984 resultados para Medical statistics
Resumo:
Background— Cardiovascular risk estimation by novel biomarkers needs assessment in disease-free population cohorts, followed up for incident cardiovascular events, assaying the serum and plasma archived at baseline. We report results from 2 cohorts in such a continuing study.
Methods and Results— Thirty novel biomarkers from different pathophysiological pathways were evaluated in 7915 men and women of the FINRISK97 population cohort with 538 incident cardiovascular events at 10 years (fatal or nonfatal coronary or stroke events), from which a biomarker score was developed and then validated in the 2551 men of the Belfast Prospective Epidemiological Study of Myocardial Infarction (PRIME) cohort (260 events). No single biomarker consistently improved risk estimation in FINRISK97 men and FINRISK97 women and the Belfast PRIME Men cohort after allowing for confounding factors; however, the strongest associations (with hazard ratio per SD in FINRISK97 men) were found for N-terminal pro-brain natriuretic peptide (1.23), C-reactive protein (1.23), B-type natriuretic peptide (1.19), and sensitive troponin I (1.18). A biomarker score was developed from the FINRISK97 cohort with the use of regression coefficients and lasso methods, with selection of troponin I, C-reactive protein, and N-terminal pro-brain natriuretic peptide. Adding this score to a conventional risk factor model in the Belfast PRIME Men cohort validated it by improved c-statistics (P=0.004) and integrated discrimination (P<0.0001) and led to significant reclassification of individuals into risk categories (P=0.0008).
Conclusions— The addition of a biomarker score including N-terminal pro-brain natriuretic peptide, C-reactive protein, and sensitive troponin I to a conventional risk model improved 10-year risk estimation for cardiovascular events in 2 middle-aged European populations. Further validation is needed in other populations and age groups.
Resumo:
Silicone elastomer systems have been shown to offer potential for the fabrication of medical devices and sustained release drug delivery devices comprising low molecular weight drugs and protein therapeutics. For drug delivery systems in particular, there is often no clear rationale for selection of the silicone elastomer grade, particularly in respect of optimizing the manufacturing conditions to ensure thermal stability of the active agent and short cycle times. In this study, the cure characteristics of a range of addition-cure and condensation-cure, low-consistency, implant-grade silicone elastomers, either as supplied or loaded with the model protein bovine serum albumin (BSA) and the model hydrophilic excipient glycine, were investigated using oscillatory rheology with a view to better understanding the isothermal cure characteristics. The results demonstrate the influence of elastomer type, cure temperature, protein loading, and glycine loading on isothermal cure properties. By measuring the cure time required to achieve tan delta values representative of early and late-stage cure conditions, a ratio t(1)/t(2) was defined that allowed the cure characteristics of the various systems to be compared. Sustained in vitro release of BSA from glycine-loaded silicone elastomer covered rod devices was also demonstrated over 14 days. (C) 2010 Wiley Periodicals, Inc. J Appl Polym Sci 116: 2320-2327, 2010
Resumo:
In the past few decades, Coxian phase-type distributions have become increasingly more popular as a means of representing survival times. In healthcare, they are considered suitable for modelling the length of stay of patients in hospital and more recently for modelling the patient waiting times in Accident and Emergency Departments. The Coxian phase-type distribution has not only been shown to provide a good representation of real survival data, but its interpretation seems reasonably initiative to the medical experts. The drawback, however, is fitting the distribution to the data. There have been many attempts at accurately estimating the Coxian phase-type parameters. This paper wishes to examine the most promising of the approaches reported in the literature to determine the most accurate. Three performance measures are introduced to assess the fitting process of the algorithms along with the likelihood values and AIC to examine the goodness of fit and complexity of the model. Previous research suggests that the fitting process is strongly influenced by the initial parameter estimates and the data itself being quite variable. To overcome this, one experiment in this research paper will use the same initial parameter values for each estimation and perform the fits on the data simulated from a Coxian phase-type distribution with known parameters.
