The association of chronic kidney disease and dialysis treatment with foot ulceration and major amputation

Objective The objective of this study was to investigate the risk of chronic kidney disease (CKD) stage 4-5 and dialysis treatment on incidence of foot ulceration and major lower extremity amputation in comparison to CKD stage 3. Methods In this retrospective study, all individuals who visited our hospital between 2006 and 2012 because of CKD stages 3 to 5 or dialysis treatment were included. Medical records were reviewed for incidence of foot ulceration and major amputation. The time from CKD 3, CKD 4-5, and dialysis treatment until first foot ulceration and first major lower extremity amputation was calculated and analyzed by Kaplan-Meier curves and multivariate Cox proportional hazards model. Diabetes mellitus, peripheral arterial disease, peripheral neuropathy, and foot deformities were included for potential confounding. Results A total of 669 individuals were included: 539 in CKD 3, 540 in CKD 4-5, and 259 in dialysis treatment (individuals could progress from one group to the next). Unadjusted foot ulcer incidence rates per 1000 patients per year were 12 for CKD 3, 47 for CKD 4-5, and 104 for dialysis (P < .001). In multivariate analyses, the hazard ratio for incidence of foot ulceration was 4.0 (95% confidence interval [CI], 2.6-6.3) in CKD 4-5 and 7.6 (95% CI, 4.8-12.1) in dialysis treatment compared with CKD 3. Hazard ratios for incidence of major amputation were 9.5 (95% CI, 2.1-43.0) and 15 (95% CI, 3.3-71.0), respectively. Conclusions CKD 4-5 and dialysis treatment are independent risk factors for foot ulceration and major amputation compared with CKD 3. Maximum effort is needed in daily clinical practice to prevent foot ulcers and their devastating consequences in all individuals with CKD 4-5 or dialysis treatment.

IMPOSE (IMProving Outcomes after Sepsis)—the effect of a multidisciplinary follow-up service on health-related quality of life in patients postsepsis syndromes—a double-blinded randomised controlled trial: protocol

Introduction Patients post sepsis syndromes have a poor quality of life and a high rate of recurring illness or mortality. Follow-up clinics have been instituted for patients postgeneral intensive care but evidence is sparse, and there has been no clinic specifically for survivors of sepsis. The aim of this trial is to investigate if targeted screening and appropriate intervention to these patients can result in an improved quality of life (Short Form 36 health survey (SF36V.2)), decreased mortality in the first 12 months, decreased readmission to hospital and/or decreased use of health resources. Methods and analysis 204 patients postsepsis syndromes will be randomised to one of the two groups. The intervention group will attend an outpatient clinic two monthly for 6 months and receive screening and targeted intervention. The usual care group will remain under the care of their physician. To analyse the results, a baseline comparison will be carried out between each group. Generalised estimating equations will compare the SF36 domain scores between groups and across time points. Mortality will be compared between groups using a Cox proportional hazards (time until death) analysis. Time to first readmission will be compared between groups by a survival analysis. Healthcare costs will be compared between groups using a generalised linear model. Economic (health resource) evaluation will be a within-trial incremental cost utility analysis with a societal perspective. Ethics and dissemination Ethical approval has been granted by the Royal Brisbane and Women’s Hospital Human Research Ethics Committee (HREC; HREC/13/QRBW/17), The University of Queensland HREC (2013000543), Griffith University (RHS/08/14/HREC) and the Australian Government Department of Health (26/2013). The results of this study will be submitted to peer-reviewed intensive care journals and presented at national and international intensive care and/or rehabilitation conferences.

Combined time- and space-resolved Raman spectrometer for the non-invasive depth profiling of chemical hazards

A time-resolved inverse spatially offset Raman spectrometer was constructed for depth profiling of Raman-active substances under both the lab and the field environments. The system operating principles and performance are discussed along with its advantages relative to traditional continuous wave spatially offset Raman spectrometer. The developed spectrometer uses a combination of space- and time-resolved detection in order to obtain high-quality Raman spectra from substances hidden behind coloured opaque surface layers, such as plastic and garments, with a single measurement. The time-gated spatially offset Raman spectrometer was successfully used to detect concealed explosives and drug precursors under incandescent and fluorescent background light as well as under daylight. The average screening time was 50 s per measurement. The excitation energy requirements were relatively low (20 mW) which makes the probe safe for screening hazardous substances. The unit has been designed with nanosecond laser excitation and gated detection, making it of lower cost and complexity than previous picosecond-based systems, to provide a functional platform for in-line or in-field sensing of chemical substances.

Field portable time resolved SORS sensor for the identification of concealed hazards

Raman spectroscopy, when used in spatially offset mode, has become a potential tool for the identification of explosives and other hazardous substances concealed in opaque containers. The molecular fingerprinting capability of Raman spectroscopy makes it an attractive tool for the unambiguous identification of hazardous substances in the field. Additionally, minimal sample preparation is required compared with other techniques. We report a field portable time resolved Raman sensor for the detection of concealed chemical hazards in opaque containers. The new sensor uses a pulsed nanosecond laser source in conjunction with an intensified CCD detector. The new sensor employs a combination of time and space resolved Raman spectroscopy to enhance the detection capability. The new sensor can identify concealed hazards by a single measurement without any chemometric data treatments.

Real-time detection of concealed chemical hazards under ambient light conditions using Raman spectroscopy

Current concerns regarding terrorism and international crime highlight the need for new techniques for detecting unknown and hazardous substances. A novel Raman spectroscopy-based technique, spatially offset Raman spectroscopy (SORS), was recently devised for non-invasively probing the contents of diffusely scattering and opaque containers. Here, we demonstrate a modified portable SORS sensor for detecting concealed substances in-field under different background lighting conditions. Samples including explosive precursors, drugs and an organophosphate insecticide (chemical warfare agent surrogate) were concealed inside diffusely scattering packaging including plastic, paper and cloth. Measurements were carried out under incandescent and fluorescent light as well as under daylight to assess the suitability of the probe for different real-life conditions. In each case, it was possible to identify the substances against their reference Raman spectra in less than one minute. The developed sensor has potential for rapid detection of concealed hazardous substances in airports, mail distribution centers and customs checkpoints.

Molecular characterisation of environmental enterococci derived from water samples and assessment of associated public health hazards

Enterococci are versatile Gram-positive bacteria that can survive under extreme conditions. Most enterococci are non-virulent and found in the gastrointestinal tract of humans and animals. Other strains are opportunistic pathogens that contribute to a large number of nosocomial infections globally. Epidemiological studies demonstrated a direct relationship between the density of enterococci in surface waters and the risk of swimmer-associated gastroenteritis. The distribution of infectious enterococcal strains from the hospital environment or other sources to environmental water bodies through sewage discharge or other means, could increase the prevalence of these strains in the human population. Environmental water quality studies may benefit from focusing on a subset of Enterococcus spp. that are consistently associated with sources of faecal pollution such as domestic sewage, rather than testing for the entire genus. E. faecalis and E. faecium are potentially good focal species for such studies, as they have been consistently identified as the dominant Enterococcus spp. in human faeces and sewage. On the other hand enterococcal infections are predominantly caused by E. faecalis and E. faecium. The characterisation of E. faecalis and E. faecium is important in studying their population structures, particularly in environmental samples. In developing and implementing rapid, robust molecular genotyping techniques, it is possible to more accurately establish the relationship between human and environmental enterococci. Of particular importance, is to determine the distribution of high risk enterococcal clonal complexes, such as E. faecium clonal complex 17 and E. faecalis clonal complexes 2 and 9 in recreational waters. These clonal complexes are recognized as particularly pathogenic enterococcal genotypes that cause severe disease in humans globally. The Pimpama-Coomera watershed is located in South East Queensland, Australia and was investigated in this study mainly because it is used intensively for agriculture and recreational purposes and has a strong anthropogenic impact. The primary aim of this study was to develop novel, universally applicable, robust, rapid and cost effective genotyping methods which are likely to yield more definitive results for the routine monitoring of E. faecalis and E. faecium, particularly in environmental water sources. To fullfill this aim, new genotyping methods were developed based on the interrogation of highly informative single nucleotide polymorphisms (SNPs) located in housekeeping genes of both E. faecalis and E. faecium. SNP genotyping was successfully applied in field investigations of the Coomera watershed, South-East Queensland, Australia. E. faecalis and E. faecium isolates were grouped into 29 and 23 SNP profiles respectively. This study showed the high longitudinal diversity of E. faecalis and E. faecium over a period of two years, and both human-related and human-specific SNP profiles were identified. Furthermore, 4.25% of E. faecium strains isolated from water was found to correspond to the important clonal complex-17 (CC17). Strains that belong to CC17 cause the majority of hospital outbreaks and clinical infections globally. Of the six sampling sites of the Coomera River, Paradise Point had the highest number of human-related and human-specific E. faecalis and E. faecium SNP profiles. The secondary aim of this study was to determine the antibiotic-resistance profiles and virulence traits associated with environmental E. faecalis and E. faecium isolates compared to human pathogenic E. faecalis and E. faecium isolates. This was performed to predict the potential health risks associated with coming into contact with these strains in the Coomera watershed. In general, clinical isolates were found to be more resistant to all the antibiotics tested compared to water isolates and they harbored more virulence traits. Multi-drug resistance was more prevalent in clinical isolates (71.18% of E. faecalis and 70.3 % of E. faecium) compared to water isolates (only 5.66 % E. faecium). However, tetracycline, gentamicin, ciprofloxacin and ampicillin resistance was observed in water isolates. The virulence gene esp was the most prevalent virulence determinant observed in clinical isolates (67.79% of E. faecalis and 70.37 % of E. faecium), and this gene has been described as a human-specific marker used for microbial source tracking (MST). The presence of esp in water isolates (16.36% of E. faecalis and 19.14% of E. faecium) could be indicative of human faecal contamination in these waterways. Finally, in order to compare overall gene expression between environmental and clinical strains of E. faecalis, a comparative gene hybridization study was performed. The results of this investigation clearly demonstrated the up-regulation of genes associated with pathogenicity in E. faecalis isolated from water. The expression study was performed at physiological temperatures relative to ambient temperatures. The up-regulation of virulence genes demonstrates that environmental strains of E. faecalis can pose an increased health risk which can lead to serious disease, particularly if these strains belong to the virulent CC17 group. The genotyping techniques developed in this study not only provide a rapid, robust and highly discriminatory tool to characterize E. faecalis and E. faecium, but also enables the efficient identification of virulent enterococci that are distributed in environmental water sources.

A yellow filter improves response times to low-contrast targets and traffic hazards

Purpose Anecdotal evidence suggests that some sunglass users prefer yellow tints for outdoor activities, such as driving, and research has suggested that such tints improve the apparent contrast and brightness of real-world objects. The aim of this study was to establish whether yellow filters resulted in objective improvements in performance for visual tasks relevant to driving. Methods Response times of nine young (age [mean ± SD], 31.4 ± 6.7 years) and nine older (age, [mean ± SD], 74.6 ± 4.8) adults were measured using video presentations of traffic hazards (driving hazard perception task) and a simple low-contrast grating appeared at random peripheral locations on a computer screen. Response times were compared when participants wore a yellow filter (with and without a linear polarizer) versus a neutral density filter (with and without a linear polarizer). All lens combinations were matched to have similar luminance transmittances (˜27%). Results In the driving hazard perception task, the young but not the older participants responded significantly more rapidly to hazards when wearing a yellow filter than with a luminance-matched neutral density filter (mean difference, 450 milliseconds). In the low-contrast grating task, younger participants also responded more quickly for the yellow filter condition but only when combined with a polarizer. Although response times increased with increasing stimulus eccentricity for the low-contrast grating task, for the younger participants, this slowing of response times with increased eccentricity was reduced in the presence of a yellow filter, indicating that perception of more peripheral objects may be improved by this filter combination. Conclusions Yellow filters improve response times for younger adults for visual tasks relevant to driving.

Asset health prediction using the explicit hazard model

The ability to estimate the asset reliability and the probability of failure is critical to reducing maintenance costs, operation downtime, and safety hazards. Predicting the survival time and the probability of failure in future time is an indispensable requirement in prognostics and asset health management. In traditional reliability models, the lifetime of an asset is estimated using failure event data, alone; however, statistically sufficient failure event data are often difficult to attain in real-life situations due to poor data management, effective preventive maintenance, and the small population of identical assets in use. Condition indicators and operating environment indicators are two types of covariate data that are normally obtained in addition to failure event and suspended data. These data contain significant information about the state and health of an asset. Condition indicators reflect the level of degradation of assets while operating environment indicators accelerate or decelerate the lifetime of assets. When these data are available, an alternative approach to the traditional reliability analysis is the modelling of condition indicators and operating environment indicators and their failure-generating mechanisms using a covariate-based hazard model. The literature review indicates that a number of covariate-based hazard models have been developed. All of these existing covariate-based hazard models were developed based on the principle theory of the Proportional Hazard Model (PHM). However, most of these models have not attracted much attention in the field of machinery prognostics. Moreover, due to the prominence of PHM, attempts at developing alternative models, to some extent, have been stifled, although a number of alternative models to PHM have been suggested. The existing covariate-based hazard models neglect to fully utilise three types of asset health information (including failure event data (i.e. observed and/or suspended), condition data, and operating environment data) into a model to have more effective hazard and reliability predictions. In addition, current research shows that condition indicators and operating environment indicators have different characteristics and they are non-homogeneous covariate data. Condition indicators act as response variables (or dependent variables) whereas operating environment indicators act as explanatory variables (or independent variables). However, these non-homogenous covariate data were modelled in the same way for hazard prediction in the existing covariate-based hazard models. The related and yet more imperative question is how both of these indicators should be effectively modelled and integrated into the covariate-based hazard model. This work presents a new approach for addressing the aforementioned challenges. The new covariate-based hazard model, which termed as Explicit Hazard Model (EHM), explicitly and effectively incorporates all three available asset health information into the modelling of hazard and reliability predictions and also drives the relationship between actual asset health and condition measurements as well as operating environment measurements. The theoretical development of the model and its parameter estimation method are demonstrated in this work. EHM assumes that the baseline hazard is a function of the both time and condition indicators. Condition indicators provide information about the health condition of an asset; therefore they update and reform the baseline hazard of EHM according to the health state of asset at given time t. Some examples of condition indicators are the vibration of rotating machinery, the level of metal particles in engine oil analysis, and wear in a component, to name but a few. Operating environment indicators in this model are failure accelerators and/or decelerators that are included in the covariate function of EHM and may increase or decrease the value of the hazard from the baseline hazard. These indicators caused by the environment in which an asset operates, and that have not been explicitly identified by the condition indicators (e.g. Loads, environmental stresses, and other dynamically changing environment factors). While the effects of operating environment indicators could be nought in EHM; condition indicators could emerge because these indicators are observed and measured as long as an asset is operational and survived. EHM has several advantages over the existing covariate-based hazard models. One is this model utilises three different sources of asset health data (i.e. population characteristics, condition indicators, and operating environment indicators) to effectively predict hazard and reliability. Another is that EHM explicitly investigates the relationship between condition and operating environment indicators associated with the hazard of an asset. Furthermore, the proportionality assumption, which most of the covariate-based hazard models suffer from it, does not exist in EHM. According to the sample size of failure/suspension times, EHM is extended into two forms: semi-parametric and non-parametric. The semi-parametric EHM assumes a specified lifetime distribution (i.e. Weibull distribution) in the form of the baseline hazard. However, for more industry applications, due to sparse failure event data of assets, the analysis of such data often involves complex distributional shapes about which little is known. Therefore, to avoid the restrictive assumption of the semi-parametric EHM about assuming a specified lifetime distribution for failure event histories, the non-parametric EHM, which is a distribution free model, has been developed. The development of EHM into two forms is another merit of the model. A case study was conducted using laboratory experiment data to validate the practicality of the both semi-parametric and non-parametric EHMs. The performance of the newly-developed models is appraised using the comparison amongst the estimated results of these models and the other existing covariate-based hazard models. The comparison results demonstrated that both the semi-parametric and non-parametric EHMs outperform the existing covariate-based hazard models. Future research directions regarding to the new parameter estimation method in the case of time-dependent effects of covariates and missing data, application of EHM in both repairable and non-repairable systems using field data, and a decision support model in which linked to the estimated reliability results, are also identified.

The hazards

Poem

Timing, origin and emplacement dynamics of mass flows offshore of SE Montserrat in the last 110 ka : implications for landslide and tsunami hazards, eruption history, and volcanic island evolution

Mass flows on volcanic islands generated by volcanic lava dome collapse and by larger-volume flank collapse can be highly dangerous locally and may generate tsunamis that threaten a wider area. It is therefore important to understand their frequency, emplacement dynamics, and relationship to volcanic eruption cycles. The best record of mass flow on volcanic islands may be found offshore, where most material is deposited and where intervening hemipelagic sediment aids dating. Here we analyze what is arguably the most comprehensive sediment core data set collected offshore from a volcanic island. The cores are located southeast of Montserrat, on which the Soufriere Hills volcano has been erupting since 1995. The cores provide a record of mass flow events during the last 110 thousand years. Older mass flow deposits differ significantly from those generated by the repeated lava dome collapses observed since 1995. The oldest mass flow deposit originated through collapse of the basaltic South Soufriere Hills at 103-110 ka, some 20-30 ka after eruptions formed this volcanic center. A ∼1.8 km3 blocky debris avalanche deposit that extends from a chute in the island shelf records a particularly deep-seated failure. It likely formed from a collapse of almost equal amounts of volcanic edifice and coeval carbonate shelf, emplacing a mixed bioclastic-andesitic turbidite in a complex series of stages. This study illustrates how volcanic island growth and collapse involved extensive, large-volume submarine mass flows with highly variable composition. Runout turbidites indicate that mass flows are emplaced either in multiple stages or as single events.

The hazards of starting and quitting smoking: Some Australian evidence

The empirical analysis employs individual level data from the Australian Health Survey combined with retrospective data on tobacco price matched to the age at which the individual started and quit smoking. Split-population hazard models are estimated for both starting and quitting smoking. The analysis suggests price plays a significant role in the decision to start smoking but not in the decision to quit. Further sensitivity analysis of different age groups and an alternative data source, questions the robustness of the significant role of price in the smoking initiation decision. From a policy perspective, the results indicate that increases in tobacco taxation can be an important instrument in reducing the incidence of smoking, but should be combined with other mechanisms such as mandating smoke-free environments and antismoking education. Our results strongly support the targeting of antismoking campaigns towards teenagers.