Probabilistic subgroup identification using Bayesian finite mixture modelling : a case study in Parkinson’s disease phenotype identification

This article explores the use of probabilistic classification, namely finite mixture modelling, for identification of complex disease phenotypes, given cross-sectional data. In particular, if focuses on posterior probabilities of subgroup membership, a standard output of finite mixture modelling, and how the quantification of uncertainty in these probabilities can lead to more detailed analyses. Using a Bayesian approach, we describe two practical uses of this uncertainty: (i) as a means of describing a person’s membership to a single or multiple latent subgroups and (ii) as a means of describing identified subgroups by patient-centred covariates not included in model estimation. These proposed uses are demonstrated on a case study in Parkinson’s disease (PD), where latent subgroups are identified using multiple symptoms from the Unified Parkinson’s Disease Rating Scale (UPDRS).

Making sense of dementia : understanding amongst indigenous Australians

Dementia is a growing health and social concern for all Australians. Whilst the prevalence of dementia amongst Australia's indigenous people is unclear, there is some evidence that dementia rates are five times that of the general Australian population. To date no studies have examined dementia knowledge levels in indigenous communities. Purpose of the study: This paper aims to explore indigenous Australians' understanding, knowledge and misconceptions of dementia. Design and methods: Hundered and seventy-four indigenous adults participated in a cross-sectional survey using a modified version of the Alzheimer's Disease Knowledge Test (ADK). The survey included demographic information, two open-ended questions and 20 multiple choice questions. Each ADK item was examined to identify responses that revealed commonly held correct beliefs, knowledge gaps and misconceptions. Results: The overall level of understanding of dementia was poor. Younger participants were significantly more likely to have no knowledge of Alzheimer's Disease, whereas the other age groups were most likely to have at least some knowledge. It was also revealed that there are common misconceptions about Alzheimer's Disease held by both indigenous and non-indigenous communities. Implications: Culturally appropriate awareness campaigns and targeted educational interventions need to be implemented to improve the general level of understanding of dementia in indigenous communities.

A Bayesian approach to assess interaction between known risk factors: The risk of lung cancer from exposure to asbestos and smoking

We review the literature on the combined effect of asbestos exposure and smoking on lung cancer, and explore a Bayesian approach to assess evidence of interaction. Previous approaches have focussed on separate tests for an additive or multiplicative relation. We extend these approaches by exploring the strength of evidence for either relation using approaches which allow the data to choose between both models. We then compare the different approaches.

The role of coronial autopsies in a context of decreasing hospital autopsies: An investigation of the issues

This article scrutinises the argument that decreasing hospital autopsy rates are outside the control of medical personnel, based as they are on families’ unwillingness to consent to autopsy procedures, and that, as a consequence, the coronial autopsy is the appropriate alternative to the important medical and educational role of the autopsy. It makes three points which are well supported by the research. First, that while hospital autopsy rates are decreasing, they have been doing so for more than 60 years, and issues beyond the simple notion of consent, like funding formulae in hospitals, increased technology and fear of litigation by doctors are all playing their part in this decline. Secondly, the issue of consent has as much to do with families not being approached as with families declining to give consent. This is well supported by recent changes in hospital policy and procedures which include senior medical personnel and detailed consent forms, both of which have been linked to rising consent rates in recent years. Finally, the perception that coronial autopsies are beyond familial consent has been challenged recently by legislative changes in both Australia and the United States of America which allow objections based on religion and culture to be heard by coroners. For these reasons, it is argued that medical personnel need to focus on increasing hospital autopsy rates, while also addressing the complex ethical issues associated with conducting medical research within the context of the coronial autopsy.

Producing the magnum opus : A metaphor for nephrology nursing expertise acquisition

Aim. This paper elucidates the nature of metaphor and the conditions necessary to its use as an analytic device in qualitative research, and describes how the use of metaphor assisted in the analytic processes of a grounded theory study of nephrology nursing expertise. Background. The use of metaphor is pervasive in everyday thought, language and action. It is an important means for the comprehension and management of everyday life, and makes challenging or problematic concepts easier to explain. Metaphors are also pervasive in quantitative and qualitative research for the same reason. In both everyday life and in research, their use may be implicit or explicit. Methods. The study using grounded theory methodology took place in one renal unit in New South Wales, Australia between 1999 and 2000 and included six non-expert and 11 expert nurses. It involved simultaneous data collection and analysis using participant observation, semi-structured interviews and review of nursing documentation. Findings. A three stage skills-acquisitive process was identified in which an orchestral metaphor was used to explain the relationships between stages and to satisfactorily capture the data coded within each stage. Conclusion. Metaphors create images, clarify and add depth to meanings and, if used appropriately and explicitly in qualitative research, can capture data at highly conceptual levels. Metaphors also assist in explaining the relationship between findings in a clear and coherent manner. © 2005 Blackwell Publishing Ltd.

The impact of nonlinear exposure risk relationships on seasonal time series data: modelling danish neonatal birth anthropometric data

Background Birth weight and length have seasonal fluctuations. Previous analyses of birth weight by latitude effects identified seemingly contradictory results, showing both 6 and 12 monthly periodicities in weight. The aims of this paper are twofold: (a) to explore seasonal patterns in a large, Danish Medical Birth Register, and (b) to explore models based on seasonal exposures and a non-linear exposure-risk relationship. Methods Birth weight and birth lengths on over 1.5 million Danish singleton, live births were examined for seasonality. We modelled seasonal patterns based on linear, U- and J-shaped exposure-risk relationships. We then added an extra layer of complexity by modelling weighted population-based exposure patterns. Results The Danish data showed clear seasonal fluctuations for both birth weight and birth length. A bimodal model best fits the data, however the amplitude of the 6 and 12 month peaks changed over time. In the modelling exercises, U- and J-shaped exposure-risk relationships generate time series with both 6 and 12 month periodicities. Changing the weightings of the population exposure risks result in unexpected properties. A J-shaped exposure-risk relationship with a diminishing population exposure over time fitted the observed seasonal pattern in the Danish birth weight data. Conclusion In keeping with many other studies, Danish birth anthropometric data show complex and shifting seasonal patterns. We speculate that annual periodicities with non-linear exposure-risk models may underlie these findings. Understanding the nature of seasonal fluctuations can help generate candidate exposures.

The CDKN2A (p16) gene and human cancer

CDKN2A, the gene encoding the cell-cycle inhibitor p16CDKN2A, was first identified in 1994. Since then, somatic mutations have been observed in many cancers and germline alterations have been found in kindreds with familial atypical multiple mole/melanoma (FAMMM), also known as atypical mole syndrome. In this review we tabulate the known mutations in this gene and discuss specific aspects, particularly with respect to germline mutations and cancer predisposition.

Application of Mesenchymal Stem Cells for repair and regeneration of cartilage and bone

Australian efforts to provide orthopaedic surgeons with living, load-bearing scaffolds suitable for current joint (knee and hip) replacement surgery, non-union fracture repair, and miniscal and growth plate cartilage regeneration are being lead by teams at the Institute for Medical and Veterinary Science and Women's and Children's Hospital in Adelaide; the Peter MacCallum and St Vincent's Medical Research Institutes in Melbourne; and the Mater Medical Research Institute and new Institute for Health and Biomedical Innovation at QUT, Brisbane. In each case multidisciplinary teams are attempting to develop autologous living tissue constructs, utilising mesenchymal stem cells (MSC), with the intention of effecting seamless repair and regeneration of skeletal trauma and defects. In this article we will briefly review current knowledge of the phenotypic properties of MSC and discuss the potential therapeutic applications of these cells as exemplified by their use in cartilage repair and tissue engineering based approaches to the treatment of skeletal defects.

Photochemistry and chemometrics : an overview

Photochemistry has made significant contributions to our understanding of many important natural processes as well as the scientific discoveries of the man-made world. The measurements from such studies are often complex and may require advanced data interpretation with the use of multivariate or chemometrics methods. In general, such methods have been applied successfully for data display, classification, multivariate curve resolution and prediction in analytical chemistry, environmental chemistry, engineering, medical research and industry. However, in photochemistry, by comparison, applications of such multivariate approaches were found to be less frequent although a variety of methods have been used, especially with spectroscopic photochemical applications. The methods include Principal Component Analysis (PCA; data display), Partial Least Squares (PLS; prediction), Artificial Neural Networks (ANN; prediction) and several models for multivariate curve resolution related to Parallel Factor Analysis (PARAFAC; decomposition of complex responses). Applications of such methods are discussed in this overview and typical examples include photodegradation of herbicides, prediction of antibiotics in human fluids (fluorescence spectroscopy), non-destructive in- and on-line monitoring (near infrared spectroscopy) and fast-time resolution of spectroscopic signals from photochemical reactions. It is also quite clear from the literature that the scope of spectroscopic photochemistry was enhanced by the application of chemometrics. To highlight and encourage further applications of chemometrics in photochemistry, several additional chemometrics approaches are discussed using data collected by the authors. The use of a PCA biplot is illustrated with an analysis of a matrix containing data on the performance of photocatalysts developed for water splitting and hydrogen production. In addition, the applications of the Multi-Criteria Decision Making (MCDM) ranking methods and Fuzzy Clustering are demonstrated with an analysis of water quality data matrix. Other examples of topics include the application of simultaneous kinetic spectroscopic methods for prediction of pesticides, and the use of response fingerprinting approach for classification of medicinal preparations. In general, the overview endeavours to emphasise the advantages of chemometrics' interpretation of multivariate photochemical data, and an Appendix of references and summaries of common and less usual chemometrics methods noted in this work, is provided. Crown Copyright © 2010.

SNP diversity of Enterococcus faecalis and Enterococcus faecium in a South East Queensland waterway, Australia, and associated antibiotic resistance gene profiles

BACKGROUND: Enterococcus faecalis and Enterococcus faecium are associated with faecal pollution of water, linked to swimmer-associated gastroenteritis and demonstrate a wide range of antibiotic resistance. The Coomera River is a main water source for the Pimpama-Coomera watershed and is located in South East Queensland, Australia, which is used intensively for agriculture and recreational purposes. This study investigated the diversity of E. faecalis and E. faecium using Single Nucleotide Polymorphisms (SNPs) and associated antibiotic resistance profiles. RESULTS: Total enterococcal counts (cfu/ml) for three/six sampling sites were above the United States Environmental Protection Agency (USEPA) recommended level during rainfall periods and fall into categories B and C of the Australian National Health and Medical Research Council (NHMRC) guidelines (with a 1-10% gastrointestinal illness risk). E. faecalis and E. faecium isolates were grouped into 29 and 23 SNP profiles (validated by MLST analysis) respectively. This study showed the high diversity of E. faecalis and E. faecium over a period of two years and both human-related and human-specific SNP profiles were identified. 81.8% of E. faecalis and 70.21% of E. faecium SNP profiles were associated with genotypic and phenotypic antibiotic resistance. Gentamicin resistance was higher in E. faecalis (47% resistant) and harboured the aac(6')-aph(2') gene. Ciprofloxacin resistance was more common in E. faecium (12.7% resistant) and gyrA gene mutations were detected in these isolates. Tetracycline resistance was less common in both species while tet(L) and tet(M) genes were more prevalent. Ampicillin resistance was only found in E. faecium isolates with mutations in the pbp5 gene. Vancomycin resistance was not detected in any of the isolates. We found that antibiotic resistance profiles further sub-divided the SNP profiles of both E. faecalis and E. faecium. CONCLUSIONS: The distribution of E. faecalis and E. faecium genotypes is highly diverse in the Coomera River. The SNP genotyping method is rapid and robust and can be applied to study the diversity of E. faecalis and E. faecium in waterways. It can also be used to test for human-related and human-specific enterococci in water. The resolving power can be increased by including antibiotic-resistant profiles which can be used as a possible source tracking tool. This warrants further investigation.

Methodological challenges when estimating the effects of season and seasonal exposures on birth outcomes

Background Many previous studies have found seasonal patterns in birth outcomes, but with little agreement about which season poses the highest risk. Some of the heterogeneity between studies may be explained by a previously unknown bias. The bias occurs in retrospective cohorts which include all births occurring within a fixed start and end date, which means shorter pregnancies are missed at the start of the study, and longer pregnancies are missed at the end. Our objective was to show the potential size of this bias and how to avoid it. Methods To demonstrate the bias we simulated a retrospective birth cohort with no seasonal pattern in gestation and used a range of cohort end dates. As a real example, we used a cohort of 114,063 singleton births in Brisbane between 1 July 2005 and 30 June 2009 and examined the bias when estimating changes in gestation length associated with season (using month of conception) and a seasonal exposure (temperature). We used survival analyses with temperature as a time-dependent variable. Results We found strong artificial seasonal patterns in gestation length by month of conception, which depended on the end date of the study. The bias was avoided when the day and month of the start date was just before the day and month of the end date (regardless of year), so that the longer gestations at the start of the study were balanced by the shorter gestations at the end. After removing the fixed cohort bias there was a noticeable change in the effect of temperature on gestation length. The adjusted hazard ratios were flatter at the extremes of temperature but steeper between 15 and 25°C. Conclusions Studies using retrospective birth cohorts should account for the fixed cohort bias by removing selected births to get unbiased estimates of seasonal health effects.

Validation of de-identified record linkage to ascertain hospital admissions in a cohort study

Background Cohort studies can provide valuable evidence of cause and effect relationships but are subject to loss of participants over time, limiting the validity of findings. Computerised record linkage offers a passive and ongoing method of obtaining health outcomes from existing routinely collected data sources. However, the quality of record linkage is reliant upon the availability and accuracy of common identifying variables. We sought to develop and validate a method for linking a cohort study to a state-wide hospital admissions dataset with limited availability of unique identifying variables. Methods A sample of 2000 participants from a cohort study (n = 41 514) was linked to a state-wide hospitalisations dataset in Victoria, Australia using the national health insurance (Medicare) number and demographic data as identifying variables. Availability of the health insurance number was limited in both datasets; therefore linkage was undertaken both with and without use of this number and agreement tested between both algorithms. Sensitivity was calculated for a sub-sample of 101 participants with a hospital admission confirmed by medical record review. Results Of the 2000 study participants, 85% were found to have a record in the hospitalisations dataset when the national health insurance number and sex were used as linkage variables and 92% when demographic details only were used. When agreement between the two methods was tested the disagreement fraction was 9%, mainly due to "false positive" links when demographic details only were used. A final algorithm that used multiple combinations of identifying variables resulted in a match proportion of 87%. Sensitivity of this final linkage was 95%. Conclusions High quality record linkage of cohort data with a hospitalisations dataset that has limited identifiers can be achieved using combinations of a national health insurance number and demographic data as identifying variables.