Cardiomyopathy classification : ongoing debate in the genomics era

Cardiomyopathies represent a group of diseases of the myocardium of the heart and include diseases both primarily of the cardiac muscle and systemic diseases leading to adverse effects on the heart muscle size, shape, and function. Traditionally cardiomyopathies were defined according to phenotypical appearance. Now, as our understanding of the pathophysiology of the different entities classified under each of the different phenotypes improves and our knowledge of the molecular and genetic basis for these entities progresses, the traditional classifications seem oversimplistic and do not reflect current understanding of this myriad of diseases and disease processes. Although our knowledge of the exact basis of many of the disease processes of cardiomyopathies is still in its infancy, it is important to have a classification system that has the ability to incorporate the coming tide of molecular and genetic information. This paper discusses how the traditional classification of cardiomyopathies based on morphology has evolved due to rapid advances in our understanding of the genetic and molecular basis for many of these clinical entities.

Malnutrition in Parkinson's disease and an individualised approach to its management

It has been reported that poor nutritional status, in the form of weight loss and resulting body mass index (BMI) changes, is an issue in people with Parkinson's disease (PWP). The symptoms resulting from Parkinson's disease (PD) and the side effects of PD medication have been implicated in the aetiology of nutritional decline. However, the evidence on which these claims are based is, on one hand, contradictory, and on the other, restricted primarily to otherwise healthy PWP. Despite the claims that PWP suffer from poor nutritional status, evidence is lacking to inform nutrition-related care for the management of malnutrition in PWP. The aims of this thesis were to better quantify the extent of poor nutritional status in PWP, determine the important factors differentiating the well-nourished from the malnourished and evaluate the effectiveness of an individualised nutrition intervention on nutritional status. Phase DBS: Nutritional status in people with Parkinson's disease scheduled for deep-brain stimulation surgery The pre-operative rate of malnutrition in a convenience sample of people with Parkinson's disease (PWP) scheduled for deep-brain stimulation (DBS) surgery was determined. Poorly controlled PD symptoms may result in a higher risk of malnutrition in this sub-group of PWP. Fifteen patients (11 male, median age 68.0 (42.0 – 78.0) years, median PD duration 6.75 (0.5 – 24.0) years) participated and data were collected during hospital admission for the DBS surgery. The scored PG-SGA was used to assess nutritional status, anthropometric measures (weight, height, mid-arm circumference, waist circumference, body mass index (BMI)) were taken, and body composition was measured using bioelectrical impedance spectroscopy (BIS). Six (40%) of the participants were malnourished (SGA-B) while 53% reported significant weight loss following diagnosis. BMI was significantly different between SGA-A and SGA-B (25.6 vs 23.0kg/m 2, p<.05). There were no differences in any other variables, including PG-SGA score and the presence of non-motor symptoms. The conclusion was that malnutrition in this group is higher than that in other studies reporting malnutrition in PWP, and it is under-recognised. As poorer surgical outcomes are associated with poorer pre-operative nutritional status in other surgeries, it might be beneficial to identify patients at nutritional risk prior to surgery so that appropriate nutrition interventions can be implemented. Phase I: Nutritional status in community-dwelling adults with Parkinson's disease The rate of malnutrition in community-dwelling adults (>18 years) with Parkinson's disease was determined. One hundred twenty-five PWP (74 male, median age 70.0 (35.0 – 92.0) years, median PD duration 6.0 (0.0 – 31.0) years) participated. The scored PG-SGA was used to assess nutritional status, anthropometric measures (weight, height, mid-arm circumference (MAC), calf circumference, waist circumference, body mass index (BMI)) were taken. Nineteen (15%) of the participants were malnourished (SGA-B). All anthropometric indices were significantly different between SGA-A and SGA-B (BMI 25.9 vs 20.0kg/m2; MAC 29.1 – 25.5cm; waist circumference 95.5 vs 82.5cm; calf circumference 36.5 vs 32.5cm; all p<.05). The PG-SGA score was also significantly lower in the malnourished (2 vs 8, p<.05). The nutrition impact symptoms which differentiated between well-nourished and malnourished were no appetite, constipation, diarrhoea, problems swallowing and feel full quickly. This study concluded that malnutrition in community-dwelling PWP is higher than that documented in community-dwelling elderly (2 – 11%), yet is likely to be under-recognised. Nutrition impact symptoms play a role in reduced intake. Appropriate screening and referral processes should be established for early detection of those at risk. Phase I: Nutrition assessment tools in people with Parkinson's disease There are a number of validated and reliable nutrition screening and assessment tools available for use. None of these tools have been evaluated in PWP. In the sample described above, the use of the World Health Organisation (WHO) cut-off (≤18.5kg/m2), age-specific BMI cut-offs (≤18.5kg/m2 for under 65 years, ≤23.5kg/m2 for 65 years and older) and the revised Mini-Nutritional Assessment short form (MNA-SF) were evaluated as nutrition screening tools. The PG-SGA (including the SGA classification) and the MNA full form were evaluated as nutrition assessment tools using the SGA classification as the gold standard. For screening, the MNA-SF performed the best with sensitivity (Sn) of 94.7% and specificity (Sp) of 78.3%. For assessment, the PG-SGA with a cut-off score of 4 (Sn 100%, Sp 69.8%) performed better than the MNA (Sn 84.2%, Sp 87.7%). As the MNA has been recommended more for use as a nutrition screening tool, the MNA-SF might be more appropriate and take less time to complete. The PG-SGA might be useful to inform and monitor nutrition interventions. Phase I: Predictors of poor nutritional status in people with Parkinson's disease A number of assessments were conducted as part of the Phase I research, including those for the severity of PD motor symptoms, cognitive function, depression, anxiety, non-motor symptoms, constipation, freezing of gait and the ability to carry out activities of daily living. A higher score in all of these assessments indicates greater impairment. In addition, information about medical conditions, medications, age, age at PD diagnosis and living situation was collected. These were compared between those classified as SGA-A and as SGA-B. Regression analysis was used to identify which factors were predictive of malnutrition (SGA-B). Differences between the groups included disease severity (4% more severe SGA-A vs 21% SGA-B, p<.05), activities of daily living score (13 SGA-A vs 18 SGA-B, p<.05), depressive symptom score (8 SGA-A vs 14 SGA-B, p<.05) and gastrointestinal symptoms (4 SGA-A vs 6 SGA-B, p<.05). Significant predictors of malnutrition according to SGA were age at diagnosis (OR 1.09, 95% CI 1.01 – 1.18), amount of dopaminergic medication per kg body weight (mg/kg) (OR 1.17, 95% CI 1.04 – 1.31), more severe motor symptoms (OR 1.10, 95% CI 1.02 – 1.19), less anxiety (OR 0.90, 95% CI 0.82 – 0.98) and more depressive symptoms (OR 1.23, 95% CI 1.07 – 1.41). Significant predictors of a higher PG-SGA score included living alone (β=0.14, 95% CI 0.01 – 0.26), more depressive symptoms (β=0.02, 95% CI 0.01 – 0.02) and more severe motor symptoms (OR 0.01, 95% CI 0.01 – 0.02). More severe disease is associated with malnutrition, and this may be compounded by lack of social support. Phase II: Nutrition intervention Nineteen of the people identified in Phase I as requiring nutrition support were included in Phase II, in which a nutrition intervention was conducted. Nine participants were in the standard care group (SC), which received an information sheet only, and the other 10 participants were in the intervention group (INT), which received individualised nutrition information and weekly follow-up. INT gained 2.2% of starting body weight over the 12 week intervention period resulting in significant increases in weight, BMI, mid-arm circumference and waist circumference. The SC group gained 1% of starting weight over the 12 weeks which did not result in any significant changes in anthropometric indices. Energy and protein intake (18.3kJ/kg vs 3.8kJ/kg and 0.3g/kg vs 0.15g/kg) increased in both groups. The increase in protein intake was only significant in the SC group. The changes in intake, when compared between the groups, were no different. There were no significant changes in any motor or non-motor symptoms or in "off" times or dyskinesias in either group. Aspects of quality of life improved over the 12 weeks as well, especially emotional well-being. This thesis makes a significant contribution to the evidence base for the presence of malnutrition in Parkinson's disease as well as for the identification of those who would potentially benefit from nutrition screening and assessment. The nutrition intervention demonstrated that a traditional high protein, high energy approach to the management of malnutrition resulted in improved nutritional status and anthropometric indices with no effect on the presence of Parkinson's disease symptoms and a positive effect on quality of life.

Higher order spectra based support vector machine for arrhythmia classification

Heart rate variability (HRV) refers to the regulation of the sinoatrial node, the natural pacemaker of the heart by the sympathetic and parasympathetic branches of the autonomic nervous system. HRV analysis is an important tool to observe the heart’s ability to respond to normal regulatory impulses that affect its rhythm. Like many bio-signals, HRV signals are non-linear in nature. Higher order spectral analysis (HOS) is known to be a good tool for the analysis of non-linear systems and provides good noise immunity. A computer-based arrhythmia detection system of cardiac states is very useful in diagnostics and disease management. In this work, we studied the identification of the HRV signals using features derived from HOS. These features were fed to the support vector machine (SVM) for classification. Our proposed system can classify the normal and other four classes of arrhythmia with an average accuracy of more than 85%.

The contribution of major depression to the global burden of ischemic heart disease : a comparative risk assessment

Background Cardiovascular disease and mental health both hold enormous public health importance, both ranking highly in results of the recent Global Burden of Disease Study 2010 (GBD 2010). For the first time, the GBD 2010 has systematically and quantitatively assessed major depression as an independent risk factor for the development of ischemic heart disease (IHD) using comparative risk assessment methodology. Methods A pooled relative risk (RR) was calculated from studies identified through a systematic review with strict inclusion criteria designed to provide evidence of independent risk factor status. Accepted case definitions of depression include diagnosis by a clinician or by non-clinician raters adhering to Diagnostic and Statistical Manual of Mental Disorders (DSM) or International Classification of Diseases (ICD) classifications. We therefore refer to the exposure in this paper as major depression as opposed to the DSM-IV category of major depressive disorder (MDD). The population attributable fraction (PAF) was calculated using the pooled RR estimate. Attributable burden was calculated by multiplying the PAF by the underlying burden of IHD estimated as part of GBD 2010. Results The pooled relative risk of developing IHD in those with major depression was 1.56 (95% CI 1.30 to 1.87). Globally there were almost 4 million estimated IHD disability-adjusted life years (DALYs), which can be attributed to major depression in 2010; 3.5 million years of life lost and 250,000 years of life lived with a disability. These findings highlight a previously underestimated mortality component of the burden of major depression. As a proportion of overall IHD burden, 2.95% (95% CI 1.48 to 4.46%) of IHD DALYs were estimated to be attributable to MDD in 2010. Eastern Europe and North Africa/Middle East demonstrate the highest proportion with Asia Pacific, high income representing the lowest. Conclusions The present work comprises the most robust systematic review of its kind to date. The key finding that major depression may be responsible for approximately 3% of global IHD DALYs warrants assessment for depression in patients at high risk of developing IHD or at risk of a repeat IHD event.

Osteopenia and rickets in the extremely low birth weight infant: A survey of the incidence and a radiological classification

A review was carried out of the radiographs of twenty-five infants with birth weights under 1000 G, who survived for more than twenty-eight days; eighteen of these had enough suitable films for a survey of the progressive bone changes which occur in these infants, including estimation of humeral cortical cross-sectional area. The incidence of the changes has been assessed and a typical progression of radiographic appearances has been shown, with a suggested system of staging. All infants showed some loss of bone mineral, with frank changes of rickets occurring in forty-four percent. Aetiological factors are mainly concerned with the difficulty of supplying and ensuring absorption of sufficient bone mineral (calcium and phosphate) and vitamin D. Liver immaturity may be another factor. Disease states additional to prematurity accentuate the problem. Rib fractures occurring around 80–90 days post-nataEy commonly draw attention to the bone disorder and are probably the major clinical factor of importance; there is a high incidence of associated lung disease of uncertain pathology. Attention is drawn to possible confusion with other bone disorders in the post-natal period.

Genetic burden associated with varying degrees of disease severity in endometriosis

Endometriosis is primarily characterized by the presence of tissue resembling endometrium outside the uterine cavity and is usually diagnosed by laparoscopy. The most commonly used classification of disease, the revised American Fertility Society (rAFS) system to grade endometriosis into different stages based on disease severity (I to IV), has been questioned as it does not correlate well with underlying symptoms, posing issues in diagnosis and choice of treatment. Using two independent European genome-wide association (GWA) datasets and top-level classification of the endometriosis cases based on rAFS [minimal or mild (Stage A) and moderate-to-severe (Stage B) disease], we previously showed that Stage B endometriosis has greater contribution of common genetic variation to its aetiology than Stage A disease. Herein, we extend our previous analysis to four endometriosis stages [minimal (Stage I), mild (Stage II), moderate (Stage III) and severe (Stage IV) disease] based on the rAFS classification system and compared the genetic burden across stages. Our results indicate that genetic burden increases from minimal to severe endometriosis. For the minimal disease, genetic factors may contribute to a lesser extent than other disease categories. Mild and moderate endometriosis appeared genetically similar, making it difficult to tease them apart. Consistent with our previous reports, moderate and severe endometriosis showed greater genetic burden than minimal or mild disease. Overall, our results provide new insights into the genetic architecture of endometriosis and further investigation in larger samples may help to understand better the aetiology of varying degrees of endometriosis, enabling improved diagnostic and treatment modalities.

Weather variability, tides, and Barmah Forest Virus Disease in the Gladstone region, Australia

In this study we examined the impact of weather variability and tides on the transmission of Barmah Forest virus (BFV) disease and developed a weather-based forecasting model for BFV disease in the Gladstone region, Australia. We used seasonal autoregressive integrated moving-average (SARIMA) models to determine the contribution of weather variables to BFV transmission after the time-series data of response and explanatory variables were made stationary through seasonal differencing. We obtained data on the monthly counts of BFV cases, weather variables (e.g., mean minimum and maximum temperature, total rainfall, and mean relative humidity), high and low tides, and the population size in the Gladstone region between January 1992 and December 2001 from the Queensland Department of Health, Australian Bureau of Meteorology, Queensland Department of Transport, and Australian Bureau of Statistics, respectively. The SARIMA model shows that the 5-month moving average of minimum temperature (β = 0.15, p-value < 0.001) was statistically significantly and positively associated with BFV disease, whereas high tide in the current month (β = −1.03, p-value = 0.04) was statistically significantly and inversely associated with it. However, no significant association was found for other variables. These results may be applied to forecast the occurrence of BFV disease and to use public health resources in BFV control and prevention.