Modelling the effect of fibropapilloma disease on the somatic growth dynamics of Hawaiian green sea turtles

The effect of the tumour-forming disease, fibropapillomatosis, on the somatic growth dynamics of green turtles resident in the Pala'au foraging grounds (Moloka'i, Hawai'i) was evaluated using a Bayesian generalised additive mixed modelling approach. This regression model enabled us to account for fixed effects (fibropapilloma tumour severity), nonlinear covariate functional form (carapace size, sampling year) as well as random effects due to individual heterogeneity and correlation between repeated growth measurements on some turtles. Somatic growth rates were found to be nonlinear functions of carapace size and sampling year but were not a function of low-to-moderate tumour severity. On the other hand, growth rates were significantly lower for turtles with advanced fibropapillomatosis, which suggests a limited or threshold-specific disease effect. However, tumour severity was an increasing function of carapace size-larger turtles tended to have higher tumour severity scores, presumably due to longer exposure of larger (older) turtles to the factors that cause the disease. Hence turtles with advanced fibropapillomatosis tended to be the larger turtles, which confounds size and tumour severity in this study. But somatic growth rates for the Pala'au population have also declined since the mid-1980s (sampling year effect) while disease prevalence and severity increased from the mid-1980s before levelling off by the mid-1990s. It is unlikely that this decline was related to the increasing tumour severity because growth rates have also declined over the last 10-20 years for other green turtle populations resident in Hawaiian waters that have low or no disease prevalence. The declining somatic growth rate trends evident in the Hawaiian stock are more likely a density-dependent effect caused by a dramatic increase in abundance by this once-seriously-depleted stock since the mid-1980s. So despite increasing fibropapillomatosis risk over the last 20 years, only a limited effect on somatic growth dynamics was apparent and the Hawaiian green turtle stock continues to increase in abundance.

Disease risk and mortality prediction in intensive care patients with pneumonia. Australian and New Zealand practice in intensive care (ANZPIC II)

This study of ventilated patients investigated pneumonia risk factors and outcome predictors in 476 episodes of pneumonia (48% community-acquired pneumonia, 24% hospital-acquired pneumonia, 28% ventilator-associated pneumonia) using a prospective survey in 14 intensive care units within Australia and New Zealand. For community acquired pneumonia, mortality increased with immunosuppression (OR 5.32, CI 95% 1.58-17.99, P < 0. 01), clinical signs of consolidation (OR 2.43, CI 95% 1.09-5.44, P = 0. 03) and Sepsis-Related Organ Failure Assessment (SOFA) scores (OR 1.19, CI 95% 1.08-1.30, P < 0. 001) but improved if appropriate antibiotic changes were made within three days of intensive care unit admission (OR 0.42, CI 95% 0.20-0.86, P = 0.02). For hospital-acquired pneumonia, immunosuppression (OR 6.98, CI 95% 1.16-42.2, P = 0.03) and non-metastatic cancer (OR 3.78, CI 95% 1.20-11.93, P = 0.02) were the principal mortality predictors. Alcoholism (OR 7.80, CI 95% 1.20-1750, P < 0.001), high SOFA scores (OR 1.44, CI 95% 1.20-1.75, P = 0.001) and the isolation of high risk organisms including Pseudomonas aeruginosa, Acinetobacter spp, Stenotrophomonas spp and methicillin resistant Staphylococcus aureus (OR 4.79, CI 95% 1.43-16.03, P = 0.01), were associated with increased mortality in ventilator-associated pneumonia. The use of non-invasive ventilation was independently protective against mortality for patients with community-acquired and hospital-acquired pneumonia (OR 0.35, CI 95% 0.18-0.68, P = 0.002). Mortality was similar for patients requiting both invasive and non-invasive ventilation and non-invasive ventilation alone (21% compared with 20% respectively, P = 0.56). Pneumonia risks and mortality predictors in Australian and New Zealand ICUs vary with pneumonia type. A history of alcoholism is a major risk factor for mortality in ventilator-associated pneumonia, greater in magnitude than the mortality effect of immunosuppression in hospital-acquired pneumonia or community-acquired pneumonia. Non-invasive ventilation is associated with reduced ICU mortality. Clinical signs of consolidation worsen, while rationalising antibiotic therapy within three days of ICU admission improves mortality for community-acquired pneumonia patients.

The evolution of the Global Burden of Disease framework for disease, injury and risk factor quantification: Developing the evidence base for national, regional and global public health action

Reliable, comparable information about the main causes of disease and injury in populations, and how these are changing, is a critical input for debates about priorities in the health sector. Traditional sources of information about the descriptive epidemiology of diseases, injuries and risk factors are generally incomplete, fragmented and of uncertain reliability and comparability. Lack of a standardized measurement framework to permit comparisons across diseases and injuries, as well as risk factors, and failure to systematically evaluate data quality have impeded comparative analyses of the true public health importance of various conditions and risk factors. As a consequence the impact of major conditions and hazards on population health has been poorly appreciated, often leading to a lack of public health investment. Global disease and risk factor quantification improved dramatically in the early 1990s with the completion of the first Global Burden of Disease Study. For the first time, the comparative importance of over 100 diseases and injuries, and ten major risk factors, for global and regional health status could be assessed using a common metric (Disability-Adjusted Life Years) which simultaneously accounted for both premature mortality and the prevalence, duration and severity of the non-fatal consequences of disease and injury. As a consequence, mental health conditions and injuries, for which non-fatal outcomes are of particular significance, were identified as being among the leading causes of disease/injury burden worldwide, with clear implications for policy, particularly prevention. A major achievement of the Study was the complete global descriptive epidemiology, including incidence, prevalence and mortality, by age, sex and Region, of over 100 diseases and injuries. National applications, further methodological research and an increase in data availability have led to improved national, regional and global estimates for 2000, but substantial uncertainty around the disease burden caused by major conditions, including, HIV, remains. The rapid implementation of cost-effective data collection systems in developing countries is a key priority if global public policy to promote health is to be more effectively informed.

Chronic obstructive pulmonary disease: current burden and future projections

Information about the comparative magnitude of the burden from various diseases and injuries is a critical input into building the evidence base for health policies and programmes. Such information should be based on a critical evaluation of all available epidemiological data using standard and comparable procedures across diseases and injuries, including information on the age at death and the incidence, duration and severity of cases who do not die prematurely from the disease. A summary measure, disability-adjusted life yrs (DALYs), has been developed to simultaneously measure the amount of disease burden due to premature mortality and the amount due to the nonfatal consequences of disease.

Clinically active Crohn's disease in the presence of a low C-reactive protein

Objective. Clinical interest in C-reactive protein (CRP) - a component of the innate immune system - has focused mainly on its worth as an indicator of disease activity. There has been a resurgence of interest in CRP in the Crohn's disease ( CD) literature because several trials of new treatments for active CD have been characterized by both a large proportion of patients with low CRP ( < 10 mg/l) at entry to the trials and by a negative therapeutic outcome. It is therefore of interest to study the clinical characteristics of patients who are thought to have at the same time both active CD and a low CRP. Material and methods. Patients were prospectively recruited as part of the Brisbane IBD clinical and research programme. Subjects were included in the low CRP group only if there were complete datasets for CRP on all occasions of active CD, and CRP was < 10 mg/l. Active disease was defined as CD activity index (CDAI) > 200. The low CRP group was compared with patients in the raised CRP group for a range of clinical variables as well as the major NOD2 variants. Results. There were data sets for 223 CD patients, with a mean disease duration of 12 years. Of these, 22 patients fulfilled the criteria for low CRP. The low CRP group ( group 1) showed significant differences for disease site (p < 0.01) and for BMI (p = 0.006) compared to the raised CRP group ( group 2). Specifically, group 1 had a predominance of pure ileal disease (95% versus 53%) and lack of pure colonic disease (0% versus 24%) compared to group 2, and their BMI was significantly lower (20.3 kg/m(2) versus 25.0 kg/m(2)). Groups 1 and 2 did not differ with respect to Vienna behaviour at diagnosis, smoking, appendicectomy, extra-intestinal manifestations of CD, or NOD2 SNP variants. There was a trend for low CRP patients with previous ileal resection to evolve to a stricturing phenotype. Fat wrapping was noted in 11/13 (85%) of low CRP patients undergoing ileal resections. Conclusions. Patients with CD and a persistently low CRP in the face of active disease were characterized by an almost exclusive ileal disease distribution and a low BMI, compared to those with a raised CRP. These patients had a similar frequency and distribution of NOD2/CARD15 variants. Stricturing ( v inflammatory or penetrating) behaviour may explain some low CRP. Despite the abnormally low BMI, fat wrapping was noted in the majority of low CRP patients undergoing ileal resection.

Neuropathological heterogeneity in Alzheimer's disease:A study of 80 cases using principal components analysis

Three hypotheses have been proposed to explain neuropathological heterogeneity in Alzheimer's disease (AD): the presence of distinct subtypes ('subtype hypothesis'), variation in the stage of the disease ('phase hypothesis') and variation in the origin and progression of the disease ('compensation hypothesis'). To test these hypotheses, variation in the distribution and severity of senile plaques (SP) and neurofibrillary tangles (NFT) was studied in 80 cases of AD using principal components analysis (PCA). Principal components analysis using the cases as variables (Q-type analysis) suggested that individual differences between patients were continuously distributed rather than the cases being clustered into distinct subtypes. In addition, PCA using the abundances of SP and NFT as variables (R-type analysis) suggested that variations in the presence and abundance of lesions in the frontal and occipital lobes, the cingulate gyrus and the posterior parahippocampal gyrus were the most important sources of heterogeneity consistent with the presence of different stages of the disease. In addition, in a subgroup of patients, individual differences were related to apolipoprotein E (ApoE) genotype, the presence and severity of SP in the frontal and occipital cortex being significantly increased in patients expressing apolipoprotein (Apo)E allele ε4. It was concluded that some of the neuropathological heterogeneity in our AD cases may be consistent with the 'phase hypothesis'. A major factor determining this variation in late-onset cases was ApoE genotype with accelerated rates of spread of the pathology in patients expressing allele ε4.

Local-authority led economic regeneration strategies in the aftermath of the Foot-and-Mouth Disease crisis of 2001

The Foot-and-Mouth Disease (FMD) outbreak of 2001 in the UK was completely unprecedented in its scale and severity, with over four million animals culled and a cost to the Exchequer of over £4 billion. Local authorities were at the front line in dealing with the outbreak, in coordinating the cull of livestock, the disposal of carcasses as well as attempting to deal with its aftermath and, in particular, the impact on the wider rural economy. This article examines the impacts of this crisis on three local authorities, Devon, Herefordshire and Cumbria. It examines how far the crisis acted as a catalyst in developing strategies to deal with a future outbreak as well as new local initiatives to promote regeneration in the areas most adversely affected. It focuses on developments that can be directly attributed to the crisis and shows that FMD had a considerable impact on communications and 'joined-up' activity within local authorities and with local stakeholders. © 2006, LEPU, South Bank University.

Novel speech signal processing algorithms for high-accuracy classification of Parkinson's disease

There has been considerable recent research into the connection between Parkinson's disease (PD) and speech impairment. Recently, a wide range of speech signal processing algorithms (dysphonia measures) aiming to predict PD symptom severity using speech signals have been introduced. In this paper, we test how accurately these novel algorithms can be used to discriminate PD subjects from healthy controls. In total, we compute 132 dysphonia measures from sustained vowels. Then, we select four parsimonious subsets of these dysphonia measures using four feature selection algorithms, and map these feature subsets to a binary classification response using two statistical classifiers: random forests and support vector machines. We use an existing database consisting of 263 samples from 43 subjects, and demonstrate that these new dysphonia measures can outperform state-of-the-art results, reaching almost 99% overall classification accuracy using only ten dysphonia features. We find that some of the recently proposed dysphonia measures complement existing algorithms in maximizing the ability of the classifiers to discriminate healthy controls from PD subjects. We see these results as an important step toward noninvasive diagnostic decision support in PD.

Quantifying short-term dynamics of Parkinson's disease using self-reported symptom data from an internet social network

Background: Parkinson’s disease (PD) is an incurable neurological disease with approximately 0.3% prevalence. The hallmark symptom is gradual movement deterioration. Current scientific consensus about disease progression holds that symptoms will worsen smoothly over time unless treated. Accurate information about symptom dynamics is of critical importance to patients, caregivers, and the scientific community for the design of new treatments, clinical decision making, and individual disease management. Long-term studies characterize the typical time course of the disease as an early linear progression gradually reaching a plateau in later stages. However, symptom dynamics over durations of days to weeks remains unquantified. Currently, there is a scarcity of objective clinical information about symptom dynamics at intervals shorter than 3 months stretching over several years, but Internet-based patient self-report platforms may change this. Objective: To assess the clinical value of online self-reported PD symptom data recorded by users of the health-focused Internet social research platform PatientsLikeMe (PLM), in which patients quantify their symptoms on a regular basis on a subset of the Unified Parkinson’s Disease Ratings Scale (UPDRS). By analyzing this data, we aim for a scientific window on the nature of symptom dynamics for assessment intervals shorter than 3 months over durations of several years. Methods: Online self-reported data was validated against the gold standard Parkinson’s Disease Data and Organizing Center (PD-DOC) database, containing clinical symptom data at intervals greater than 3 months. The data were compared visually using quantile-quantile plots, and numerically using the Kolmogorov-Smirnov test. By using a simple piecewise linear trend estimation algorithm, the PLM data was smoothed to separate random fluctuations from continuous symptom dynamics. Subtracting the trends from the original data revealed random fluctuations in symptom severity. The average magnitude of fluctuations versus time since diagnosis was modeled by using a gamma generalized linear model. Results: Distributions of ages at diagnosis and UPDRS in the PLM and PD-DOC databases were broadly consistent. The PLM patients were systematically younger than the PD-DOC patients and showed increased symptom severity in the PD off state. The average fluctuation in symptoms (UPDRS Parts I and II) was 2.6 points at the time of diagnosis, rising to 5.9 points 16 years after diagnosis. This fluctuation exceeds the estimated minimal and moderate clinically important differences, respectively. Not all patients conformed to the current clinical picture of gradual, smooth changes: many patients had regimes where symptom severity varied in an unpredictable manner, or underwent large rapid changes in an otherwise more stable progression. Conclusions: This information about short-term PD symptom dynamics contributes new scientific understanding about the disease progression, currently very costly to obtain without self-administered Internet-based reporting. This understanding should have implications for the optimization of clinical trials into new treatments and for the choice of treatment decision timescales.

High accuracy discrimination of Parkinson's disease participants from healthy controls using smartphones

The aim of this study is to accurately distinguish Parkinson's disease (PD) participants from healthy controls using self-administered tests of gait and postural sway. Using consumer-grade smartphones with in-built accelerometers, we objectively measure and quantify key movement severity symptoms of Parkinson's disease. Specifically, we record tri-axial accelerations, and extract a range of different features based on the time and frequency-domain properties of the acceleration time series. The features quantify key characteristics of the acceleration time series, and enhance the underlying differences in the gait and postural sway accelerations between PD participants and controls. Using a random forest classifier, we demonstrate an average sensitivity of 98.5% and average specificity of 97.5% in discriminating PD participants from controls. © 2014 IEEE.

Retinal arteriolar diameter response to flicker light provocation - A useful marker for risk stratification in cardiovascular disease?

Purpose: To to evaluate the benefit of bilinear and linear fitting to characterize the retinal vessel dilation to flicker light stimulation for the purpose of risk stratification in cardiovascular disease. Methods: Forty-five patients (15 with coronary artery disease (CAD), 15 with Diabetes Mellitus (DM) and 15 with CAD and DM) all underwent contact tonometry, digital blood pressure measurement, fundus photography, retinal vessel oximetry, static retinal vessel analysis and continous retinal diameter assessment using the retinal vessel analyser (and flicker light provocation). In addition we measured blood glucose (HbA1c) and keratinin levels in DM patients. Results: With increased severity of cardiovascular disease a more linear reaction profile of retinal arteriolar diameter to flicker light provocation can be observed. Conclusion: Absolute values of vessel dilation provide only limited information on the state of retinal arteriolar dilatory response to flicker light. The approach of bilinear fitting takes into account the immediate response to flicker light provocation as well as the maintained dilatory capacity during prolonged stimulation. Individuals with cardiovascular disease however show a largely linear reaction profile indicating an impairment of the initial rapid dilatory response as usually observed in healty individuals

High-accuracy discrimination of Parkinson’s Disease participants from healthy controls using smartphones

Objective: To test the practicality and effectiveness of cheap, ubiquitous, consumer-grade smartphones to discriminate Parkinson’s disease (PD) subjects from healthy controls, using self-administered tests of gait and postural sway. Background: Existing tests for the diagnosis of PD are based on subjective neurological examinations, performed in-clinic. Objective movement symptom severity data, collected using widely-accessible technologies such as smartphones, would enable the remote characterization of PD symptoms based on self-administered, behavioral tests. Smartphones, when backed up by interviews using web-based videoconferencing, could make it feasible for expert neurologists to perform diagnostic testing on large numbers of individuals at low cost. However, to date, the compliance rate of testing using smart-phones has not been assessed. Methods: We conducted a one-month controlled study with twenty participants, comprising 10 PD subjects and 10 controls. All participants were provided identical LG Optimus S smartphones, capable of recording tri-axial acceleration. Using these smartphones, patients conducted self-administered, short (less than 5 minute) controlled gait and postural sway tests. We analyzed a wide range of summary measures of gait and postural sway from the accelerometry data. Using statistical machine learning techniques, we identified discriminating patterns in the summary measures in order to distinguish PD subjects from controls. Results: Compliance was high all 20 participants performed an average of 3.1 tests per day for the duration of the study. Using this test data, we demonstrated cross-validated sensitivity of 98% and specificity of 98% in discriminating PD subjects from healthy controls. Conclusions: Using consumer-grade smartphone accelerometers, it is possible to distinguish PD from healthy controls with high accuracy. Since these smartphones are inexpensive (around $30 each) and easily available, and the tests are highly non-invasive and objective, we envisage that this kind of smartphone-based testing could radically increase the reach and effectiveness of experts in diagnosing PD.

Machine learning for large-scale wearable sensor data in Parkinson disease:concepts, promises, pitfalls, and futures

For the treatment and monitoring of Parkinson's disease (PD) to be scientific, a key requirement is that measurement of disease stages and severity is quantitative, reliable, and repeatable. The last 50 years in PD research have been dominated by qualitative, subjective ratings obtained by human interpretation of the presentation of disease signs and symptoms at clinical visits. More recently, “wearable,” sensor-based, quantitative, objective, and easy-to-use systems for quantifying PD signs for large numbers of participants over extended durations have been developed. This technology has the potential to significantly improve both clinical diagnosis and management in PD and the conduct of clinical studies. However, the large-scale, high-dimensional character of the data captured by these wearable sensors requires sophisticated signal processing and machine-learning algorithms to transform it into scientifically and clinically meaningful information. Such algorithms that “learn” from data have shown remarkable success in making accurate predictions for complex problems in which human skill has been required to date, but they are challenging to evaluate and apply without a basic understanding of the underlying logic on which they are based. This article contains a nontechnical tutorial review of relevant machine-learning algorithms, also describing their limitations and how these can be overcome. It discusses implications of this technology and a practical road map for realizing the full potential of this technology in PD research and practice. © 2016 International Parkinson and Movement Disorder Society.

Trading between perceived risks and benefits related to biosimilar biological treatment in Crohn’s disease; discrete choice experiment among gastroenterologists

Objective: The objective of the study is to explore preferences of gastroenterologists for biosimilar drugs in Crohn’s Disease and reveal trade-offs between the perceived risks and benefits related to biosimilar drugs. Method: Discrete choice experiment was carried out involving 51 Hungarian gastroenterologists in May, 2014. The following attributes were used to describe hypothetical choice sets: 1) type of the treatment (biosimilar/originator) 2) severity of disease 3) availability of continuous medicine supply 4) frequency of the efficacy check-ups. Multinomial logit model was used to differentiate between three attitude types: 1) always opting for the originator 2) willing to consider biosimilar for biological-naïve patients only 3) willing to consider biosimilar treatment for both types of patients. Conditional logit model was used to estimate the probabilities of choosing a given profile. Results: Men, senior consultants, working in IBD center and treating more patients are more likely to willing to consider biosimilar for biological-naïve patients only. Treatment type (originator/biosimilar) was the most important determinant of choice for patients already treated with biologicals, and the availability of continuous medicine supply in the case biological-naïve patients. The probabilities of choosing the biosimilar with all the benefits offered over the originator under current reimbursement conditions are 89% vs 11% for new patients, and 44% vs 56% for patients already treated with biological. Conclusions: Gastroenterologists were willing to trade between perceived risks and benefits of biosimilars. The continuous medical supply would be one of the major benefits of biosimilars. However, benefits offered in the scenarios do not compensate for the change from the originator to the biosimilar treatment of patients already treated with biologicals.