A Stepped-Wedge Cluster-Randomized Trial to Improve Adherence to Evidence-Based Practices for Acute Stroke Management.

BACKGROUND: There is limited evidence regarding the optimal design and composition of multifaceted quality improvement programs to improve acute stroke care. The researchers aimed to test the effectiveness of a co-designed multifaceted intervention (STELAR: Shared Team Efforts Leading to Adherence Results) directed at hospital clinicians for improving acute stroke care tailored to the local context using feedback of national registry indicator data. METHODS: STELAR was a stepped-wedge cluster trial (partial randomization) using routinely collected Australian Stroke Clinical Registry data from Victorian hospitals segmented in two-month blocks. Each hospital (cluster) contributed control data from May 2017 and data for the intervention phase from July 2017 until September 2018. The intervention was multifaceted, delivered predominantly in two educational outreach workshops by experienced, external improvement facilitators, consisting of (1) feedback of registry data to identify practice gaps and (2) interprofessional education, barrier assessment, and documentation of an agreed action plan initiated by local clinical leaders appointed as change champions for prioritized clinical indicators. The researchers provided additional outreach support by e-mail/telephone for two months. Multilevel, multivariable regression models were used to assess change in a composite outcome of indicators selected for actions plans (primary outcome) and individual indicators (secondary outcome). Patient survival and disability 90-180 days after stroke were also compared. RESULTS: Nine hospitals (clusters) participated, and 144 clinicians attended 18 intervention workshops. The control phase included 1,001 patients (median age 76.7 years; 47.4% female, 64.7% ischemic stroke), and the intervention phase 2,146 patients (median age 74.9 years; 44.2% female, 73.8% ischemic stroke). Compared to the control phase, the median score for the composite outcome for the intervention phase was 17% greater for the indicators included in the hospitals' action plans (range 3% to 30%, p = 0.016) and overall for the 10 indicators 6% greater (range 3% to 10%, p < 0.001). Compared to the control phase, patients in the intervention phase more often received stroke unit care (odds ratio [OR] 1.39, 95% confidence interval [CI] 1.05-1.84), were discharged on antithrombotic medications (OR 1.87, 95% CI 1.50-2.33), and received a discharge care plan (OR 1.27, 95% CI 1.05-1.53). Patient outcomes were unchanged. CONCLUSION: External quality improvement facilitation using workshops and remote support, aligned with routine monitoring via registries, can improve acute stroke care.

COVID-19 Pandemic Impact on Care for Stroke in Australia: Emerging Evidence From the Australian Stroke Clinical Registry.

We present information on acute stroke care for the first wave of the COVID-19 pandemic in Australia using data from the Australian Stroke Clinical Registry (AuSCR). The first case of COVID-19 in Australia was recorded in late January 2020 and national restrictions to control the virus commenced in March. To account for seasonal effects of stroke admissions, patient-level data from the registry from January to June 2020 were compared to the same period in 2019 (historical-control) from 61 public hospitals. We compared periods using descriptive statistics and performed interrupted time series analyses. Perceptions of stroke clinicians were obtained from 53/72 (74%) hospitals participating in the AuSCR (80% nurses) via a voluntary, electronic feedback survey. Survey data were summarized to provide contextual information for the registry-based analysis. Data from the registry covered locations that had 91% of Australian COVID-19 cases to the end of June 2020. For the historical-control period, 9,308 episodes of care were compared with the pandemic period (8,992 episodes). Patient characteristics were similar for each cohort (median age: 75 years; 56% male; ischemic stroke 69%). Treatment in stroke units decreased progressively during the pandemic period (control: 76% pandemic: 70%, p < 0.001). Clinical staff reported fewer resources available for stroke including 10% reporting reduced stroke unit beds. Several time-based metrics were unchanged whereas door-to-needle times were longer during the peak pandemic period (March-April, 2020; 82 min, control: 74 min, p = 0.012). Our data emphasize the need to maintain appropriate acute stroke care during times of national emergency such as pandemic management.

Diabetic retinopathy in pregnancy: a review.

The prevalence of diabetes in pregnancy is increasing. Pre-existing diabetes is present in 1 in 167 pregnancies in Australia, divided equally between type 1 and type 2 diabetes. Diabetic retinopathy is a leading cause of blindness in women during their childbearing years, and pregnancy increases the short-term risk of diabetic retinopathy progression. We examine the risk factors for progression of diabetic retinopathy during pregnancy including duration of diabetes, baseline level of retinopathy, level of glycaemic control and hypertension. We also examine current screening and management guidelines and their levels of evidence, current treatment options for diabetic retinopathy and avenues for further research.

Diabetic Macular Edema at the time of Cataract Surgery trial: a prospective, randomized clinical trial of intravitreous bevacizumab versus triamcinolone in patients with diabetic macular oedema at the time of cataract surgery - preliminary 6 month results.

BACKGROUND: To compare visual and anatomical outcomes between intravitreous bevacizumab (BVB, Avastin) and triamcinolone (TA, Triesence) when administered at the time of cataract surgery in patients with diabetic macular oedema (DME). DESIGN: Prospective, single-masked, randomized clinical trial at The Royal Victorian Eye and Ear Hospital, Melbourne. PARTICIPANTS: Patients with clinically significant cataract and either centre-involving DME or DME treated within the previous 24 months. METHODS: Participants were randomized 1:1 to receive intravitreous BVB 1.25 mg or TA 4 mg during cataract surgery, and at subsequent review if required over 6 months. MAIN OUTCOME MEASURES: Change in central macular thickness (CMT) and best corrected visual acuity at 6 months. RESULTS: Forty-one patients (mean age 66.4 years, 73.2% male) were recruited. Visual acuity and CMT were similar between groups at baseline (P > 0.2).After six months, both groups gained vision (mean +21.4 letters in TA group P < 0.0001, +12.5 letters in BVB, P = 0.002), with no significant difference between groups (P = 0.085). In addition, 60.9% of eyes receiving TA achieved a VA of ≥6/12 compared to 73.3% in the BVB group (P = 0.501). However, only TA was associated with a sustained reduction in CMT (-43.8-µm reduction TA vs. +37.3-µm increase BVB, P = 0.006 over 6 months). Following surgery, additional injections were required in 70.6% of participants in the BVB group, compared to 16.7% in the TA group (P < 0.0001). Three patients in the TA group experienced a rise of IOP over 21 mmHg (12.5%) during the 6-month follow-up; BVB had no cases (P = 0.130). There were no cases of endophthalmitis in either group. CONCLUSIONS: When administered at the time of cataract surgery in patients with DME, at 6 months both TA and BVB improve visual acuity; however, only TA results in a sustained reduction in CMT. Further follow-up will determine whether this translates into better long-term visual outcomes in the TA group.

A lock-and-key model for protein-protein interactions.

MOTIVATION: Protein-protein interaction networks are one of the major post-genomic data sources available to molecular biologists. They provide a comprehensive view of the global interaction structure of an organism's proteome, as well as detailed information on specific interactions. Here we suggest a physical model of protein interactions that can be used to extract additional information at an intermediate level: It enables us to identify proteins which share biological interaction motifs, and also to identify potentially missing or spurious interactions. RESULTS: Our new graph model explains observed interactions between proteins by an underlying interaction of complementary binding domains (lock-and-key model). This leads to a novel graph-theoretical algorithm to identify bipartite subgraphs within protein-protein interaction networks where the underlying data are taken from yeast two-hybrid experimental results. By testing on synthetic data, we demonstrate that under certain modelling assumptions, the algorithm will return correct domain information about each protein in the network. Tests on data from various model organisms show that the local and global patterns predicted by the model are indeed found in experimental data. Using functional and protein structure annotations, we show that bipartite subnetworks can be identified that correspond to biologically relevant interaction motifs. Some of these are novel and we discuss an example involving SH3 domains from the Saccharomyces cerevisiae interactome. AVAILABILITY: The algorithm (in Matlab format) is available (see http://www.maths.strath.ac.uk/~aas96106/lock_key.html).

GeneRank: using search engine technology for the analysis of microarray experiments.

BACKGROUND: Interpretation of simple microarray experiments is usually based on the fold-change of gene expression between a reference and a "treated" sample where the treatment can be of many types from drug exposure to genetic variation. Interpretation of the results usually combines lists of differentially expressed genes with previous knowledge about their biological function. Here we evaluate a method--based on the PageRank algorithm employed by the popular search engine Google--that tries to automate some of this procedure to generate prioritized gene lists by exploiting biological background information. RESULTS: GeneRank is an intuitive modification of PageRank that maintains many of its mathematical properties. It combines gene expression information with a network structure derived from gene annotations (gene ontologies) or expression profile correlations. Using both simulated and real data we find that the algorithm offers an improved ranking of genes compared to pure expression change rankings. CONCLUSION: Our modification of the PageRank algorithm provides an alternative method of evaluating microarray experimental results which combines prior knowledge about the underlying network. GeneRank offers an improvement compared to assessing the importance of a gene based on its experimentally observed fold-change alone and may be used as a basis for further analytical developments.