3,632 research outputs found
Does Unemployment Influence Mass Shootings on the USA
Soumita Banerjee and Philip Maymin's poster examining the potential relationship between mass shootings and unemployment
Proliferative Vitreoretinopathy; strategies to improve anatomical and visual outcomes
Proliferative vitreoretinopathy (PVR) is the most common cause of late anatomical failure of retinal detachment surgery. Efforts to modify this vitreoretinal scarring response have so far proved clinically unsuccessful, with surgical and visual outcomes remaining poor. This work is aimed at identifying strategies to improve outcomes in eyes at high risk of PVR development following open globe trauma (OGT), and those with established PVR disease. Two prospective clinical trials investigating the benefit of adjunctive corticosteroids in these two populations were conducted in a total of one hundred and eighty patients. Clinical and imaging data were collected over the course of approximately 3500 hospital attendances. The Adjunct in Ocular Trauma (AOT) Trial was a two year, pilot, single-centre prospective, participant and surgeon-masked randomized-controlled-clinical trial (RCT). Forty patients requiring vitrectomy surgery following OGT were randomized to either standard (control) or study treatment (adjuncts) in a 1:1 allocation ratio. Perioperatively, the adjunct group received intravitreal and subtenons triamcinolone acetonide, oral flurbiprofen and guttae prednisolone acetate 1%. The control group received standard care. Primary outcome was anatomical success at 6 months and showed similar results in anatomical success with 50% (10/20) in the adjunct group, compared to 47% (9/19) in the standard group (Odds Ratio 1.11, 95% Confidence Interval 0.316-3.904). Secondary outcomes included final visual acuity, occurrence of PVR, intraocular pressure (IOP) rise, number of operations and recruitment rate. Final median visual acuity was 31 ETDRS letters in the adjunct group compared to 25 ETDRS letters in the standard group. Other secondary outcomes were similar between the two groups. The hypothesis that an adjunctive slow-release dexamethasone implant (Ozurdex ®) could improve the outcomes of vitreoretinal surgery for established PVR was tested in the Ozurdex® in PVR Study. In this two year, single-centre prospective, participant and surgeon-masked RCT, 140 patients requiring vitrectomy surgery with silicone oil for retinal detachment with established PVR (Grade C) were randomized to either standard (control) or study treatment (adjunct) in a 1:1 allocation ratio. Intraoperatively, the adjunct group received an injection of 0.7mg of slow-release dexamethasone (Ozurdex) at the time of (a) vitrectomy surgery and (b) at silicone oil removal. The control group received standard care. Primary outcome measure was the proportion of patients with a stable retinal reattachment with removal of silicone oil without additional vitreoretinal surgical intervention at 6 months. Secondary outcomes included i) final visual acuity (median and ETDRS of 55 letters or better), ii) cystoid macular edema (CMO), foveal thickness and macular volume iii) development of overt PVR recurrence, iv) complete and posterior retinal reattachment, vi) tractional retinal detachment, vii) hypotony/raised IOP, viii) macula pucker/epiretinal membrane, ix) cataract, x) quality of life All 140 patients were recruited within 25 months of study commencement; 138 patients had primary outcome data. Primary outcome assessment showed similar results in anatomical success between the two groups (49.3% vs 46.3%, adjunct vs control, (Odds Ratio 0.89, 95% Confidence interval 0.46 – 1.74, p= 0.733). Mean visual acuity at 6 months was 38.3 ETDRS letters and 40.2 letters in the adjunct and control group respectively. Secondary anatomical outcomes (complete/posterior reattachment rates and PVR recurrence) were comparable between the two groups. Exploratory analysis suggested that the proportion of patients with cystoid macular oedema (CMO) or a foveal thickness of >300µm was lower in steroid-treated eyes compared to controls (42.7% and 47.6% vs 67.2% and 67.7%, respectively p= 0.004, p= 0.023). Cystoid macular oedema is a secondary cause of visual loss. At 6 months following successful surgery for PVR, eyes with evidence of external limiting membrane (ELM) disruption on Spectral Domain-Optical Coherence Tomography achieve a worse visual outcome than eyes where the ELM appears preserved (p=0.006). Provisional work using retinectomy specimens retrieved at the time of surgery in sixteen patients were studied aiming to isolate a population of Müller glia with stem cell characteristics (hMSC). This suggested that it is feasible to isolate a cell population of appropriate morphology of hMSCs, from eyes with advanced PVR. These cells survived up to ten weeks in culture but eventually terminally differentiate. The work in this thesis has shown that corticosteroids do not modify the vitreoretinal scarring response sufficiently to improve anatomical outcomes at 6 months. Further work is required to improve the outcome in eyes with PVR. Adopting visual acuity as a primary outcome, may be a plausible design in future vitreoretinal trials
Development of a Machine Learning Model for Optimal Applicator Selection in High-Dose-Rate Cervical Brachytherapy
PurposeTo develop and validate a preliminary machine learning (ML) model aiding in the selection of intracavitary (IC) versus hybrid interstitial (IS) applicators for high-dose-rate (HDR) cervical brachytherapy.MethodsFrom a dataset of 233 treatments using IC or IS applicators, a set of geometric features of the structure set were extracted, including the volumes of OARs (bladder, rectum, sigmoid colon) and HR-CTV, proximity of OARs to the HR-CTV, mean and maximum lateral and vertical HR-CTV extent, and offset of the HR-CTV centre-of-mass from the applicator tandem axis. Feature selection using an ANOVA F-test and mutual information removed uninformative features from this set. Twelve classification algorithms were trained and tested over 100 iterations to determine the highest performing individual models through nested 5-fold cross-validation. Three models with the highest accuracy were combined using soft voting to form the final model. This model was trained and tested over 1,000 iterations, during which the relative importance of each feature in the applicator selection process was determined.ResultsFeature selection indicated that the mean and maximum lateral and vertical extent, volume, and axis offset of the HR-CTV were the most informative features and were thus provided to the ML models. Relative feature importances indicated that the HR-CTV volume and mean lateral extent were most important for applicator selection. From the comparison of the individual classification algorithms, it was found that the highest performing algorithms were tree-based ensemble methods – AdaBoost Classifier (ABC), Gradient Boosting Classifier (GBC), and Random Forest Classifier (RFC). The accuracy of the individual models was compared to the voting model for 100 iterations (ABC = 91.6 ± 3.1%, GBC = 90.4 ± 4.1%, RFC = 89.5 ± 4.0%, Voting Model = 92.2 ± 1.8%) and the voting model was found to have superior accuracy. Over the final 1,000 evaluation iterations, the final voting model demonstrated a high predictive accuracy (91.5 ± 0.9%) and F1 Score (90.6 ± 1.1%).ConclusionThe presented model demonstrates high discriminative performance, highlighting the potential for utilization in informing applicator selection prospectively following further clinical validation
Identifying undetected dementia in UK primary care patients: a retrospective case-control study comparing machine-learning and standard epidemiological approaches
Background
Identifying dementia early in time, using real world data, is a public health challenge. As only two-thirds of people with dementia now ultimately receive a formal diagnosis in United Kingdom health systems and many receive it late in the disease process, there is ample room for improvement. The policy of the UK government and National Health Service (NHS) is to increase rates of timely dementia diagnosis. We used data from general practice (GP) patient records to create a machine-learning model to identify patients who have or who are developing dementia, but are currently undetected as having the condition by the GP.
Methods
We used electronic patient records from Clinical Practice Research Datalink (CPRD). Using a case-control design, we selected patients aged >65y with a diagnosis of dementia (cases) and matched them 1:1 by sex and age to patients with no evidence of dementia (controls). We developed a list of 70 clinical entities related to the onset of dementia and recorded in the 5 years before diagnosis. After creating binary features, we trialled machine learning classifiers to discriminate between cases and controls (logistic regression, naïve Bayes, support vector machines, random forest and neural networks). We examined the most important features contributing to discrimination.
Results
The final analysis included data on 93,120 patients, with a median age of 82.6 years; 64.8% were female. The naïve Bayes model performed least well. The logistic regression, support vector machine, neural network and random forest performed very similarly with an AUROC of 0.74. The top features retained in the logistic regression model were disorientation and wandering, behaviour change, schizophrenia, self-neglect, and difficulty managing.
Conclusions
Our model could aid GPs or health service planners with the early detection of dementia. Future work could improve the model by exploring the longitudinal nature of patient data and modelling decline in function over time
Poor prognostic factors in predicting abatacept response in a phase III randomized controlled trial in psoriatic arthritis
In ASTRAEA (NCT01860976), abatacept significantly increased American College of Rheumatology criteria 20% (ACR20) responses at Week 24 versus placebo in patients with psoriatic arthritis (PsA). This post hoc analysis explored relationships between prospectively identified baseline characteristics [poor prognostic factors (PPFs) ] and response to abatacept. Patients were randomized (1:1) to receive subcutaneous abatacept 125 mg weekly or placebo for 24 weeks; those without ≥ 20% improvement in joint counts at Week 16 switched to open-label abatacept. Potential predictors of ACR20 response were identified by treatment arm using multivariate analyses. Likelihood of ACR20 response to abatacept versus placebo was compared in univariate and multivariate analyses in subgroups stratified by the PPF, as defined by EULAR and/or GRAPPA treatment guidelines. Odds ratios (ORs) were generated using logistic regression to identify meaningful differences (OR cut-off: 1.2). 424 patients were randomized and treated (abatacept n = 213; placebo n = 211). In abatacept-treated patients, elevated C-reactive protein (CRP), high Disease Activity Score based on 28 joints (CRP), presence of dactylitis, and ≥ 3 joint erosions were identified as predictors of response (OR > 1.2). In placebo-treated patients, only dactylitis was a potential predictor of response. In the univariate analysis stratified by PPF, ACR20 response was more likely (OR > 1.2) with abatacept versus placebo in patients with baseline PPFs than in those without; multivariate analysis confirmed this finding. Response to abatacept versus placebo is more likely in patients with features indicative of high disease activity and progressive disease; these characteristics are recognized as PPFs in treatment guidelines for PsA
Efficacy and Safety of Abatacept, a T-cell Modulator, in a Randomised, Double-blind, Placebo-controlled, Phase III Study in Psoriatic Arthritis
OBJECTIVES: To assess the efficacy and safety of abatacept, a selective T-cell costimulation modulator, in a phase III study in psoriatic arthritis (PsA). METHODS: This study randomised patients (1:1) with active PsA (~60% with prior exposure to a tumour necrosis factor inhibitor) to blinded weekly subcutaneous abatacept 125 mg (n=213) or placebo (n=211) for 24 weeks, followed by open-label subcutaneous abatacept. Patients without \u3e/=20% improvement in joint counts at week 16 were switched to open-label abatacept. The primary end point was the proportion of patients with \u3e/=20% improvement in the American College of Rheumatology (ACR20) criteria at week 24. RESULTS: Abatacept significantly increased ACR20 response versus placebo at week 24 (39.4% vs 22.3%; p/=0.35) at week 24, this was not statistically significant (31.0% vs 23.7%; p=0.097). The benefits of abatacept were seen in ACR20 responses regardless of tumour necrosis factor inhibitor exposure and in other musculoskeletal manifestations, but significance could not be attributed due to ranking below Health Assessment Questionnaire-Disability Index response in hierarchical testing. However, the benefit on psoriasis lesions was modest. Efficacy was maintained or improved up to week 52. Abatacept was well tolerated with no new safety signals. CONCLUSIONS: Abatacept treatment of PsA in this phase III study achieved its primary end point, ACR20 response, showed beneficial trends overall in musculoskeletal manifestations and was well tolerated. There was only a modest impact on psoriasis lesions. TRIAL REGISTRATION NUMBER: ClinicalTrials.gov number, NCT01860976 (funded by Bristol-Myers Squibb)
Safer in the Clouds (Extended Abstract)
We outline the design of a framework for modelling cloud computing
systems.The approach is based on a declarative programming model which takes
the form of a lambda-calculus enriched with suitable mechanisms to express and
enforce application-level security policies governing usages of resources
available in the clouds. We will focus on the server side of cloud systems, by
adopting a pro-active approach, where explicit security policies regulate
server's behaviour.Comment: In Proceedings ICE 2010, arXiv:1010.530
Outpatient parenteral antimicrobial therapy practices among adult infectious disease physicians
Objective. To identify current outpatient parenteral antibiotic therapy practice patterns and complications. Methods. We administered an 11-question survey to adult infectious disease physicians participating in the Emerging Infections Network (EIN), a Centers for Disease Control and Prevention-sponsored sentinel event surveillance network in North America. The survey was distributed electronically or via facsimile in November and December 2012. Respondent demographic characteristics were obtained from EIN enrollment data. Results. Overall, 555 (44.6%) of EIN members responded to the survey, with 450 (81%) indicating that they treated 1 or more patients with outpatient parenteral antimicrobial therapy (OPAT) during an average month. Infectious diseases consultation was reported to be required for a patient to be discharged with OPAT by 99 respondents (22%). Inpatient (282 [63%] of 449) and outpatient (232 [52%] of 449) infectious diseases physicians were frequently identified as being responsible for monitoring laboratory results. Only 26% (118 of 448) had dedicated OPAT teams at their clinical site. Few infectious diseases physicians have systems to track errors, adverse events, or "near misses" associated with OPAT (97 [22%] of 449). OPAT-associated complications were perceived to be rare. Among respondents, 80% reported line occlusion or clotting as the most common complication (occurring in 6% of patients or more), followed by nephrotoxicity and rash (each reported by 61%). Weekly laboratory monitoring of patients who received vancomycin was reported by 77% of respondents (343 of 445), whereas 19% of respondents (84 of 445) reported twice weekly laboratory monitoring for these patients. Conclusions. Although use of OPAT is common, there is significant variation in practice patterns. More uniform OPAT practices may enhance patient safety
Relocating Bike-Kiosks to Maximize Ridership – A Weighted Matching Optimization Problem
poster abstractBike share infrastructure can benefit from optimized allocation of resources, such as bike share stations or kiosks that have relatively high capital costs. Suboptimal placement of stations increases the cost of service and may impede membership. If impedances like distance to kiosk is high then ridership may decrease thereby not allowing the system to reach its full potential. Currently, the 25 bike-share stations managed by the non-profit Indiana Pacers Bikeshare program are located around the Indianapolis downtown area and the Indianapolis Cultural Trail. We developed a weighted matching solution to minimize the distance potential users must travel to reach a kiosk while taking into account the pairing of existing kiosks with new locations. We also provide a model to introduce several new locations that restricts maximum distance traveled by customers to the nearest kiosk. For both, we apply integer programming heuristics to solve the optimization problem – an NP hard problem. NP hard problems are computationally prohibitive and require specialized mathematical programming for robust solutions. Analyses show that 20 optimally located kiosks will serve the 25 existing kiosks clientele without any increase in impedance to kiosk access – a 20 percent increase in efficiency
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