Background: Systemic sclerosis (scleroderma, SSc) is a chronic multisystem autoimmune disease characterised by fibrosis of the skin and internal organs and vasculopathy. One of the major contributors to mortality in p...
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Background: Systemic sclerosis (scleroderma, SSc) is a chronic multisystem autoimmune disease characterised by fibrosis of the skin and internal organs and vasculopathy. One of the major contributors to mortality in patients with SSc is pulmonary arterial hypertension (PAH). International recommendations advise annual screening for the early detection of PAH in asymptomatic patients with SSc. Objectives: To evaluate by systematic review current measures employed for screening for PAH. To summarise by meta-analysis the current evidence for long-term outcomes of screening for PAH in SSc. Methods: Manuscripts published until 12th March 2019 were identified through searching Medline, Embase and Cochrane Central Register of Controlled Trials and Database of Systematic Reviews. Eligible studies included abstracts or full reports investigating patients with SSc undergoing screening by any protocol to detect PAH. Risk of bias was assessed with reference to the QUADAS-2 tool. Results: The review resulted in 580 unique citations with 15 manuscripts included for final systematic review of screening methods, and six for meta-analysis. The systematic review demonstrated that there are varying protocols for screening for PAH. Screened populations were reported to have better risk stratification parameters at PAH diagnosis. Meta-analysis showed improved survival in patients with SSc-PAH diagnosed as a result of screening. There were trends towards having better risk stratification parameters at PAH diagnosis in those screened, although not all of these were statistically significant. Limitations: There are no randomised controlled trials of screening for PAH in patients with SSc and the evidence presented in this review is derived from publications of registry data, cross-sectional and cohort studies. Conclusions: This review demonstrates long-term benefit through the systematic screening of patients with SSc of varying disease duration for the early detection of PAH. Screened coh
Background: Labeling color fundus photos (CFP) is an important step in the development of artificial intelligence screening algorithms for the detection of diabetic retinopathy (DR). Most studies use the International...
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Background: Labeling color fundus photos (CFP) is an important step in the development of artificial intelligence screening algorithms for the detection of diabetic retinopathy (DR). Most studies use the International Classification of Diabetic Retinopathy (ICDR) to assign labels to CFP, plus the presence or absence of macular edema (ME). Images can be grouped as referrable or nonreferrable according to these classifications. There is little guidance in the literature about how to collect and use metadata as a part of the CFP labeling process. Objective: This study aimed to improve the quality of the Multimodal Database of Retinal Images in Africa (MoDRIA) by determining whether the availability of metadata during the image labeling process influences the accuracy, sensitivity, and specificity of image labels. MoDRIA was developed as one of the inaugural research projects of the Mbarara University Data Science Research Hub, part of the Data Science for Health Discovery and Innovation in Africa (DS-I Africa) initiative. Methods: This is a crossover assessment with 2 groups and 2 phases. Each group had 10 randomly assigned labelers who provided an ICDR score and the presence or absence of ME for each of the 50 CFP in a test image with and without metadata including blood pressure, visual acuity, glucose, and medical history. Specificity and sensitivity of referable retinopathy were based on ICDR scores, and ME was calculated using a 2-sided t test. Comparison of sensitivity and specificity for ICDR scores and ME with and without metadata for each participant was calculated using the Wilcoxon signed rank test. Statistical significance was set at P<.05. Results: The sensitivity for identifying referrable DR with metadata was 92.8% (95% CI 87.6-98.0) compared with 93.3% (95% CI 87.6-98.9) without metadata, and the specificity was 84.9% (95% CI 75.1-94.6) with metadata compared with 88.2% (95% CI 79.5-96.8) without metadata. The sensitivity for identifying the presence of
Background: Enterobacteriaceae are a common cause of hospital infections. Carbapenems are a clinically effective treatment of such infections. However, resistance is on the rise. In particular, carbapenemase-producing...
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Background: Enterobacteriaceae are a common cause of hospital infections. Carbapenems are a clinically effective treatment of such infections. However, resistance is on the rise. In particular, carbapenemase-producing carbapenem-resistant Enterobacteriaceae (CP-CRE) are increasingly common. In order to limit spread in clinical settings, screening and isolation is being recommended, but many different screening methods are available. We aimed to compare the impact and costs of three algorithms for detecting CP-CRE carriage. Methods: We developed an individual-based simulation model to compare three screening algorithms using data from a UK National Health Service (NHS) trust. The first algorithm, "Direct PCR", was highly sensitive/specific and quick (half a day), but expensive. The second, "Culture + PCR", was relatively sensitive/specific but slower, requiring 2.5 days. A third algorithm, "PHE", repeated the "Culture + PCR" three times with an additional PCR. Scenario analysis was used to compare several levels of CP-CRE prevalence and coverage of screening, different specialities as well as isolation strategies. Our outcomes were (1) days that a patient with CP-CRE was not detected and hence not isolated ("days at risk"), (2) isolation bed days, (3) total costs and (4) mean cost per CP-CRE risk day averted per year. We also explored limited isolation bed day capacity. Results: We found that although a Direct PCR algorithm would reduce the number of CP-CRE days at risk, the mean cost per CP-CRE risk day averted per year was substantially higher than for a Culture + PCR algorithm. For example, in our model of an intensive care unit, during a year with a 1.6% CP-CRE prevalence and 63% screening coverage, there were 508 (standard deviation 15), 642 (14) and 655 (14) days at risk under screening algorithms Direct PCR, Culture + PCR and PHE respectively, with mean costs per risk day averted of 192 pound, 61 pound and 79 pound. These results were robust to sensitivity ana
Sleep Disordered Breathing (SDB) is a group of diseases that affect the normal respiratory function during sleep, from primary snoring to obstructive sleep apnea (OSA) being the most severe. SDB can be detected using ...
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Sleep Disordered Breathing (SDB) is a group of diseases that affect the normal respiratory function during sleep, from primary snoring to obstructive sleep apnea (OSA) being the most severe. SDB can be detected using a complex and expensive exam called polysomnography. This exam monitors the sleep of a person during the night by measuring 21 different signals from an Electrocardiogram to Nasal Air Flow. Several automatic methods have been developed to detect this disorder in adults, with a very high performance and using only one signal. However, we have not found similar algorithms especially developed for Children. We benchmarked 6 different methods developed for adults. We showed empirically that those models' performance is drastically reduced when used on children (under 15 years old). Afterwards, we present a new approach for screening children with risk of having SDB. Moreover, our algorithm uses less information than a polysomnography and out performs state-of-the-art techniques when used on children. We also showed empirically that no signal alone is a good SDB screening in children. Moreover, we discover that combinations of three signals which are not used in any other previous work are the best for this task in children. (C) 2015 Elsevier Ltd. All rights reserved.
Background The diagnosis of syphilis is most frequently dependent on antibody detection with serological assays. Assays for both treponemal and non-treponemal antibodies are needed to provide a sensitive and specific ...
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Background The diagnosis of syphilis is most frequently dependent on antibody detection with serological assays. Assays for both treponemal and non-treponemal antibodies are needed to provide a sensitive and specific diagnosis. For decades, a first screening has been done with non-treponemal assays, followed by treponemal. However, in recent years, following laboratory automation, the reverse sequence screening algorithms have been developed, using a treponemal assay as the initial screening test. Objective To evaluate serological assays for treponemal and non-treponemal antibodies, to use in reverse algorithm screening of syphilis. Material and methods Six treponemal assays (one IgM-specific assay), two non-treponemal assays and one novel dual point-of-care (POC) assay for serological diagnosis of syphilis were evaluated. Serum samples from Guinea-Bissau and Sweden were examined, as well as two performance panels and samples from blood donors. Sensitivity and specificity were calculated for each assay, using different assays as gold standard test. Results The Macro-Vue RPR Card test was the most sensitive non-treponemal test and the TrepSure Anti-Treponema EIA Screen and the SeroDia TP-PA were the most sensitive and specific treponemal assays. Among the automated assays, both the Liaison Treponema Screen and Architect Syphilis TP showed high sensitivity, however, the former had clearly higher specificity. Conclusions In resourced settings, where the reverse sequence algorithm is preferred for screening, an automated treponemal immunoassay for initial screening subsequently followed by the TrepSure test or TP-PA assay as a second treponemal assay appear highly effective. Finally, a quantitative highly sensitive non-treponemal assay, e.g. the Macro-Vue RPR Card test, could then be used as a supplementary test to evaluate activity of the syphilis infection.
screening for hereditary hemochromatosis, although largely discussed, is not yet implemented in clinical practice. We evaluated the cost-effectiveness of 165 hemochromatosis population-screening algorithms involving t...
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screening for hereditary hemochromatosis, although largely discussed, is not yet implemented in clinical practice. We evaluated the cost-effectiveness of 165 hemochromatosis population-screening algorithms involving two or three of several screening tests by developing a computer program that simulates all possible screening scenarios. Input data comprised government estimates of health services data and costs and a virtual population with user-defined demographic characteristics (including variable HFE mutation frequencies and penetrance values). We show that when C282Y homozygote prevalence is set at 3:1000, population screening appears cost-effective when penetrance of the biochemical phenotype is > 0.70. When only hepatocellular carcinoma and cirrhosis are considered as the cost-driving complications, population-based screening is not significantly more cost-efficient than no screening, but life expectancy of individuals identified with hereditary hemochromatosis and treated is still improved by 7 years. Among the 165 screening algorithms tested in 91 different virtual populations of one million individuals, biochemical tests usually perform better as the initial test than genetic testing. Indeed, the genetic testing is most cost-effective as the final confirmatory test. Finally, for most combinations of prevalence and penetrance of HFE, one screening algorithm - unbound iron-binding capacity + transferrin saturation - appeared robust enough to be always within the top 5 most cost-effective strategies.
On any given day, organizations use software simulations to make better decisions. Software simulations of real world systems are often large and rich with many parameters potentially affecting outcomes. Faced with a ...
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On any given day, organizations use software simulations to make better decisions. Software simulations of real world systems are often large and rich with many parameters potentially affecting outcomes. Faced with a multitude of parameters, decision makers may not know or may lose sight of the few truly critical factors. Thus, screening algorithms are essential in order to identify the factors that most impact outcome measures. This enables experimenters to better utilize their resources by focusing on truly important factors. Fractional Factorial Controlled Sequential Bifurcation (FFCSB) is a newly proposed two-phase screening procedure for large-scale simulation experiments. This thesis evaluates the performance of FFCSB from accuracy and efficiency perspectives. FFCSB is also compared to existing algorithms, Controlled Sequential Bifurcation (CSB) and Fractional Factorial (FF), in order to understand the relative merits and weaknesses of each algorithm. FFCSB delivers consistent accuracy guarantees across more factor patterns and offers efficiency savings over CSB. FFCSB and FF are equally matched in accuracy; however, FFCSB is more robust to non-ideal settings of control parameters and scales better with increasing response model size; conversely FFCSB can be less efficient than FF. A first-case application of FFCSB on the Hierarchy organizational model yields results in agreement with prior research, as well as providing interesting hypotheses for further exploration. The Hierarchy model serves as a benchmark to compare innovative Command and Control structures for enabling more effective warfare.
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