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.

If smoking increases absences, does quitting reduce them?

OBJECTIVE: This study examined the impact of smoking, quitting, and time since quit on absences from work. METHODS: Data from the nationally representative Tobacco Use Supplements of the 1992/93, 1995/96, and 1998/99 Current Population Surveys were used. The study included full time workers aged between 18-64 years, yielding a sample size of 383 778 workers. A binary indicator of absence due to sickness in the last week was analysed as a function of smoking status including time since quit for former smokers. Extensive demographic variables were included as controls in all models. RESULTS: In initial comparisons between current and former smokers, smoking increased absences, but quitting did not reduce them. However, when length of time since quit was examined, it was discovered that those who quit within the last year, and especially the last three months, had a much greater probability of absences than did current smokers. As the time since quitting increased, absences returned to a rate somewhere between that of never and current smokers. Interactions between health and smoking status significantly improved the fit of the model. CONCLUSIONS: Smokers who quit reduced their absences over time but increase their absences immediately after quitting. Quitting ill may account for some but not all of this short run impact.

Exploring the effects of image persistence in low frame rate virtual environments

© 2015 IEEE.In virtual reality applications, there is an aim to provide real time graphics which run at high refresh rates. However, there are many situations in which this is not possible due to simulation or rendering issues. When running at low frame rates, several aspects of the user experience are affected. For example, each frame is displayed for an extended period of time, causing a high persistence image artifact. The effect of this artifact is that movement may lose continuity, and the image jumps from one frame to another. In this paper, we discuss our initial exploration of the effects of high persistence frames caused by low refresh rates and compare it to high frame rates and to a technique we developed to mitigate the effects of low frame rates. In this technique, the low frame rate simulation images are displayed with low persistence by blanking out the display during the extra time such image would be displayed. In order to isolate the visual effects, we constructed a simulator for low and high persistence displays that does not affect input latency. A controlled user study comparing the three conditions for the tasks of 3D selection and navigation was conducted. Results indicate that the low persistence display technique may not negatively impact user experience or performance as compared to the high persistence case. Directions for future work on the use of low persistence displays for low frame rate situations are discussed.

Anti-hypotensive treatment and endothelin blockade synergistically antagonize exercise fatigue in rats under simulated high altitude.

Rapid ascent to high altitude causes illness and fatigue, and there is a demand for effective acute treatments to alleviate such effects. We hypothesized that increased oxygen delivery to the tissue using a combination of a hypertensive agent and an endothelin receptor A antagonist drugs would limit exercise-induced fatigue at simulated high altitude. Our data showed that the combination of 0.1 mg/kg ambrisentan with either 20 mg/kg ephedrine or 10 mg/kg methylphenidate significantly improved exercise duration in rats at simulated altitude of 4,267 m, whereas the individual compounds did not. In normoxic, anesthetized rats, ephedrine alone and in combination with ambrisentan increased heart rate, peripheral blood flow, carotid and pulmonary arterial pressures, breathing rate, and vastus lateralis muscle oxygenation, but under inspired hypoxia, only the combination treatment significantly enhanced muscle oxygenation. Our results suggest that sympathomimetic agents combined with endothelin-A receptor blockers offset altitude-induced fatigue in rats by synergistically increasing the delivery rate of oxygen to hypoxic muscle by concomitantly augmenting perfusion pressure and improving capillary conductance in the skeletal muscle. Our findings might therefore serve as a basis to develop an effective treatment to prevent high-altitude illness and fatigue in humans.

A new instrument for measuring anticoagulation-related quality of life: development and preliminary validation.

BACKGROUND: Anticoagulation can reduce quality of life, and different models of anticoagulation management might have different impacts on satisfaction with this component of medical care. Yet, to our knowledge, there are no scales measuring quality of life and satisfaction with anticoagulation that can be generalized across different models of anticoagulation management. We describe the development and preliminary validation of such an instrument - the Duke Anticoagulation Satisfaction Scale (DASS). METHODS: The DASS is a 25-item scale addressing the (a) negative impacts of anticoagulation (limitations, hassles and burdens); and (b) positive impacts of anticoagulation (confidence, reassurance, satisfaction). Each item has 7 possible responses. The DASS was administered to 262 patients currently receiving oral anticoagulation. Scales measuring generic quality of life, satisfaction with medical care, and tendency to provide socially desirable responses were also administered. Statistical analysis included assessment of item variability, internal consistency (Cronbach's alpha), scale structure (factor analysis), and correlations between the DASS and demographic variables, clinical characteristics, and scores on the above scales. A follow-up study of 105 additional patients assessed test-retest reliability. RESULTS: 220 subjects answered all items. Ceiling and floor effects were modest, and 25 of the 27 proposed items grouped into 2 factors (positive impacts, negative impacts, this latter factor being potentially subdivided into limitations versus hassles and burdens). Each factor had a high degree of internal consistency (Cronbach's alpha 0.78-0.91). The limitations and hassles factors consistently correlated with the SF-36 scales measuring generic quality of life, while the positive psychological impact scale correlated with age and time on anticoagulation. The intra-class correlation coefficient for test-retest reliability was 0.80. CONCLUSIONS: The DASS has demonstrated reasonable psychometric properties to date. Further validation is ongoing. To the degree that dissatisfaction with anticoagulation leads to decreased adherence, poorer INR control, and poor clinical outcomes, the DASS has the potential to help identify reasons for dissatisfaction (and positive satisfaction), and thus help to develop interventions to break this cycle. As an instrument designed to be applicable across multiple models of anticoagulation management, the DASS could be crucial in the scientific comparison between those models of care.