The impact of an electronic clinical decision support for pulmonary embolism imaging on the efficiency of computed tomography pulmonary angiography utilisation in a resource-limited setting

Background. Pulmonary embolism (PE) is associated with high morbidity and mortality. Effective intervention requires prompt diagnosis. Computed tomography pulmonary angiography (CTPA) is sensitive and specific for PE and is the investigation of choice. Inappropriate CTPA utilisation results in unnecessary high radiation exposure and is costly. State-of-the-art electronic radiology workflow can provide clinical decision support (CDS) for specialised imaging requests, but there has been limited work on the clinical impact of CDS in PE, particularly in resource-constrained environments.Objective. To determine the impact of an electronic CDS for PE on the efficiency of CTPA utilisation in a resource-limited setting.Methods. In preparation, a PE diagnostic algorithm was distributed to hospital clinicians, explaining the combined role of the validated modified Wells score and the quantitative D-dimer test in defining the pre-test probability of PE. Thereafter, an automated, electronic CDS was introduced for all CTPA requests. Total CTPA referrals and the proportion positive for PE were assessed for three study phases: (i) prediagnostic algorithm; (ii) post-algorithm, pre-CDS; and (iii) post-CDS.Results. The proportion of CTPAs positive for PE after CDS implementation was almost double that prior to introduction of the diagnostic algorithm (phase 1 v. 3, 17.4% v. 30.7%; p=0.036), with a correspondingly significant decrease in the proportion of non-positive CTPAs (phases 1 v. 3, 82.6% v. 69.3%; p=0.015) During phases 2 and 3, no CTPAs were requested for patients with a modified Wells score of ≤4 and a documented negative D-dimer, indicating adherence to the algorithm.Conclusion. Implementing an electronic CDS for PE significantly increased the efficiency of CTPA utilisation and significantly decreased the proportion of inappropriate scans

The X-ray spectrum of the Seyfert I galaxy Markarian 766: Dusty warm absorber or relativistic emission lines?

Competing models for broad spectral features in the soft X-ray spectrum of the Seyfert I galaxy Mrk 766 are tested against data from a 130 ks XMM-Newton observation. A model including relativistically broadened Lyalpha emission lines of O VIII N VII and C VI is a better fit to 0.3-2 keV XMM RGS data than a dusty warm absorber. Moreover, the measured depth of neutral iron absorption lines in the spectrum is inconsistent with the magnitude of the iron edge required to produce the continuum break at 17-18 Angstrom in the dusty warm absorber model. The relativistic emission line model can reproduce the broadband (0.1-12 keV) XMM EPIC data with the addition of a fourth line to represent emission from ionized iron at 6.7 keV and an excess due to reflection at energies above the iron line. The pro le of the 6.7 keV iron line is consistent with that measured for the low-energy lines. There is evidence in the RGS data, at the 3sigma level, of spectral features that vary with source flux. The covering fraction of warm absorber gas is estimated to be 12%. Iron in the warm absorber is found to be overabundant with respect to CNO, compared to solar values

Probabilistic Analysis of Optimization Problems on Generalized Random Shortest Path Metrics

Simple heuristics often show a remarkable performance in practice for optimization problems. Worst-case analysis often falls short of explaining this performance. Because of this, "beyond worst-case analysis" of algorithms has recently gained a lot of attention, including probabilistic analysis of algorithms. The instances of many optimization problems are essentially a discrete metric space. Probabilistic analysis for such metric optimization problems has nevertheless mostly been conducted on instances drawn from Euclidean space, which provides a structure that is usually heavily exploited in the analysis. However, most instances from practice are not Euclidean. Little work has been done on metric instances drawn from other, more realistic, distributions. Some initial results have been obtained by Bringmann et al. (Algorithmica, 2013), who have used random shortest path metrics on complete graphs to analyze heuristics. The goal of this paper is to generalize these findings to non-complete graphs, especially Erd\H{o}s-R\'enyi random graphs. A random shortest path metric is constructed by drawing independent random edge weights for each edge in the graph and setting the distance between every pair of vertices to the length of a shortest path between them with respect to the drawn weights. For such instances, we prove that the greedy heuristic for the minimum distance maximum matching problem, the nearest neighbor and insertion heuristics for the traveling salesman problem, and a trivial heuristic for the $k$-median problem all achieve a constant expected approximation ratio. Additionally, we show a polynomial upper bound for the expected number of iterations of the 2-opt heuristic for the traveling salesman problem.Comment: An extended abstract appeared in the proceedings of WALCOM 201

Automatic quantitative analysis of experimental primary and secondary retinal neurodegeneration: implications for optic neuropathies.

Secondary neurodegeneration is thought to play an important role in the pathology of neurodegenerative disease, which potential therapies may target. However, the quantitative assessment of the degree of secondary neurodegeneration is difficult. The present study describes a novel algorithm from which estimates of primary and secondary degeneration are computed using well-established rodent models of partial optic nerve transection (pONT) and ocular hypertension (OHT). Brn3-labelled retinal ganglion cells (RGCs) were identified in whole-retinal mounts from which RGC density, nearest neighbour distances and regularity indices were determined. The spatial distribution and rate of RGC loss were assessed and the percentage of primary and secondary degeneration in each non-overlapping segment was calculated. Mean RGC number (82 592±681) and RGC density (1695±23.3 RGC/mm(2)) in naïve eyes were comparable with previous studies, with an average decline in RGC density of 71±17 and 23±5% over the time course of pONT and OHT models, respectively. Spatial analysis revealed greatest RGC loss in the superior and central retina in pONT, but significant RGC loss in the inferior retina from 3 days post model induction. In comparison, there was no significant difference between superior and inferior retina after OHT induction, and RGC loss occurred mainly along the superior/inferior axis (~30%) versus the nasal-temporal axis (~15%). Intriguingly, a significant loss of RGCs was also observed in contralateral eyes in experimental OHT. In conclusion, a novel algorithm to automatically segment Brn3a-labelled retinal whole-mounts into non-overlapping segments is described, which enables automated spatial and temporal segmentation of RGCs, revealing heterogeneity in the spatial distribution of primary and secondary degenerative processes. This method provides an attractive means to rapidly determine the efficacy of neuroprotective therapies with implications for any neurodegenerative disorder affecting the retina

Formal Methods in Industrial Practice:Bridging the Gap (Track Summary)

Already for many decades, formal methods are considered to be the way forward to help the software industry to make more reliable and trustworthy software. However, despite this strong belief, and many individual success stories, no real change in industrial software development seems to happen. In fact, the software industry is moving fast forward itself, and the gap between what formal methods can achieve, and the daily software development practice does not seem to get smaller (and might even be growing)

Critical Innovations in the UK Peer-to-Peer (P2P) and Equity Alternative Finance Markets for Small Firm Growth

© The Author(s) 2016. The final, definitive version of this paper has been published in The International Journal of Entrepreneurship and Innovation by Sage Publications Ltd. All rights reserved. It is available at: https://doi.org/10.1177/1465750316655906This paper examines the disruptive nature of financial innovations available to small firms by the growing range of online platforms that have emerged in the UK since the financial crisis. It is unveiled that finance provided to small firms via such mechanisms is not identical to more traditional sources and its adoption therefore cannot be said to be simply a question of direct substitution based, for example, on a price comparison. These offer a series of important advantages over more traditional sources of early-stage capital for entrepreneurs seeking funding. Service innovations around security, flexibility of terms, speed of access and transparency of pricing are as important as price considerations for many users, as are innovations made possible by the way these online markets are structured and in particular in the way these innovative structures allow important types of risk to be dispersed and mitigated.Peer reviewedFinal Accepted Versio

A note on the use of sensitivity analysis to explore the potential impact of declining institutional care utilisation on disability prevalence

Many health and disability surveys are conducted using the non-institutionalised population as a sampling frame. Consequently, it is possible that changes in the utilisation of institutional care could account for all or part of any change in the observed prevalence of functional limitation, disability or other health state, based on samples from the non-institutionalised population. Using conditional probability arguments, I present an adjustment formula for computing health state prevalences for the non-institutionalised population under a scenario in which health state prevalences are held constant except for movement into the non-institutionalised population of individuals who would formerly have been in institutional care. By comparing the adjusted prevalence with observed non-institutionalised health state prevalences the contribution of changes in institutionalisation to observed changes in the non-institutionalised health state prevalence can be assessed

Glaucoma Rose Plot Analysis: detecting early structural progression using angular histograms

Purpose To evaluate the novel Rose Plot Analysis (RPA) in the analysis and presentation of glaucoma structural progression data. Design Case-control image analysis study using retrospective retinal imaging series. Subjects Subjects with open-angle glaucoma with at least 5 registered spectral-domain OCT scans. Methods Glaucoma RPA was developed, combining a novel application of angular histograms and dynamic cluster analysis of circumpapillary retinal nerve fiber layer (cRNFL) OCT data. Rose Plot Analysis plots were created for each eye and each visit. Significant clusters of progression were indicated in red. Three masked clinicians categorized all RPA plots (progressing, not progressing), in addition to measuring the significant RPA area. A masked OCT series assessment with linear regression of averaged global and sectoral cRNFL thicknesses was conducted as the clinical imaging standard. Main Outcome Measures Interobserver agreement was compared between RPA and the clinical imaging standard. Discriminative ability was assessed using receiver-operating characteristic curves. The time to detection of progression was compared using a Kaplan–Meier survival analysis, and the agreement of RPA with the clinical imaging standard was calculated. Results Seven hundred fourty-three scans from 98 eyes were included. Interobserver agreement was significantly greater when categorizing RPA (κ, 0.86; 95% confidence interval [CI], 0.81–0.91) compared with OCT image series (κ, 0.66; 95% CI, 0.54–0.77). The discriminative power of RPA to differentiate between eyes that were progressing and not progressing (area under the curve [AUC], 0.97; 95% CI, 0.92–1.00) was greater than that of global cRNFL thickness (AUC, 0.71; 95% CI, 0.59–0.82; P < 0.0001) and equivalent to that of sectoral cRNFL regression (AUC, 0.97; 95% CI, 0.92–1.00). A Kaplan–Meier survival analysis showed that progression was detected 8.7 months sooner by RPA than by global cRNFL linear regression (P < 0.0001) in progressing eyes but was not sooner than with sectoral cRNFL (P = 0.06). Rose Plot Analysis showed substantial agreement with the presence of significant thinning on sectoral cRNFL linear regression (κ, 0.715; 95% CI, 0.578–0.853). Conclusions Rose Plot Analysis has been shown to provide accurate and intuitive, at-a-glance data analysis and presentation that improve interobserver agreement and may aid early diagnosis of glaucomatous disease progression

Annexins in glaucoma

Glaucoma is one of the leading causes of irreversible visual loss, which has been estimated to affect 3.5% of those over 40 years old and projected to affect a total of 112 million people by 2040. Such a dramatic increase in affected patients demonstrates the need for continual improvement in the way we diagnose and treat this condition. Annexin A5 is a 36 kDa protein that is ubiquitously expressed in humans and is studied as an indicator of apoptosis in several fields. This molecule has a high calcium-dependent affinity for phosphatidylserine, a cell membrane phospholipid externalized to the outer cell membrane in early apoptosis. The DARC (Detection of Apoptosing Retinal Cells) project uses fluorescently-labelled annexin A5 to assess glaucomatous degeneration, the inherent process of which is the apoptosis of retinal ganglion cells. Furthermore, this project has conducted investigation of the retinal apoptosis in the neurodegenerative conditions of the eye and brain. In this present study, we summarized the use of annexin A5 as a marker of apoptosis in the eye. We also relayed the progress of the DARC project, developing real-time imaging of retinal ganglion cell apoptosis in vivo from the experimental models of disease and identifying mechanisms underlying neurodegeneration and its treatments, which has been applied to the first human clinical trials. DARC has potential as a biomarker in neurodegeneration, especially in the research of novel treatments, and could be a useful tool for the diagnosis and monitoring of glaucoma