Parametric conditional frailty models for recurrent cardiovascular events in the lipid study

Background Analysis of recurrent event data is frequently needed in clinical and epidemiological studies. An important issue in such analysis is how to account for the dependence of the events in an individual and any unobserved heterogeneity of the event propensity across individuals.Methods We applied a number of conditional frailty and nonfrailty models in an analysis involving recurrent myocardial infarction events in the Long-Term Intervention with Pravastatin in Ischaemic Disease study. A multiple variable risk prediction model was developed for both males and females. Results A Weibull model with a gamma frailty term fitted the data better than other frailty models for each gender. Among nonfrailty models the stratified survival model fitted the data best for each gender. The relative risk estimated by the elapsed time model was close to that estimated by the gap time model. We found that a cholesterol-lowering drug, pravastatin (the intervention being tested in the trial) had significant protective effect against the occurrence of myocardial infarction in men (HR¼0.71, 95% CI0.60–0.83). However, the treatment effect was not significant in women due to smaller sample size (HR¼0.75, 95% CI 0.51–1.10). There were no significant interactions between the treatment effect and each recurrent MI event (p¼0.24 for men and p¼0.55 for women). The risk of developing an MI event for a male who had an MI event during follow-up was about 3.4 (95% CI 2.6–4.4) times the risk compared with those who did not have an MI event. The corresponding relative risk for a female was about 7.8 (95% CI 4.4–13.6). Limitations The number of female patients was relatively small compared with their male counterparts, which may result in low statistical power to find real differences in the effect of treatment and other potential risk factors.Conclusions The conditional frailty model suggested that after accounting for all the risk factors in the model, there was still unmeasured heterogeneity of the risk for myocardial infarction, indicating the effect of subject-specific risk factors. These risk prediction models can be used to classify cardiovascular disease patients into different risk categories and may be useful for the most effective targeting of preventive therapies for cardiovascular disease.

Pro-oxidative synergic bactericidal effect of NO: kinetics and inhibition by nitroxides

NO plays diverse roles in physiological and pathological processes, occasionally resulting in opposing effects, particularly in cells subjected to oxidative stress. NO mostly protects eukaryotes against oxidative injury, but was demonstrated to kill prokaryotes synergistically with H2O2. This could be a promising therapeutic avenue. However, recent conflicting findings were reported describing dramatic protective activity of NO. The previous studies of NO effects on prokaryotes applied a transient oxidative stress while arbitrarily checking the residual bacterial viability after 30 or 60min and ignoring the process kinetics. If NO-induced synergy and the oxidative stress are time-dependent, the elucidation of the cell killing kinetics is essential, particularly for survival curves exhibiting a "shoulder" sometimes reflecting sublethal damage as in the linear-quadratic survival models. We studied the kinetics of NO synergic effects on H2O2-induced killing of microbial pathogens. A synergic pro-oxidative activity toward gram-negative and gram-positive cells is demonstrated even at sub-μM/min flux of NO. For certain strains, the synergic effect progressively increased with the duration of cell exposure, and the linear-quadratic survival model best fit the observed survival data. In contrast to the failure of SOD to affect the bactericidal process, nitroxide SOD mimics abrogated the pro-oxidative synergy of NO/H2O2. These cell-permeative antioxidants, which hardly react with diamagnetic species and react neither with NO nor with H2O2, can detoxify redox-active transition metals and catalytically remove intracellular superoxide and nitrogen-derived reactive species such as (•)NO2 or peroxynitrite. The possible mechanism underlying the bactericidal NO synergy under oxidative stress and the potential therapeutic gain are discussed.

Determining the sensitivity of the Antarctic amphipod Orchomenella pinguides to metals using a joint model of survival response to exposure concentration and duration

Developing water quality guidelines for Antarctic marine environments requires understanding the sensitivity of local biota to contaminant exposure. Antarctic invertebrates have shown slower contaminant responses in previous experiments compared to temperate and tropical species in standard toxicity tests. Consequently, test methods which take into account environmental conditions and biological characteristics of cold climate species need to be developed. This study investigated the effects of five metals on the survival of a common Antarctic amphipod, Orchomenella pinguides. Multiple observations assessing mortality to metal exposure were made over the 30 days exposure period. Traditional toxicity tests with quantal data sets are analysed using methods such as maximum likelihood regression (probit analysis) and Spearman–Kärber which treat individual time period endpoints independently. A new statistical model was developed to integrate the time-series concentration–response data obtained in this study. Grouped survival data were modelled using a generalized additive mixed model (GAMM) which incorporates all the data obtained from multiple observation times to derive time integrated point estimates. The sensitivity of the amphipod, O. pinguides, to metals increased with increasing exposure time. Response times varied for different metals with amphipods responding faster to copper than to cadmium, lead or zinc. As indicated by 30 days lethal concentration (LC50) estimates, copper was the most toxic metal (31 µg/L), followed by cadmium (168 µg/L), lead (256 µg/L) and zinc (822 µg/L). Nickel exposure (up to 1.12 mg/L) did not affect amphipod survival. Using longer exposure durations and utilising the GAMM model provides an improved methodology for assessing sensitivities of slow responding Antarctic marine invertebrates to contaminants.

Amalgamation of health services in South-West Victoria: reinvention or survival?

In Australia 'the hospital' has long been considered the cornerstone of small, rural health services. However, this premise has been altered significantly by the introduction of casemix loading and diagnostic-related groups that promote a rationalised output-based model of management. In the light of these changes, many rural health services have struggled to reinvent themselves by establishing a range of service models such as Multi-purpose Service (MPS) and Health Streams, while maintaining traditional models (i.e. bush nursing centres, nursing homes and aged-care facilities). These changes are about survival. This paper analyses one such case in south-west Victoria, the Macarthur and District Community Outreach Service, and compares the outcomes with other similar Victorian rural health research projects. Particular attention is paid to the nature of the health services, the management of change and the proposed health outcomes for the local rural communities. In conclusion, it is argued that this study adds to the body of knowledge surrounding the construction of models of community health and development programming, These models impact upon future rural and remote area initiatives throughout Australia.

Naturalistic decision making: a model to overcome methodological challenges in the study of critical care nurses` decision making about patients` hemodynamic status

The quality of critical care nurses' decision making about patients' hemodynamic status in the immediate period after cardiac surgery is important for the patients' well-being and, at times, survival. The way nurses respond to hemodynamic cues varies according to the nurses' skills, experiences, and knowledge. Variability in decisions is also associated with the inherent complexity of hemodynamic monitoring. Previous methodological approaches to the study of hemodynamic assessment and treatment decisions have ignored the important interplay between nurses, the task, and the environment in which these decisions are made. The advantages of naturalistic decision making as a framework for studying the manner in which nurses make decisions are presented.

Use of in vitro critical inhibitory concentration, a novel approach to predict in vivo synergistic bactericidal effect of combined amikacin and piperacillin against pseudomonas aeruginosa in a systemic rat infection model

PURPOSE: This study was undertaken to explore the use of in vitro critical inhibitory concentration (CIC) as a surrogate marker relating the pharmacokinetic (PK) parameters to in vivo bactericidal synergistic effect [pharmacodynamic (PD)] of amikacin + piperacillin combination against Pseudomonas aeruginosa in a systemic rat infection model. METHODS: The in vitro antibacterial activities of amikacin and piperacillin, alone and in combinations at various ratios of the concentrations, were tested against a standard [5 x 10(5) colony-forming units (CFU)/ml] and a large (1.5 x 10(8) CFU/ml) inoculum of P. aeruginosa ATCC 9027 using a modified survival-time method. The CIC of each individual antibiotic for the different combinations was determined using a cup-plate method. In vivo studies were performed on Sprague-Dawley rats using a systemic model of infection with P. aeruginosa ATCC 9027. PK profiles and in vivo killing effects of the combination at different dosing ratios were studied. RESULTS: An inoculum effect was observed with the antibiotics studied. Synergy was seen against both the inocula at the following concentration ratios: 70% C(ami) + 30% C(pip) and 75% C(ami) + 25% C(pip), where C(ami) and C(pip) are the concentrations of amikacin and piperacillin to produce a 1000-fold decrease in bacterial population over 5 h, respectively. The CIC values determined corroborated with the order of in vitro bacterial killing observed for the antibiotic combinations. The dosing ratio of 12.6 mg/kg amikacin + 36 mg/kg piperacillin (a 70:30 ratio of the individual doses) exhibited the greatest killing in vivo when compared to the other ratios. The PK-PD relationships were described by simple, linear regression equations using the area under the in vivo killing curve as a PD marker and the AUCIC(ami)/CIC(ami) + AUCIC(pip)/CIC(pip), AUC(ami)/CIC(ami) + AUC(pip)/CIC(pip), C(max,ami)/CIC(ami) + C(max,pip)/CIC(pip), and AUCIC(ami)/MIC(ami) + AUCIC(pip)/MIC(pip) as PK markers for the amikacin + piperacillin combination. CONCLUSION: The combination of amikacin and piperacillin exhibited synergistic killing effect on P. aeruginosa that could be modeled using CIC as a surrogate marker relating the PK parameters to in vivo bactericidal effect.

Firm survival through a crisis : the influence of market orientation, marketing innovation and business strategy

As an outcome of the economic crisis, the global manufacturing sector is collapsing. Focusing on Chinese manufacturing small and medium enterprises (SMEs), this study investigates whether marketing innovation, defined as improvements in the marketing mix, can assist in withstanding the challenges of operating under the current economic conditions. A conceptual model linking market orientation, marketing innovation, competitive advantage and firm survival is tested using structural equation modelling. Three key findings are derived. First, the examined Chinese manufacturing SMEs had a greater perceived likelihood of survival had they developed and sustained a competitive advantage. Second, marketing innovation assisted in developing and sustaining competitive advantages based on differentiation and cost leadership strategies. Third, marketing innovation capabilities improved when the examined manufacturing SMEs were competitor oriented and had good inter-functional capabilities.

Estimating survival and movements using both live and dead recoveries : a case study of oystercatchers confronted with habitat change

1. Animals facing partial habitat loss can try to survive in the remaining habitat or emigrate. Effects on survival and movements should be studied simultaneously since survival rates may be underestimated if emigrants are not considered, and since emigrants may experience reduced survival.

2. We analysed movements and survival of adult wintering oystercatcher Haematopus ostralegus in response to the 1986–1987 partial closure of the Oosterschelde in the Dutch Delta. This reduced by one-third the tidal area of this major European wintering area for waders.

3. We developed a novel variant of a multistate capture–recapture model allowing simultaneous estimation of survival and movement between sites using a mixture of data (live recaptures and dead recoveries). We used a two-step process, first estimating movements between sites followed by site-specific survival rates.

4. Most birds were faithful to their ringing site. Winter survival was negatively affected by winter severity and was lowest among birds changing wintering site (i.e. moving outside of the Oosterschelde).

5. During mild winters, survival rates were very high, and similar to before the closure in both changed and unchanged sectors of the Oosterschelde. However, the combined effect of habitat loss with severe winters decreased the survival of birds from changed sectors and induced emigration.

6. The coastal engineering project coincided with three severe winters and high food stock, making assessment of its effects difficult. However, the habitat loss seems to have had less impact on adult survival and movements than did winter severity.

7. Synthesis and applications. Human-induced habitat change may result in population decline through costly emigration or reduced survival or reproduction of individuals that stay. Long-term monitoring of marked individuals helps to understand how populations respond to environmental change, but site-specific survival and movement rates should be integrated in the same model in order to maximize the information yield. Our modelling approach facilitates this because it allows the inclusion of recoveries from outside the study area.

Mortality disparities between geographic regions : results from a risk percentiles model for coronary heart disease

Background: Planning of disease prevention strategies requires information regarding the distribution of absolute risk in the population to allow targeting of people at high disease risk. It is well known that death rates from coronary heart disease (CHD) are higher in remote areas of Australia compared with major cities. Less well understood is the distribution of the absolute risk of CHD death within the different geographic regions. We present a mathematical model of CHD which projects the lifetime risk of death among individuals in different percentiles of CHD risk. We apply this to model the distribution of CHD risk within different geographic regions.

Methods: Using information from the Framingham1, MRFIT2 and AusDiab3 studies, the Australian population was divided into percentiles of CHD risk within age and gender groups by geographic location. Absolute mortality risk was determined at each percentile using current Australian mortality data. Survival curves were generated for each percentile using these risk estimates. Approximate confidence intervals were derived using bootstrap methods.

Conclusions: The difference in life expectancy at age 25 between those in the lowest decile of CHD risk compared to the highest was 5.8 years (95%CI:4.7,6.7) in major cities compared to 8.5 years (95%CI:7.6,9.7) in remote areas. The difference in risk of premature death (before age 75) was 12% (95%CI:10%,14%) in major cities compared to 33% (95%CI:28%,38%) in remote areas.

Multifaceted role of nitric oxide in an in vitro mouse neuronal injury model: transcriptomic profiling defines the temporal recruitment of death signalling cascades

Nitric oxide is implicated in the pathogenesis of various neuropathologies characterized by oxidative stress. Although nitric oxide has been reported to be involved in the exacerbation of oxidative stress observed in several neuropathologies, existent data fail to provide a holistic description of how nitrergic pathobiology elicits neuronal injury. Here we provide a comprehensive description of mechanisms contributing to nitric oxide induced neuronal injury by global transcriptomic profiling. Microarray analyses were undertaken on RNA from murine primary cortical neurons treated with the nitric oxide generator DETA-NONOate (NOC-18, 0.5 mM) for 8–24 hrs. Biological pathway analysis focused upon 3672 gene probes which demonstrated at least a ±1.5-fold expression in a minimum of one out of three time-points and passed statistical analysis (one-way anova, P < 0.05). Numerous enriched processes potentially determining nitric oxide mediated neuronal injury were identified from the transcriptomic profile: cell death, developmental growth and survival, cell cycle, calcium ion homeostasis, endoplasmic reticulum stress, oxidative stress, mitochondrial homeostasis, ubiquitin-mediated proteolysis, and GSH and nitric oxide metabolism. Our detailed time-course study of nitric oxide induced neuronal injury allowed us to provide the first time a holistic description of the temporal sequence of cellular events contributing to nitrergic injury. These data form a foundation for the development of screening platforms and define targets for intervention in nitric oxide neuropathologies where nitric oxide mediated injury is causative.

Survival misperception, time inconsistency, and implications for life-cycle saving and welfare

Some empirical studies firmly reveal that people tend to form overly pessimistic survival expectations for relatively less distant ages and overly optimistic survival expectations for relatively more distant ages. We incorporate this observation into a life-cycle continuous time overlapping-generations model of consumption/saving with a general form for a subjective survival function. Resulting time-inconsistent optimal control problem has been analytically solved. At the micro level, time inconsistency leads to higher consumption at young and old ages, but this alone fails to improve lifetime well-being since micro-level decisions made with a lack of information about true mortality are suboptimal. In general equilibrium, however, such time inconsistent behavior with survival misperception is conducive to aggregate capital accumulation and greater equilibrium bequest income. The latter effects can produce substantial welfare gains. We also note that empirically observed old age optimistic bias is an important phenomenon, as it helps to avoid unrealistic very old-age debt accumulation within a life-cycle model. In addition, if for a given level of optimistic bias we increase early-life pessimism, this would result in slower capital accumulation, lower bequest income, and thus be detrimental to welfare. Since recent literature reports that young-age survival pessimism has grown over time, it raises some concerns.

Survival analysis of time-to-event data in respiratory health research studies

This article provides a review of techniques for the analysis of survival data arising from respiratory health studies. Popular techniques such as the Kaplan–Meier survival plot and the Cox proportional hazards model are presented and illustrated using data from a lung cancer study. Advanced issues are also discussed, including parametric proportional hazards models, accelerated failure time models, time-varying explanatory variables, simultaneous analysis of multiple types of outcome events and the restricted mean survival time, a novel measure of the effect of treatment.

The resurrection plant Sporobolus stapfianus: An unlikely model for engineering enhanced plant biomass?

The resurrection grass Sporobolus stapfianus Gandoger can rapidly recover from extended periods of time in the desiccated state (water potential equilibrated to 2% relative humidity) (Gaff and Ellis, Bothalia 11:305–308 1974; Gaff and Loveys, Transactions of the Malaysian Society of Plant Physiology 3:286–287 1993). Physiological studies have been conducted in S. stapfianus to investigate the responses utilised by these desiccation-tolerant plants to cope with severe water-deficit. In a number of instances, more recent gene expression analyses in S. stapfianus have shed light on the molecular and cellular mechanisms mediating these responses. S. stapfianus is a versatile research tool for investigating desiccation-tolerance in vegetative grass tissue, with several useful characteristics for differentiating desiccation-tolerance adaptive genes from the many dehydration-responsive genes present in plants. A number of genes orthologous to those isolated from dehydrating S. stapfianus have been successfully used to enhance drought and salt tolerance in model plants as well as important crop species. In addition to the ability to desiccate and rehydrate successfully, the survival of resurrection plants in regions experiencing short sporadic rainfall events may depend substantially on the ability to tightly down-regulate cell division and cell wall loosening activities with decreasing water availability and then grow rapidly after rainfall while water is plentiful. Hence, an analysis of gene transcripts present in the desiccated tissue of resurrection plants may reveal important growth-related genes. Recent findings support the proposition that, as well as being a versatile model for devising strategies for protecting plants from water-loss, resurrection plants may be a very useful tool for pinpointing genes to target for enhancing growth rate and biomass production.

Machine-learning prediction of cancer survival: a retrospective study using electronic administrative records and a cancer registry

Using the prediction of cancer outcome as a model, we have tested the hypothesis that through analysing routinely collected digital data contained in an electronic administrative record (EAR), using machine-learning techniques, we could enhance conventional methods in predicting clinical outcomes.

Modelling grouped survival times in toxicological studies using generalized additive models

A method for combining a proportional-hazards survival time model with a bioassay model where the log-hazard function is modelled as a linear or smoothing spline function of log-concentration combined with a smoothing spline function of time is described. The combined model is fitted to mortality numbers, resulting from survival times that are grouped due to a common set of observation times, using Generalized Additive Models (GAMs). The GAM fits mortalities as conditional binomials using an approximation to the log of the integral of the hazard function and is implemented using freely-available, general software for fitting GAMs. Extensions of the GAM are described to allow random effects to be fitted and to allow for time-varying concentrations by replacing time with a calibrated cumulative exposure variable with calibration parameter estimated using profile likelihood. The models are demonstrated using data from a studies of a marine and a, previously published, freshwater taxa. The marine study involved two replicate bioassays of the effect of zinc exposure on survival of an Antarctic amphipod, Orchomenella pinguides. The other example modelled survival of the daphnid, Daphnia magna, exposed to potassium dichromate and was fitted by both the GAM and the process-based DEBtox model. The GAM fitted with a cubic regression spline in time gave a 61 % improvement in fit to the daphnid data compared to DEBtox due to a non-monotonic hazard function. A simulation study using each of these hazard functions as operating models demonstrated that the GAM is overall more accurate in recovering lethal concentration values across the range of forms of the underlying hazard function compared to DEBtox and standard multiple endpoint probit analyses.