database MEDLINE and a manual search were performed. Selection of publications, extraction of data and validity assessment were made independently by two reviewers. The search provided 122 titles of which 11 longitudinal publications were included. The heterogeneity of the data prevented the performance of a meta-analysis. While findings from some publications rejected a possible role of IL-1 composite genotype on progression of periodontitis after various therapies, other reported a prognostic value for disease progression of the positive IL-1 genotype status. When assessed on a multivariate risk assessment model, several publications concluded that the assessment of the IL-1 composite genotype in conjunction with other covariates (e.g. smoking and presence of specific bacteria) may provide additional information on disease progression. The small sample size of the available publications, however, requires caution in the interpretation of the results. Based on these findings, (i) there is insufficient evidence to establish if a positive IL-1 genotype status contributes to progression of periodontitis and/or treatment outcomes. Therefore, (ii) results obtained with commercially available tests should be interpreted with caution.

A Multivariate Fall Risk Assessment Model for VHA Nursing Homes Using the Minimum Data Set

The purpose of this study was to develop a multivariate fall risk assessment model beyond the current fall Resident Assessment Protocol (RAP) triggers for nursing home residents using the Minimum Data Set (MDS). Retrospective, clustered secondary data analysis. National Veterans Health Administration (VHA) long-term care nursing homes (N = 136). The study population consisted of 6577 national VHA nursing home residents who had an annual assessment during FY 2005, identified from the MDS, as well as an earlier annual or admission assessment within a 1-year look-back period. A dichotomous multivariate model of nursing home residents coded with a fall on selected fall risk characteristics from the MDS, estimated with general estimation equations (GEE). There were 17 170 assessments corresponding to 6577 long-term care nursing home residents. The increased odds ratio (OR) of being classified as a faller relative to the omitted "dependent" category of activities of daily living (ADL) ranged from OR = 1.35 for "limited" ADL category up to OR = 1.57 for "extensive-2" ADL (P < .0001). Unsteady gait more than doubles the odds of being a faller (OR = 2.63, P < .0001). The use of assistive devices such as canes, walkers, or crutches, or the use of wheelchairs increases the odds of being a faller (OR = 1.17, P < .0005) or (OR = 1.19, P < .0002), respectively. Foot problems may also increase the odds of being a faller (OR = 1.26, P < .0016). Alzheimer's or other dementias also increase the odds of being classified as a faller (OR = 1.18, P < .0219) or (OR=1.22, P < .0001), respectively. In addition, anger (OR = 1.19, P < .0065); wandering (OR = 1.53, P < .0001); or use of antipsychotic medications (OR = 1.15, P < .0039), antianxiety medications (OR = 1.13, P < .0323), or antidepressant medications (OR = 1.39, P < .0001) was also associated with the odds of being a faller. This national study in one of the largest managed healthcare systems in the United States has empirically confirmed the relative importance of certain risk factors for falls in long-term care settings. The model incorporated an ADL index and adjusted for case mix by including only long-term care nursing home residents. The study offers clinicians practical estimates by combining multiple univariate MDS elements in an empirically based, multivariate fall risk assessment model.