Do selective cyclo-oxygenase-2 inhibitors and traditional non-steroidal anti-inflammatory drugs increase the risk of atherothrombosis? Meta-analysis of randomised trials

Objective: To assess the effects of selective cyclo-oxygenase-2 (COX 2) inhibitors and traditional non-steroidal anti-inflammatory drugs (NSAIDs) on the risk of vascular events. Design: Meta-analysis of published and unpublished tabular data from randomised trials, with indirect estimation of the effects of traditional NSAIDs. Data sources: Medline and Embase (January 1966 to April 2005); Food and Drug Administration records; and data on file from Novartis, Pfizer, and Merck. Review methods: Eligible studies were randomised trials that included a comparison of a selective COX 2 inhibitor versus placebo or a selective COX 2 inhibitor versus a traditional NSAID, of at least four weeks' duration, with information on serious vascular events (defined as myocardial infarction, stroke, or vascular death). Individual investigators and manufacturers provided information on the number of patients randomised, numbers of vascular events, and the person time of follow-up for each randomised group. Results: In placebo comparisons, allocation to a selective COX 2 inhibitor was associated with a 42% relative increase in the incidence of serious vascular events (1.2%/year v 0.9%/year; rate ratio 1.42, 95% confidence interval 1.13 to 1.78; P = 0.003), with no significant heterogeneity among the different selective COX 2 inhibitors. This was chiefly attributable to an increased risk of myocardial infarction (0.6%/year v 0.3%/year; 1.86, 1.33 to 2.59; P = 0.0003), with little apparent difference in other vascular outcomes. Among trials of at least one year's duration (mean 2.7 years), the rate ratio for vascular events was 1.45 (1.12 to 1.89; P = 0.005). Overall, the incidence of serious vascular events was similar between a selective COX 2 inhibitor and any traditional NSAID (1.0%/year v 0.9/%year; 1.16, 0.97 to 1.38; P = 0.1). However, statistical heterogeneity (P = 0.001) was found between trials of a selective COX 2 inhibitor versus naproxen (1.57, 1.21 to 2.03) and of a selective COX 2 inhibitor versus non-naproxen NSAIDs (0.88, 0.69 to 1.12). The summary rate ratio for vascular events, compared with placebo, was 0.92 (0.67 to 1.26) for naproxen, 1.51 (0.96 to 2.37) for ibuprofen, and 1.63 (1.12 to 2.37) for diclofenac. Conclusions: Selective COX 2 inhibitors are associated with a moderate increase in the risk of vascular events, as are high dose regimens of ibuprofen and diclofenac, but high dose naproxen is not associated with such an excess.

Optimal Capital Requirements in Financial Networks with Fire Sales

I explore and analyze a problem of finding the socially optimal capital requirements for financial institutions considering two distinct channels of contagion: direct exposures among the institutions, as represented by a network and fire sales externalities, which reflect the negative price impact of massive liquidation of assets.These two channels amplify shocks from individual financial institutions to the financial system as a whole and thus increase the risk of joint defaults amongst the interconnected financial institutions; this is often referred to as systemic risk. In the model, there is a trade-off between reducing systemic risk and raising the capital requirements of the financial institutions. The policymaker considers this trade-off and determines the optimal capital requirements for individual financial institutions. I provide a method for finding and analyzing the optimal capital requirements that can be applied to arbitrary network structures and arbitrary distributions of investment returns.

In particular, I first consider a network model consisting only of direct exposures and show that the optimal capital requirements can be found by solving a stochastic linear programming problem. I then extend the analysis to financial networks with default costs and show the optimal capital requirements can be found by solving a stochastic mixed integer programming problem. The computational complexity of this problem poses a challenge, and I develop an iterative algorithm that can be efficiently executed. I show that the iterative algorithm leads to solutions that are nearly optimal by comparing it with lower bounds based on a dual approach. I also show that the iterative algorithm converges to the optimal solution.

Finally, I incorporate fire sales externalities into the model. In particular, I am able to extend the analysis of systemic risk and the optimal capital requirements with a single illiquid asset to a model with multiple illiquid assets. The model with multiple illiquid assets incorporates liquidation rules used by the banks. I provide an optimization formulation whose solution provides the equilibrium payments for a given liquidation rule.

I further show that the socially optimal capital problem using the ``socially optimal liquidation" and prioritized liquidation rules can be formulated as a convex and convex mixed integer problem, respectively. Finally, I illustrate the results of the methodology on numerical examples and

discuss some implications for capital regulation policy and stress testing.

On the Advancement of Probabilistic Models of Decompression Sickness

The work presented in this dissertation is focused on applying engineering methods to develop and explore probabilistic survival models for the prediction of decompression sickness in US NAVY divers. Mathematical modeling, computational model development, and numerical optimization techniques were employed to formulate and evaluate the predictive quality of models fitted to empirical data. In Chapters 1 and 2 we present general background information relevant to the development of probabilistic models applied to predicting the incidence of decompression sickness. The remainder of the dissertation introduces techniques developed in an effort to improve the predictive quality of probabilistic decompression models and to reduce the difficulty of model parameter optimization.

The first project explored seventeen variations of the hazard function using a well-perfused parallel compartment model. Models were parametrically optimized using the maximum likelihood technique. Model performance was evaluated using both classical statistical methods and model selection techniques based on information theory. Optimized model parameters were overall similar to those of previously published Results indicated that a novel hazard function definition that included both ambient pressure scaling and individually fitted compartment exponent scaling terms.

We developed ten pharmacokinetic compartmental models that included explicit delay mechanics to determine if predictive quality could be improved through the inclusion of material transfer lags. A fitted discrete delay parameter augmented the inflow to the compartment systems from the environment. Based on the observation that symptoms are often reported after risk accumulation begins for many of our models, we hypothesized that the inclusion of delays might improve correlation between the model predictions and observed data. Model selection techniques identified two models as having the best overall performance, but comparison to the best performing model without delay and model selection using our best identified no delay pharmacokinetic model both indicated that the delay mechanism was not statistically justified and did not substantially improve model predictions.

Our final investigation explored parameter bounding techniques to identify parameter regions for which statistical model failure will not occur. When a model predicts a no probability of a diver experiencing decompression sickness for an exposure that is known to produce symptoms, statistical model failure occurs. Using a metric related to the instantaneous risk, we successfully identify regions where model failure will not occur and identify the boundaries of the region using a root bounding technique. Several models are used to demonstrate the techniques, which may be employed to reduce the difficulty of model optimization for future investigations.

Inverse Association Between Gluteofemoral Obesity and Risk of Barrett's Esophagus in a Pooled Analysis

BACKGROUND & AIMS: Gluteofemoral obesity (determined by measurement of subcutaneous fat in hip and thigh regions) could reduce risks of cardiovascular and diabetic disorders associated with abdominal obesity. We evaluated whether gluteofemoral obesity also reduces risk of Barrett's esophagus (BE), a premalignant lesion associated with abdominal obesity.

METHODS: We collected data from non-Hispanic white participants in 8 studies in the Barrett's and Esophageal Adenocarcinoma Consortium. We compared measures of hip circumference (as a proxy for gluteofemoral obesity) from cases of BE (n=1559) separately with 2 control groups: 2557 population-based controls and 2064 individuals with gastroesophageal reflux disease (GERD controls). Study-specific odds ratios (OR) and 95% confidence intervals (95% CI) were estimated using individual participant data and multivariable logistic regression and combined using random effects meta-analysis.

RESULTS: We found an inverse relationship between hip circumference and BE (OR per 5 cm increase, 0.88; 95% CI, 0.81-0.96), compared with population-based controls in a multivariable model that included waist circumference. This association was not observed in models that did not include waist circumference. Similar results were observed in analyses stratified by frequency of GERD symptoms. The inverse association with hip circumference was only statistically significant among men (vs population-based controls: OR, 0.85; 95% CI, 0.76-0.96 for men; OR, 0.93; 95% CI, 0.74-1.16 for women). For men, within each category of waist circumference, a larger hip circumference was associated with decreased risk of BE. Increasing waist circumference was associated with increased risk of BE in the mutually adjusted population-based and GERD control models.

CONCLUSIONS: Although abdominal obesity is associated with increased risk of BE, there is an inverse association between gluteofemoral obesity and BE, particularly among men.

Lifestyle Risk Factors for Serrated Colorectal Polyps: a Systematic Review and Meta-Analysis

Background & Aims: Certain subsets of colorectal serrated polyps (SP) have malignant potential. Weperformed a systematic review and meta-analysis to investigate the association between modifiablelifestyle factors and risk for SPs. 
Methods: We conducted a systematic search of Medline, Embase, and Web of Science, forobservational or interventional studies that contained the terms risk or risk factor, and serrated orhyperplastic, and polyps or adenomas, and colorectal (or synonymous terms), published by March2016. Titles and abstracts of identified articles were independently reviewed by at least 2 reviewers.Adjusted relative risks (RR) and 95% CIs were combined using random effects meta-analyses toassess the risk of SP, when possible. 
Results: We identified 43 studies of SP risk associated with 7 different lifestyle factors: smoking,alcohol, body fatness, diet, physical activity, medication and/or hormone replacement therapy.When we compared the highest and lowest categories of exposure, factors we found to significantlyincrease risk for SP included tobacco smoking (RR, 2.47; 95% CI, 2.12–2.87), alcohol intake (RR, 1.33;95% CI, 1.17–1.52), body mass index (RR, 1.40; 95% CI, 1.22–1.61), and high intake of fat or meat.Direct associations for smoking and alcohol, but not body fat, tended to be stronger for sessileserrated adenomas/polyps than hyperplastic polyps. In contrast, factors we found to significantlydecrease risks for SP included use of non-steroidal anti-inflammatory drugs (RR, 0.77; 95% CI, 0.65–0.92) or aspirin (RR, 0.81; 95% CI, 0.67–0.99), as well as high intake of folate, calcium, or fiber. Nosignificant associations were detected between SP risk and physical activity or hormone replacementtherapy. 
Conclusions: Several lifestyle factors, most notably smoking and alcohol, are associated with SP risk.These findings enhance our understanding of mechanisms of SP development and indicate that riskof serrated pathway colorectal neoplasms could be reduced with lifestyle changes.

Multiphase flow in porous media: meta-modeling techniques for sensitivity analysis and risk assessment

One of the biggest challenges that contaminant hydrogeology is facing, is how to adequately address the uncertainty associated with model predictions. Uncertainty arise from multiple sources, such as: interpretative error, calibration accuracy, parameter sensitivity and variability. This critical issue needs to be properly addressed in order to support environmental decision-making processes. In this study, we perform Global Sensitivity Analysis (GSA) on a contaminant transport model for the assessment of hydrocarbon concentration in groundwater. We provide a quantification of the environmental impact and, given the incomplete knowledge of hydrogeological parameters, we evaluate which are the most influential, requiring greater accuracy in the calibration process. Parameters are treated as random variables and a variance-based GSA is performed in a optimized numerical Monte Carlo framework. The Sobol indices are adopted as sensitivity measures and they are computed by employing meta-models to characterize the migration process, while reducing the computational cost of the analysis. The proposed methodology allows us to: extend the number of Monte Carlo iterations, identify the influence of uncertain parameters and lead to considerable saving computational time obtaining an acceptable accuracy.

Global, regional, and national comparative risk assessment of 79 behavioural, environmental and occupational, and metabolic risks or clusters of risks in 188 countries, 1990-2013 : a systematic analysis for the Global Burden of Disease Study 2013

Global, regional, and national comparative risk assessment of 79 behavioral, environmental and occupational, and metabolic risks or clusters of risks, 1990–2015 : a systematic analysis for the Global Burden of Disease Study 2015

Performance of protective factors assessment in risk prediction for adults: systematic review and meta-analysis

Protective factors are neglected in risk assessment in adult psychiatric and criminal justice populations. This review investigated the predictive efficacy of selected tools that assess protective factors. Five databases were searched using comprehensive terms for records up to June 2014, resulting in 17 studies (n = 2,198). Results were combined in a multilevel meta-analysis using the R (R Core Team, R: A Language and Environment for Statistical Computing, Vienna, Austria: R Foundation for Statistical Computing, 2015) metafor package (Viechtbauer, Journal of Statistical Software, 2010, 36, 1). Prediction of outcomes was poor relative to a reference category of violent offending, with the exception of prediction of discharge from secure units. There were no significant differences between the predictive efficacy of risk scales, protective scales, and summary judgments. Protective factor assessment may be clinically useful, but more development is required. Claims that use of these tools is therapeutically beneficial require testing.

Meta-analysis of the influence of chronic kidney disease on the risk of thromboembolism among patients with nonvalvular atrial fibrillation

Chronic kidney disease (CKD) and atrial fibrillation (AF) frequently coexist. However, the extent to which CKD increases the risk of thromboembolism in patients with nonvalvular AF and the benefits of anticoagulation in this group remain unclear. We addressed the role of CKD in the prediction of thromboembolic events and the impact of anticoagulation using a meta-analysis method. Data sources included MEDLINE, EMBASE, and Cochrane (from inception to January 2014). Three independent reviewers selected studies. Descriptive and quantitative information was extracted from each selected study and a random-effects meta-analysis was performed. After screening 962 search results, 19 studies were considered eligible. Among patients with AF, the presence of CKD resulted in an increased risk of thromboembolism (hazard ratio [HR] 1.46, 95% confidence interval [CI] 1.20 to 1.76, p = 0.0001), particularly in case of end-stage CKD (HR 1.83, 95% CI 1.56 to 2.14, p <0.00001). Warfarin decreased the incidence of thromboembolic events in patients with non-end-stage CKD (HR 0.39, 95% CI 0.18 to 0.86, p <0.00001). Recent data on novel oral anticoagulants suggested a higher efficacy of these agents compared with warfarin (HR 0.80, 95% CI 0.66 to 0.96, p = 0.02) and aspirin (HR 0.32, 95% CI 0.19 to 0.55, p <0.0001) in treating non-end-stage CKD. In conclusion, the presence of CKD in patients with AF is associated with an almost 50% increased thromboembolic risk, which can be effectively decreased with appropriate antithrombotic therapy. Further prospective studies are needed to better evaluate the interest of anticoagulation in patients with severe CKD.

Toxicity and Contamination in Bear Creek Sediment: Spatial Analysis and Implications for Risk Assessment

The sediments of Bear Creek near Baltimore, Maryland demonstrate substantial toxicity to benthic organisms, and contain a complex mixture of organic and inorganic contaminants. The present study maps the spatial extent and depth profile of toxicity and contamination in Bear Creek, and explores correlations between heavy metals, organic contaminants, and toxic responses. Two novel analytical techniques – handheld XRF and an antibody-based PAH biosensor – were applied to samples from the site to quantify total metals and total PAHs in sediments. By comprehensively assessing toxicity in Bear Creek, the present study provides data to inform future risk assessments and management decisions relating for the site, while demonstrating the benefits of applying joint biological assays and chemical assessment methods to sediments with complex contaminant mixtures.

Numerical analysis of wooden slabs with perforations under fire conditions

Wood is considered an ideal solution for floors and roofs building construction, due the mechanical and thermal properties, associated with acoustic conditions. These constructions have good sound absorption, heat insulation and relevant architectonic characteristics. They are used in many civil applications: concert and conference halls, auditoriums, ceilings, walls… However, the high vulnerability of wooden elements submitted to fire conditions requires the evaluation of its structural behaviour with accuracy. The main objective of this work is to present a numerical model to assess the fire resistance of wooden cellular slabs with different perforations. Also the thermal behaviour of the wooden slabs will be compared considering different material insulation, with different sizes, inside the cavities. A transient thermal analysis with nonlinear material behaviour will be solved using ANSYS© program. This study allows to verify the fire resistance, the temperature evolution and the char-layer, throughout a wooden cellular slab with perforations and considering the insulation effect inside the cavities.