Unusual Presentation of Brain Aspergillosis in Chronic Granulomatous Disease

Aspergillus is a frequently observed pathogen in patients with chronic granulomatous disease. We report on a patient with chronic granulomatous disease and severe brain aspergillosis with an unusual presentation and favorable course. We discuss the impact of this infection on morbidity and mortality, adequate therapeutic management, and the need to investigate a possible fungal infection, despite nonspecific signs. (C) 2010 by Elsevier Inc. All rights reserved.

Hematologically important mutations: X-linked chronic granulomatous disease (third update)

Chronic granulomatous disease (CGD) is an immunodeficiency disorder affecting about 1 in 250,000 individuals. The disease is caused by a lack of superoxide production by the leukocyte enzyme NADPH oxidase. Superoxide is used to kill phagocytosed micro-organisms in neutrophils, eosinophils, monocytes and macrophages. The leukocyte NADPH oxidase is composed of five subunits, of which the enzymatic component is gp91-phox, also called Nox2. This protein is encoded by the CYBB gene on the X chromosome. Mutations in this gene are found in about 70% of all CGD patients. This article lists all mutations identified in CYBB in the X-linked form of CGD. Moreover, apparently benign polymorphisms in CYBB are also given, which should facilitate the recognition of future disease-causing mutations. (C) 2010 Elsevier Inc. All rights reserved.

Predictive models for chronic renal disease using decision trees, naïve bayes and case-based methods

Data mining can be used in healthcare industry to “mine” clinical data to discover hidden information for intelligent and affective decision making. Discovery of hidden patterns and relationships often goes intact, yet advanced data mining techniques can be helpful as remedy to this scenario. This thesis mainly deals with Intelligent Prediction of Chronic Renal Disease (IPCRD). Data covers blood, urine test, and external symptoms applied to predict chronic renal disease. Data from the database is initially transformed to Weka (3.6) and Chi-Square method is used for features section. After normalizing data, three classifiers were applied and efficiency of output is evaluated. Mainly, three classifiers are analyzed: Decision Tree, Naïve Bayes, K-Nearest Neighbour algorithm. Results show that each technique has its unique strength in realizing the objectives of the defined mining goals. Efficiency of Decision Tree and KNN was almost same but Naïve Bayes proved a comparative edge over others. Further sensitivity and specificity tests are used as statistical measures to examine the performance of a binary classification. Sensitivity (also called recall rate in some fields) measures the proportion of actual positives which are correctly identified while Specificity measures the proportion of negatives which are correctly identified. CRISP-DM methodology is applied to build the mining models. It consists of six major phases: business understanding, data understanding, data preparation, modeling, evaluation, and deployment.

Association between levels of pentraxin 3 and incidence of chronic kidney disease in the elderly

OBJECTIVE: Higher levels of the novel inflammatory marker pentraxin 3 (PTX3) predict cardiovascular mortality in patients with chronic kidney disease (CKD). Yet, whether PTX3 predicts worsening of kidney function has been less well studied. We therefore investigated the associations between PTX3 levels, kidney disease measures and CKD incidence. METHODS: Cross-sectional associations between serum PTX3 levels, urinary albumin/creatinine ratio (ACR) and cystatin C-estimated glomerular filtration rate (GFR) were assessed in two independent community-based cohorts of elderly subjects: the Prospective Investigation of the Vasculature in Uppsala Seniors (PIVUS, n = 768, 51% women, mean age 75 years) and the Uppsala Longitudinal Study of Adult Men (ULSAM, n = 651, mean age 77 years). The longitudinal association between PTX3 level at baseline and incident CKD (GFR <60 mL( ) min(-1)  1.73 m(-) ²) was also analysed (number of events/number at risk: PIVUS 229/746, ULSAM 206/315). RESULTS: PTX3 levels were inversely associated with GFR [PIVUS: B-coefficient per 1 SD increase -0.16, 95% confidence interval (CI) -0.23 to -0.10, P < 0.001; ULSAM: B-coefficient per 1 SD increase -0.09, 95% CI -0.16 to -0.01, P < 0.05], but not ACR, after adjusting for age, gender, C-reactive protein and prevalent cardiovascular disease in cross-sectional analyses. In longitudinal analyses, PTX3 levels predicted incident CKD after 5 years in both cohorts [PIVUS: multivariable odds ratio (OR) 1.21, 95% CI 1.01-1.45, P < 0.05; ULSAM: multivariable OR 1.37, 95% CI 1.07-1.77, P < 0.05]. CONCLUSIONS: Higher PTX3 levels are associated with lower GFR and independently predict incident CKD in elderly men and women. Our data confirm and extend previous evidence suggesting that inflammatory processes are activated in the early stages of CKD and drive impairment of kidney function. Circulating PTX3 appears to be a promising biomarker of kidney disease.

Comorbidity of cardiovascular disease, diabetes and chronic kidney disease in Australia

This is the first report of a projected series regarding the comorbidity of cardiovascular disease (CVD), diabetes and chronic kidney disease (CKD) in Australia. Comorbidity refers to any two or more of these diseases that occur in one person at the same time. The questions to be answered in this report include: 1. How many Australians have comorbidity of CVD, diabetes and CKD? 2. What is the proportion of hospitalisations with these comorbidities? 3. How much do these comorbidities contribute to deaths? 4. What is the magnitude of comorbidity in the context of each individual disease? 5. Are there differences in the distribution of these comorbidities among age groups and sexes?

Self-management programmes in stages 1–4 chronic kidney disease: a literature review

Background
Chronic kidney disease (CKD) is a complex health problem, which requires individuals to invest considerable time and energy in managing their health and adhering to multifaceted treatment regimens.

Objectives
To review studies delivering self-management interventions to people with CKD (Stages 1–4) and assess whether these interventions improve patient outcomes.

Design
Systematic review.

Methods
Nine electronic databases (MedLine, CINAHL, EMBASE, ProQuest Health & Medical Complete, ProQuest Nursing & Allied Health, The Cochrane Library, The Joanna Briggs Institute EBP Database, Web of Science and PsycINFO) were searched using relevant terms for papers published between January 2003 and February 2013.

Results
The search strategy identified 2,051 papers, of which 34 were retrieved in full with only 5 studies involving 274 patients meeting the inclusion criteria. Three studies were randomised controlled trials, a variety of methods were used to measure outcomes, and four studies included a nurse on the self-management intervention team. There was little consistency in the delivery, intensity, duration and format of the self-management programmes. There is some evidence that knowledge- and health-related quality of life improved. Generally, small effects were observed for levels of adherence and progression of CKD according to physiologic measures.

Conclusion
The effectiveness of self-management programmes in CKD (Stages 1–4) cannot be conclusively ascertained, and further research is required. It is desirable that individuals with CKD are supported to effectively self-manage day-to-day aspects of their health.