Ankylosing spondylitis patients commencing biologic therapy have high baseline levels of comorbidity: a report from the Australian Rheumatology Association Database

Aims: To compare the baseline characteristics of a population-based cohort of patients with ankylosing spondylitis (AS) commencing biological therapy to the reported characteristics of bDMARD randomised controlled trials (RCTs) participants.
Methods: Descriptive analysis of AS participants in the Australian Rheumatology Association Database (ARAD) who were commencing bDMARD therapy.
Results: Up to December 2008, 389 patients with AS were enrolled in ARAD. 354 (91.0%) had taken bDMARDs at some time, and 198 (55.9%) completed their entry questionnaire prior to or within 6 months of commencing bDMARDs. 131 (66.1%) had at least one comorbid condition, and 24 (6.8%) had a previous malignancy (15 nonmelanoma skin, 4 melanoma, 2 prostate, 1 breast, cervix, and bowel). Compared with RCT participants, ARAD participants were older, had longer disease duration and higher baseline disease activity.
Conclusions: AS patients commencing bDMARDs in routine care are significantly different to RCT participants and have significant baseline comorbidities.

Baseline comorbidities in a population-bases cohort of rheumatoid arthritis patients receiving biological therapy: data from the Australian Rheumatology Association database

Aims: To describe the baseline characteristics of an Australian population-based cohort of rheumatoid arthritis (RA) patients commencing biological therapy.

Methods: Descriptive analysis from the Australian Rheumatology Association Database (ARAD).

Results: Up to October 2006, there were 681 RA patients taking biologics enrolled in ARAD. Baseline data were available for 624 (72% female, mean (SD) age 57.0 (12.5) years). Of these, 59.5% reported at least one comorbid condition, most commonly hypertension (35.7%) and osteoporosis (30.4%); 61 (9.8%) had a history of malignancy (35 nonmelanoma skin, 5 breast, 4 bowel, 5 cervix, 3 melanoma, 3 prostate and 1 each of lip, lung, myeloma, testis, uterus, vagina). Self-reported infections within the previous 6 months were common (71.5%).

Conclusions: History of comorbidities, including recent infections, is common among Australian RA patients commencing biologics, and 10% have a history of malignancy. This may impact future evaluations of health outcomes among this population, including attribution of adverse events of biologic therapy.

Hierarchical development of training database for artificial neural network-based damage identification

Though serving as an effective means for damage identification, the capability of an artificial neural network (ANN) for quantitative prediction is substantially dependent on the amount of training data. In virtue of a concept of “Digital Damage Fingerprints” (DDF), a hierarchical approach for the development of training databases was proposed for ANN-based damage identification. With the object of exploiting the capability of ANN to address the key questions: “Is there damage?” and “Where is the damage?”, the amount of training data (damage cases) was increased progressively. Mutuality was established between the quantity of training data and the accuracy of answers to the two questions of interest, and was experimentally validated by identifying the position of actual damage in carbon fibre-reinforced composite laminates. The results demonstrate that such a hierarchical approach is capable of offering prediction as to the presence and location of damage individually, with substantially reduced computational cost and effort in the development of the ANN training database.

Permanent genetic resources added to molecular ecology resources database 1 August 2010 – 30 September 2010

This article documents the addition of 229 microsatellite marker loci to the Molecular Ecology Resources Database. Loci were developed for the following species: Acacia auriculiformis · Acacia mangium hybrid, Alabama argillacea, Anoplopoma fimbria, Aplochiton zebra, Brevicoryne brassicae, Bruguiera gymnorhiza, Bucorvus leadbeateri, Delphacodes detecta, Tumidagena minuta, Dictyostelium giganteum, Echinogammarus berilloni, Epimedium sagittatum, Fraxinus excelsior, Labeo chrysophekadion, Oncorhynchus clarki lewisi, Paratrechina longicornis, Phaeocystis antarctica, Pinus roxburghii and Potamilus capax. These loci were cross-tested on the following species: Acacia peregrinalis, Acacia crassicarpa, Bruguiera cylindrica, Delphacodes detecta, Tumidagena minuta, Dictyostelium macrocephalum, Dictyostelium discoideum, Dictyostelium purpureum, Dictyostelium mucoroides, Dictyostelium rosarium, Polysphondylium pallidum, Epimedium brevicornum, Epimedium koreanum, Epimedium pubescens, Epimedium wushanese and Fraxinus angustifolia.

Restrictive interventions for people with a disability exhibiting challenging behaviours : analysis of a population database

Background: People with an intellectual disability whose behaviours are perceived to be of serious harm to themselves or others are at risk of being subjected to restrictive interventions. Prevalence rates are difficult to determine, as most research is unable to draw on the results of population-level data.

Method: The current study reports on the use of chemical and mechanical restraint and seclusion in the State of Victoria, Australia, over a 12-month period.

Results: The majority of people included were subjected to chemical restraint. The use of restraint was found to be routine rather than a strategy of last resort. Consistent with findings in the UK and USA, those subjected to restrictive interventions were more likely to be young males with multiple disabilities, including autism.

Conclusions: Systemic policy and procedural developments are needed to address current use of restrictive interventions, together with a longitudinal study to evaluate the effectiveness, of alternative, non-restrictive strategies.

Small rural hospital emergency department database

This data includes activity and performance data from the emergency departments at the local hospitals (Rural Category Three Public Health Services) in the Southwest region of Victoria.

Bird biometrics condition and disease database

Contains biometric measurements (tarsus length, bill length, total head length, body mass) of birds caught at various locations in Australia (though mainly South Australia and Victoria), including data on the viral (mainly Avian Influenza Virus) analysis of cloacal and oropharyngeal swabs, serology of sera samples, and additional data on metabolites and parasite prevalence in swabs, blood cells and sera. Approximately 1500 birds (mainly waterbirds) are sampled annually.

Greater Green Triangle diabetes prevention project database

Data includes anthropometric and laboratory (lipid profile, glucose) measurements, and self-reported questionnaires including demographics, self-efficacy, social support, psychological well being (HADS, K10, SF-36 v2), diet (three-day food diaries, food frequency questionnaire), physical activity (seven-day diary, Active Australia Survey), smoking, and alcohol consumption. Most data is measured at baseline, 3 months, 12 months, and 30 months. Some blood samples are still stored at -80 degrees Celsius.

Geelong Osteoporosis Study Health Database

The database contains the following clinical, questionnaire and socio-demographic data suitable for cross-sectional and longitudinal analyses:
-Body composition: dual-energy x-ray absorptiometry (DXA) measures of the lumbar spine (posterior-anterior projection), proximal femur, whole body and forearm (ultradistal forearm and distal 33%)
-Other clinical assessments: body weight, height, arm span, waist and hip circumferences, blood pressure, visual acuity, muscle strength, functional reach test and timed ‘up-&-go’ test.
-Mental health: Major axis psychiatric disorders diagnosed using a Structured Clinical Interview.
-Blood and urine collections: blood and urine collected after an overnight fast.
-Questionnaires: exposure to disease, use of medications and supplements, diet, mobility, physical activity, sleep, sun exposure, falls and fractures, alcohol and tobacco use, reproductive history, family history of fractures and disease, quality of life, pain, anxiety and depression.
-Socio-demographics: Country of birth, ethnicity, marital status, education, housing and employment status, occupation, socioeconomic Index for Areas (SEIFA) scores.