Time-dependent analysis of length of stay and mortality due urinary tract infections in ten developing countries : INICC findings

Catheter associated urinary tract infections (CAUTI) are a worldwide problem that may lead to increased patient morbidity, cost and mortality.1e3 The literature is divided on whether there are real effects from CAUTI on length of stay or mortality. Platt4 found the costs and mortality risks to be largeyetGraves et al found the opposite.5 A reviewof the published estimates of the extra length of stay showed results between zero and 30 days.6 The differences in estimates may have been caused by the different epidemiological methods applied. Accurately estimating the effects of CAUTI is difficult because it is a time-dependent exposure. This means that standard statistical techniques, such asmatched case-control studies, tend to overestimate the increased hospital stay and mortality risk due to infection. The aim of the study was to estimate excess length of stay andmortality in an intensive care unit (ICU) due to a CAUTI, using a statistical model that accounts for the timing of infection. Data collected from ICU units in lower and middle income countries were used for this analysis.7,8 There has been little research for these settings, hence the need for this paper.

Using a longitudinal model to estimate the effect of methicillin-resistant staphylococcus aureus infection on length of stay in an intensive care unit

Healthcare-associated methicillin-resistant Staphylococcus aureus(MRSA) infection may cause increased hospital stay or, sometimes, death. Quantifying this effect is complicated because it is a time-dependent exposure: infection may prolong hospital stay, while longer stays increase the risk of infection. We overcome these problems by using a multinomial longitudinal model for estimating the daily probability of death and discharge. We then extend the basic model to estimate how the effect of MRSA infection varies over time, and to quantify the number of excess ICU days due to infection. We find that infection decreases the relative risk of discharge (relative risk ratio = 0.68, 95% credible interval: 0.54, 0.82), but is only indirectly associated with increased mortality. An infection on the first day of admission resulted in a mean extra stay of 0.3 days (95% CI: 0.1, 0.5) for a patient with an APACHE II score of 10, and 1.2 days (95% CI: 0.5, 2.0) for a patient with an APACHE II score of 30. The decrease in the relative risk of discharge remained fairly constant with day of MRSA infection, but was slightly stronger closer to the start of infection. These results confirm the importance of MRSA infection in increasing ICU stay, but suggest that previous work may have systematically overestimated the effect size.

A fully Bayesian approach to inference for Coxian phase-type distributions with covariate dependent mean

Phase-type distributions represent the time to absorption for a finite state Markov chain in continuous time, generalising the exponential distribution and providing a flexible and useful modelling tool. We present a new reversible jump Markov chain Monte Carlo scheme for performing a fully Bayesian analysis of the popular Coxian subclass of phase-type models; the convenient Coxian representation involves fewer parameters than a more general phase-type model. The key novelty of our approach is that we model covariate dependence in the mean whilst using the Coxian phase-type model as a very general residual distribution. Such incorporation of covariates into the model has not previously been attempted in the Bayesian literature. A further novelty is that we also propose a reversible jump scheme for investigating structural changes to the model brought about by the introduction of Erlang phases. Our approach addresses more questions of inference than previous Bayesian treatments of this model and is automatic in nature. We analyse an example dataset comprising lengths of hospital stays of a sample of patients collected from two Australian hospitals to produce a model for a patient's expected length of stay which incorporates the effects of several covariates. This leads to interesting conclusions about what contributes to length of hospital stay with implications for hospital planning. We compare our results with an alternative classical analysis of these data.

Scale-dependent fracture mode in Cu-Ni laminate composites

Fracture behavior of Cu-Ni laminate composites has been investigated by tensile testing. It was found that as the individual layer thickness decreases from 100 to 20nm, the resultant fracture angle of the Cu-Ni laminate changes from 72 degrees to 50 degrees. Cross-sectional observations reveal that the fracture of the Ni layers transforms from opening to shear mode as the layer thickness decreases while that of the Cu layers keeps shear mode. Competition mechanisms were proposed to understand the variation in fracture mode of the metallic laminate composites associated with length scale.

Half metallicity in finite-length zigzag single walled carbon nanotube : A first-principle prediction

We predict here from first-principle calculations that finite-length (n,0) single walled carbon nanotubes (SWCNTs) with H-termination at the open ends displaying antiferromagnetic coupling when n is greater than 6. An opposite local gating effect of the spin states, i.e., half metallicity, is found under the influence of an external electric field along the direction of tube axis. Remarkably, boron doping of unpassivated SWCNTs at both zigzag edges is found to favor a ferromagnetic ground state, with the B-doped tubes displaying half-metallic behavior even in the absence of an electric field. Aside of the intrinsic interest of these results, an important avenue for development of CNT-based spintronic is suggested.

MT1-MMP-dependent and -independent regulation of gelatinase A activation in long-term, ascorbate-treated fibroblast cultures: Regulation by fibrillar collagen

Human skin fibroblasts were cultured long-term in the presence of ascorbic acid to allow formation of a three-dimensional collagen matrix, and the effects of this on activation of secreted matrix metalloproteinase-2 (MMP-2) were examined. Accumulation of collagen over time correlated with increased levels of both mature MMP-2 and cell-associated membrane type 1-MMP (MT1-MMP), and subsequently increased mRNA levels for MT1-MMP, providing temporal resolution of the "nontranscriptional" and "transcriptional" effects of collagen on MT-1MMP functionality. MMP-2 activation by these cultures was blocked by inhibitors of prolyl-4-hydroxylase, or when fibroblasts derived from the collagen α1(I) gene-deficient Mov-13 mouse were used. MMP-2 activation by the Mov-13 fibroblasts was rescued by transfection of a full-length α1(I) collagen cDNA, and to our surprise, also by transfection with an α1(I) collagen cDNA carrying a mutation at the C-proteinase cleavage, which almost abrogated fibrillogenesis. Although studies with ascorbate-cultured MT1-MMP-/- fibroblasts showed that MT1-MMP played a significant role in the collagen-induced MMP-2 activation, a residual MT1-MMP-independent activation of MMP-2 was seen which resembled the level of MMP-2 activation persisting when wild-type fibroblasts were cultured in the presence of both ascorbic acid and MMP inhibitors. We were also unable to block this residual activation with inhibitors specific for serinyl, aspartyl, or cysteinyl enzymes.

Survival models of community tenure and length of hospital stay for the seriously mentally ill : a 10-year perspective

Objective: To examine the effects of personal and community characteristics, specifically race and rurality, on lengths of state psychiatric hospital and community stays using maximum likelihood survival analysis with a special emphasis on change over a ten year period of time. Data Sources: We used the administrative data of the Virginia Department of Mental Health, Mental Retardation, and Substance Abuse Services (DMHMRSAS) from 1982-1991 and the Area Resources File (ARF). Given these two sources, we constructed a history file for each individual who entered the state psychiatric system over the ten year period. Histories included demographic, treatment, and community characteristics. Study Design: We used a longitudinal, population-based design with maximum likelihood estimation of survival models. We presented a random effects model with unobserved heterogeneity that was independent of observed covariates. The key dependent variables were lengths of inpatient stay and subsequent length of community stay. Explanatory variables measured personal, diagnostic, and community characteristics, as well as controls for calendar time. Data Collection: This study used secondary, administrative, and health planning data. Principal Findings: African-American clients leave the community more quickly than whites. After controlling for other characteristics, however, race does not affect hospital length of stay. Rurality does not affect length of community stays once other personal and community characteristics are controlled for. However, people from rural areas have longer hospital stays even after controlling for personal and community characteristics. The effects of time are significantly smaller than expected. Diagnostic composition effects and a decrease in the rate of first inpatient admissions explain part of this reduced impact of time. We also find strong evidence for the existence of unobserved heterogeneity in both types of stays and adjust for this in our final models. Conclusions: Our results show that information on client characteristics available from inpatient stay records is useful in predicting not only the length of inpatient stay but also the length of the subsequent community stay. This information can be used to target increased discharge planning for those at risk of more rapid readmission to inpatient care. Correlation across observed and unobserved factors affecting length of stay has significant effects on the measurement of relationships between individual factors and lengths of stay. Thus, it is important to control for both observed and unobserved factors in estimation.

Structure- and composition-dependent electron field emission from nitrogenated carbon nanotips

The electron field emission (EFE) properties of nitrogenated carbon nanotips (NCNTPs) were studied under high-vacuum conditions. The NCNTPs were prepared in a plasma-assisted hot filament chemical vapor deposition system using CH4 and N2 as the carbon and nitrogen sources, respectively. The work functions of NCNTPs were measured using x-ray photoelectron spectroscopy. The morphological and structural properties of NCNTPs were studied by field emission scanning electron microscopy, micro-Raman spectroscopy, and x-ray photoelectron spectroscopy. The field enhancement factors of NCNTPs were calculated using relevant EFE models based on the Fowler-Nordheim approximation. Analytical characterization and modeling results were used to establish the relations between the EFE properties of NCNTPs and their morphology, structure, and composition. It is shown that the EFE properties of NCNTPs can be enhanced by the reduction of oxygen termination on the surface as well as by increasing the ratio of the NCNTP height to the radius of curvature at its top. These results also suggest that a significant amount of electrons is emitted from other surface areas besides the NCNTP tops, contrary to the common belief. The outcomes of this study advance our knowledge on the electron emission properties of carbonnanomaterials and contribute to the development of the next-generation of advanced applications in the fields of micro- and opto-electronics.

Temperature-dependent properties of nc-Si thin films synthesized in low-pressure, thermally nonequilibrium, high-density inductively coupled plasmas

Silicon thin films were synthesized simultaneously on single-crystal silicon and glass substrates by lowpressure, thermally nonequilibrium, high-density inductively coupled plasma-assisted chemical vapor deposition from the silane precursor gas without any additional hydrogen dilution in a broad range of substrate temperatures from 100 to 500 °C. The effect of the substrate temperature on the morphological, structural and optical properties of the synthesized silicon thin films is systematically studied by X-ray diffractometry, Raman spectroscopy, UV-vis spectroscopy, and scanning electron microscopy. It is shown that the formation of nanocrystalline silicon (nc-Si) occurs when the substrate temperature is higher than 200 °C and that all the deposited nc-Si films have a preferential growth along the (111) direction. However, the mean grain size of the (111) orientation slightly and gradually decreases while the mean grain size of the (220) orientation shows a monotonous increase with the increased substrate temperature from 200 to 500 °C. It is also found that the crystal volume fraction of the synthesized nc-Si thin films has a maximum value of ∼69.1% at a substrate temperature of 300 rather than 500 °C. This rather unexpected result is interpreted through the interplay of thermokinetic surface diffusion and hydrogen termination effects. Furthermore, we have also shown that with the increased substrate temperature from 100 to 500 °C, the optical bandgap is reduced while the growth rates tend to increase. The maximum rates of change of the optical bandgap and the growth rates occur when the substrate temperature is increased from 400 to 500 °C. These results are highly relevant to the development of photovoltaic thin-film solar cells, thin-film transistors, and flat-panel displays.

Thermodynamical and plasma-driven kinetic growth of high-aspect-ratio nanostructures : effect of hydrogen termination

The results of studies on the growth of high-aspect nanostructures in low-temperature non-equilibrium plasmas of reactive gas mixtures with or without hydrogen are presented. The results suggest that the hydrogen in the reactive plasma strongly affects the length of the nanostructures. This phenomenon is explained in terms of selective hydrogen passivation of the lateral and top surfaces of the surface-supported nanostructures. The theoretical model describes the effect of the atomic hydrogen passivation on the nanostructure shape and predicts the critical hydrogen coverage of the lateral surfaces necessary to achieve the nanostructure growth with the pre-determined shape. Our results demonstrate that the use of a strongly non-equilibrium plasma is very effective in significantly improving the shape control of quasi-one-dimensional single-crystalline nanostructures.

The prolongation of length of stay because of Clostridium difficile infection

Background Clostridium difficile infection (CDI) possibly extends hospital length of stay (LOS); however, the current evidence does not account for the time-dependent bias, ie, when infection is incorrectly analyzed as a baseline covariate. The aim of this study was to determine whether CDI increases LOS after managing this bias. Methods We examined the estimated extra LOS because of CDI using a multistate model. Data from all persons hospitalized >48 hours over 4 years in a tertiary hospital in Australia were analyzed. Persons with health care-associated CDIs were identified. Cox proportional hazards models were applied together with multistate modeling. Results One hundred fifty-eight of 58,942 admissions examined had CDI. The mean extra LOS because of infection was 0.9 days (95% confidence interval: −1.8 to 3.6 days, P = .51) when a multistate model was applied. The hazard of discharge was lower in persons who had CDI (adjusted hazard ratio, 0.42; P < .001) when a Cox proportional hazard model was applied. Conclusion This study is the first to use multistate models to determine the extra LOS because of CDI. Results suggest CDI does not significantly contribute to hospital LOS, contradicting findings published elsewhere. Conversely, when methods prone to result in time-dependent bias were applied to the data, the hazard of discharge significantly increased. These findings contribute to discussion on methods used to evaluate LOS and health care-associated infections.

Growth curves with time-dependent explanatory variables

A class of growth models incorporating time-dependent factors and stochastic perturbations are introduced. The proposed model includes the existing growth models used in fisheries as special cases. Particular attention is given to growth of a population (in average weight or length) from which observations are taken randomly each time and the analysis of tag-recapture data. Two real data sets are used for illustration: (a) to estimate the seasonal effect and population density effect on growth of farmed prawn (Penaeus monodon) from weight data and (b) to assess the effect of tagging on growth of barramundi (Lates calcarifer)

Size-dependent natural mortality of juvenile banana prawns Penaeus merguiensis in the Gulf of Carpentaria, Australia

Natural mortality of marine invertebrates is often very high in the early life history stages and decreases in later stages. The possible size-dependent mortality of juvenile banana prawns, P. merguiensis (2-15 mm carapace length) in the Gulf of Carpentaria was investigated. The analysis was based on the data collected at 2-weekly intervals by beam trawls at four sites over a period of six years (between September 1986 and March 1992). It was assumed that mortality was a parametric function of size, rather than a constant. Another complication in estimating mortality for juvenile banana prawns is that a significant proportion of the population emigrates from the study area each year. This effect was accounted for by incorporating the size-frequency pattern of the emigrants in the analysis. Both the extra parameter in the model required to describe the size dependence of mortality, and that used to account for emigration were found to be significantly different from zero, and the instantaneous mortality rate declined from 0.89 week(-1) for 2 mm prawns to 0.02 week(-1) for 15 mm prawns.