Bayesian Hierarchical Distributed Lag Models for Summer Ozone Exposure and Cardio-Respiratory Mortality

In this paper, we develop Bayesian hierarchical distributed lag models for estimating associations between daily variations in summer ozone levels and daily variations in cardiovascular and respiratory (CVDRESP) mortality counts for 19 U.S. large cities included in the National Morbidity Mortality Air Pollution Study (NMMAPS) for the period 1987 - 1994. At the first stage, we define a semi-parametric distributed lag Poisson regression model to estimate city-specific relative rates of CVDRESP associated with short-term exposure to summer ozone. At the second stage, we specify a class of distributions for the true city-specific relative rates to estimate an overall effect by taking into account the variability within and across cities. We perform the calculations with respect to several random effects distributions (normal, t-student, and mixture of normal), thus relaxing the common assumption of a two-stage normal-normal hierarchical model. We assess the sensitivity of the results to: 1) lag structure for ozone exposure; 2) degree of adjustment for long-term trends; 3) inclusion of other pollutants in the model;4) heat waves; 5) random effects distributions; and 6) prior hyperparameters. On average across cities, we found that a 10ppb increase in summer ozone level for every day in the previous week is associated with 1.25 percent increase in CVDRESP mortality (95% posterior regions: 0.47, 2.03). The relative rate estimates are also positive and statistically significant at lags 0, 1, and 2. We found that associations between summer ozone and CVDRESP mortality are sensitive to the confounding adjustment for PM_10, but are robust to: 1) the adjustment for long-term trends, other gaseous pollutants (NO_2, SO_2, and CO); 2) the distributional assumptions at the second stage of the hierarchical model; and 3) the prior distributions on all unknown parameters. Bayesian hierarchical distributed lag models and their application to the NMMAPS data allow us estimation of an acute health effect associated with exposure to ambient air pollution in the last few days on average across several locations. The application of these methods and the systematic assessment of the sensitivity of findings to model assumptions provide important epidemiological evidence for future air quality regulations.

A BAYESIAN HIERARCHICAL MODEL FOR CONSTRAINED DISTRIBUTED LAG FUNCTIONS: ESTIMATING THE TIME COURSE OF HOSPITALIZATION ASSOCIATED WITH AIR POLLUTION EXPOSURE

Numerous time series studies have provided strong evidence of an association between increased levels of ambient air pollution and increased levels of hospital admissions, typically at 0, 1, or 2 days after an air pollution episode. An important research aim is to extend existing statistical models so that a more detailed understanding of the time course of hospitalization after exposure to air pollution can be obtained. Information about this time course, combined with prior knowledge about biological mechanisms, could provide the basis for hypotheses concerning the mechanism by which air pollution causes disease. Previous studies have identified two important methodological questions: (1) How can we estimate the shape of the distributed lag between increased air pollution exposure and increased mortality or morbidity? and (2) How should we estimate the cumulative population health risk from short-term exposure to air pollution? Distributed lag models are appropriate tools for estimating air pollution health effects that may be spread over several days. However, estimation for distributed lag models in air pollution and health applications is hampered by the substantial noise in the data and the inherently weak signal that is the target of investigation. We introduce an hierarchical Bayesian distributed lag model that incorporates prior information about the time course of pollution effects and combines information across multiple locations. The model has a connection to penalized spline smoothing using a special type of penalty matrix. We apply the model to estimating the distributed lag between exposure to particulate matter air pollution and hospitalization for cardiovascular and respiratory disease using data from a large United States air pollution and hospitalization database of Medicare enrollees in 94 counties covering the years 1999-2002.

A BAYESIAN HIERARCHICAL FRAMEWORK FOR SPATIAL MODELING OF fMRI DATA

Functional neuroimaging techniques enable investigations into the neural basis of human cognition, emotions, and behaviors. In practice, applications of functional magnetic resonance imaging (fMRI) have provided novel insights into the neuropathophysiology of major psychiatric,neurological, and substance abuse disorders, as well as into the neural responses to their treatments. Modern activation studies often compare localized task-induced changes in brain activity between experimental groups. One may also extend voxel-level analyses by simultaneously considering the ensemble of voxels constituting an anatomically defined region of interest (ROI) or by considering means or quantiles of the ROI. In this work we present a Bayesian extension of voxel-level analyses that offers several notable benefits. First, it combines whole-brain voxel-by-voxel modeling and ROI analyses within a unified framework. Secondly, an unstructured variance/covariance for regional mean parameters allows for the study of inter-regional functional connectivity, provided enough subjects are available to allow for accurate estimation. Finally, an exchangeable correlation structure within regions allows for the consideration of intra-regional functional connectivity. We perform estimation for our model using Markov Chain Monte Carlo (MCMC) techniques implemented via Gibbs sampling which, despite the high throughput nature of the data, can be executed quickly (less than 30 minutes). We apply our Bayesian hierarchical model to two novel fMRI data sets: one considering inhibitory control in cocaine-dependent men and the second considering verbal memory in subjects at high risk for Alzheimer’s disease. The unifying hierarchical model presented in this manuscript is shown to enhance the interpretation content of these data sets.

Reduced Bayesian Hierarchical Models: Estimating Health Effects of Simultaneous Exposure to Multiple Pollutants

Quantifying the health effects associated with simultaneous exposure to many air pollutants is now a research priority of the US EPA. Bayesian hierarchical models (BHM) have been extensively used in multisite time series studies of air pollution and health to estimate health effects of a single pollutant adjusted for potential confounding of other pollutants and other time-varying factors. However, when the scientific goal is to estimate the impacts of many pollutants jointly, a straightforward application of BHM is challenged by the need to specify a random-effect distribution on a high-dimensional vector of nuisance parameters, which often do not have an easy interpretation. In this paper we introduce a new BHM formulation, which we call "reduced BHM", aimed at analyzing clustered data sets in the presence of a large number of random effects that are not of primary scientific interest. At the first stage of the reduced BHM, we calculate the integrated likelihood of the parameter of interest (e.g. excess number of deaths attributed to simultaneous exposure to high levels of many pollutants). At the second stage, we specify a flexible random-effect distribution directly on the parameter of interest. The reduced BHM overcomes many of the challenges in the specification and implementation of full BHM in the context of a large number of nuisance parameters. In simulation studies we show that the reduced BHM performs comparably to the full BHM in many scenarios, and even performs better in some cases. Methods are applied to estimate location-specific and overall relative risks of cardiovascular hospital admissions associated with simultaneous exposure to elevated levels of particulate matter and ozone in 51 US counties during the period 1999-2005.

Oxidative stress precedes peak systemic inflammatory response in pediatric patients undergoing cardiopulmonary bypass operation

Oxidative stress seems to contribute to cardiopulmonary bypass (CPB)-related postoperative complications. Pediatric patients are particularly prone to these complications. With this in mind, we measured oxidative stress markers in blood plasma of 20 children undergoing elective heart surgery before, during, and up to 48 h after cessation of CPB, along with inflammatory parameters and full analysis of iron status. Ascorbate levels were decreased by approximately 50% (P < 0.001) at the time of aorta cross-clamp removal (or pump switch-off in 4 patients with partial CPB), and associated with corresponding increases in dehydroascorbate (P < 0.001, r = -0.80) and malondialdehyde (P < 0.01, r = -0.59). In contrast to the immediate oxidative response, peak levels of IL-6 and IL-8 were not observed until 3-12 h after CPB cessation. The early loss of ascorbate correlated with duration of CPB (P < 0.002, r = 0.72), plasma hemoglobin after cross-clamp removal (P < 0.001, r = 0.70), and IL-6 and IL-8 levels at 24 and 48 h after CPB (P < 0.01), but not with postoperative lactate levels, strongly suggesting that hemolysis, and not inflammation or ischemia, was the main cause of early oxidative stress. The correlation of ventilation time with early changes in ascorbate (P < 0.02, r = 0.55), plasma hemoglobin (P < 0.01, r = 0.60), and malondialdehyde (P < 0.02, r = 0.54) suggests that hemolysis-induced oxidative stress may be an underlying cause of CPB-associated pulmonary dysfunction. Optimization of surgical procedures or therapeutic intervention that minimize hemolysis (e.g., off-pump surgery) or the resultant oxidative stress (e.g., antioxidant treatment) should be considered as possible strategies to lower the rate of postoperative complications in pediatric CPB.

Excision of high and mid cervical spinal cord arteriovenous malformations by anterior operation

Symptomatic cervical spinal arteriovenous malformations (AVMs) located on the anterior aspect of the spinal cord are rare and surgical removal of these AVMs presents considerable challenges and risks. Surgical techniques to date have usually been by posterior approach and lateral dissection around the cord or via midline myelotomy, both approaches involving cord manipulation and retraction and in the latter, dissection through the spinal cord. We present two teenage patients with symptomatic anteriorly placed mid to high cervical spinal AVMs and associated aneurysm in which excision of the AVMs and aneurysm was performed by an anterior approach using vertebrectomy/corpectomy. The first case had a small perimedullary glomus-type AVM with an aneurysm on the anterior aspect of the cord at the C3/4 level; excision was performed using a single level vertebrectomy/corpectomy, the patient remaining neurologically intact. The second case had a medium-sized juvenile AVM with an aneurysm, both perimedullary and intramedullary, centred at the C5/6 level; excision was performed using a two-level vertebrectomy/corpectomy with no deterioration in the marked pre-operative tetraparesis, which at long-term follow up had improved and stabilised. Anterior approaches have been recently described for treatment of anteriorly placed cervical arteriovenous fistulas (AVFs) and an intramedullary haemangioblastoma, but not as yet for spinal AVMs. These are the first two reported cases of anteriorly situated cervical AVMs successfully removed surgically by an anterior approach and with good neurological outcomes.

Algorithms for autonomous tandem operation of a dual M113 system

In mid-July 2003, the U.S. Army Tank-Automotive & Armaments Command (TACOM) performed a series of experiments at Keweenaw Research Center (KRC), with a remote operated mine roller system. This system, named Panther Lite, consists of two M113 Armored Personnel Carriers (APC’s) connected by a Tandem Vehicle Linkage Assembly (TVLA). The system has three sets of mine rollers, two of which are connected to the front of the lead vehicle with one set trailing from the trail vehicle. Currently, the system requires two joystick controllers. One regulates the braking of the tracks, throttle, and transmission of the lead vehicle and the other controls the braking and throttle of the rear vehicle. One operator controls both joysticks, attempting to maneuver the lead vehicle along a desired path. At the same time, this operator makes compensation maneuvers to reduce lateral loads in the TVLA and to guide the rear mine rollers along the desired path. The purpose of this project is to create algorithms that would allow the slave (trail) vehicle to operate using inputs that maneuver the control (lead) vehicle. The project will be completed by first reconstructing the experimental data. Kinematic models will be generated and simulations created. The models will then be correlated with the reconstructions of the experimental data. The successful completion of this project will be a first step to eliminating the need for the second joystick.

"Rapid two-stage" Norwood operation in a child with multiorgan failure

The Norwood I operation continues to be a procedure with significant operative mortality. One well-accepted risk factor for death after the first step of the Norwood operation is critical preoperative status. We describe herein a new concept for the treatment of patients with hypoplastic left heart syndrome (HLHS) in very poor preoperative condition. This is a case report of a child who was born in a rural hospital. On the second day of life he was referred to our center in multiorgan failure. There were signs of liver dysfunction and the child was anuric. Therapy was started immediately with prostaglandin and vasodilators as well as diuretics, milrinone, and dobutamine. However, systemic perfusion continued to be insufficient. Finally, the child was placed on a ventilator. On the fourth day of life, bilateral pulmonary artery (PA) banding was performed and circulation stabilized immediately. Two hours after the operation urine output started. Liver function stabilized over the next couple of days. Two days after PA banding the child was weaned from the ventilator. On the 12th day of life a Norwood operation with PA debanding and a right ventricle-PA conduit was performed, and 2 days postoperatively the child was weaned from the ventilator. Twenty days after the operation he was discharged home. When the boy was 4 months old a bidirectional cavopulmonary anastomosis was performed. In selected cases of patients with HLHS with very poor hemodynamic conditions, a rapid two-stage approach with bilateral banding followed by a Norwood operation after cardiac stabilization can be recommended.