Alessandro Baldi Antognini

Sleep disturbance and daytime sleepiness in patients with cirrhosis: a case control study

Sleep disturbance and excessive daytime sleepiness have been reported in patients with hepatic cirrhosis. The objective of this study was to evaluate daytime somnolence and sleep complaints in a group of 178 patients with cirrhosis compared to a control group. Sleep features and excessive daytime sleepiness were evaluated by the Basic Nordic Sleep Questionnaire (BNSQ) and the Epworth Sleepiness Scale (ESS). We collected clinical and laboratory data, neurological assessment and EEG recordings in cirrhotic patients. Patients with cirrhosis complained of more daytime sleepiness (p<0.005), sleeping badly at least three times a week (p<0.005), difficulties falling asleep (p<0.01) and frequent nocturnal awakening (p<0.005) than controls. We found a poor correlation between sleep disorders and clinical or laboratory parameters. Our results confirm previous literature reports suggesting a high prevalence of sleep disturbance in patients with cirrhosis. Insomnia and daytime sleepiness are the main complaints. Sleep disorders are probably a multifactorial phenomenon.

Covariate Adjusted Designs for Combining Efficiency, Ethics and Randomness in Normal Response Trials

This paper deals with the problem of allocating patients to two competing treatments in the presence of covariates in order to achieve a good trade-off between efficiency, ethical concern and randomization. We propose a compound criterion that combines inferential precision and ethical gain by flexible weights depending on the unknown treatment effects. In the absence of treatment-covariate interactions, this criterion leads to a locally optimal allocation which does not depend on the covariates and can be targeted by a suitable implementation of the doubly-adaptive biased coin design aimed at balancing the roles of randomization, ethics and information. Some properties of the suggested procedure are described.

Computer Simulations for the Optimization of Technological Processes

This chapter is about experiments for quality improvement and the innovation of products and processes performed by computer simulation. It describes familiar methods for creating surrogate models of simulators (emulators), with particular reference to Kriging interpolation, and some new ways of fitting the models to the simulated data.

Survival of Dialysis Patients with Restless Legs Syndrome: A 15-Year Follow-Up Study

Background: Restless legs syndrome, also known as Willis/Ekbom disease (RLS/WED), is a sleep-related, sensorimotor disorder with a high prevalence among end-stage renal disease (ESRD) patients undergoing haemodialysis (HD) (about 15-40%). Whether RLS/WED in uremic patients influences cardiovascular morbidity and mortality remains a matter of controversy. The aim of this study was to evaluate the relationship of RLS/WED and mortality in a population of chronically dialyzed patients. Method: In 1996, we studied 128 patients with ESRD undergoing HD; 47 subjects (36.7%) complained RLS/WED symptoms. Fifteen years later we evaluated the mortality of this population. No clinical follow-up examination of the uremic population was made. The Kaplan-Maier curves in dialysis patients with or without RLS/WED (control group matched for age) were constructed for all-cause mortality and compared using log-rank test. Results: The Kaplan-Maier curves disclosed a lower mortality rate in the uremic patients with RLS/WED than in those without RLS/WED (p = 0.04). In our analysis, the mortality rate was not influenced by RLS/WED severity (p = 0.11) or gender (p = 0.15). No difference among the causes of death was found in the 2 groups. Conclusions: Our study suggests that mortality in ESRD patients is not influenced by concomitant RLS/WED. After a 15-year follow-up, survival rates in our cohort were significantly longer in uremic subjects with RLS/WED than in those without RLS/WED. Finally, we found no relationship between RLS/WED severity and mortality.

Space filling and locally optimal designs for Gaussian Universal Kriging

Computer simulations are often used to replace physical experiments aimed at exploring the complex relationships between input and output variables. Undoubtedly, computer experiments have several advantages over real ones, however, when the response function is complex, simulation runs may be very expensive and/or time-consuming, and a possible solution consists of approximating the simulator by a suitable stochastic metamodel, simpler and much faster to run. Several metamodel techniques have been suggested in the literature and one of the most popular is the Kriging methodology. In this paperwe study the optimal design problem for the Universal Kriging metamodel with respect to different approaches, related to prediction, information gain and estimation. Also we give further justifications and some criticism concerning the adoption of the space filling designs, based on theoretical results and numerical evidence as well.