2,097 research outputs found

    Bootstrapping multiple systems estimates to account for model selection

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    Multiple systems estimation is a standard approach to quantifying hidden populations where data sources are based on lists of known cases. A typical modelling approach is to fit a Poisson loglinear model to the numbers of cases observed in each possible combination of the lists. It is necessary to decide which interaction parameters to include in the model, and information criterion approaches are often used for model selection. Difficulties in the context of multiple systems estimation may arise due to sparse or nil counts based on the intersection of lists, and care must be taken when information criterion approaches are used for model selection due to issues relating to the existence of estimates and identifiability of the model. Confidence intervals are often reported conditional on the model selected, providing an over-optimistic impression of the accuracy of the estimation. A bootstrap approach is a natural way to account for the model selection procedure. However, because the model selection step has to be carried out for every bootstrap replication, there may be a high or even prohibitive computational burden. We explore the merit of modifying the model selection procedure in the bootstrap to look only among a subset of models, chosen on the basis of their information criterion score on the original data. This provides large computational gains with little apparent effect on inference. Another model selection approach considered and investigated is a downhill search approach among models, possibly with multiple starting points.Comment: 21 pages, 5 figures, 6 table

    The changing world of communications

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    A targeted gene panel that covers coding, non-coding and short tandem repeat regions improves the diagnosis of patients with neurodegenerative diseases

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    Genetic testing for neurodegenerative diseases (NDs) is highly challenging because of genetic heterogeneity and overlapping manifestations. Targeted-gene panels (TGPs), coupled with next-generation sequencing (NGS), can facilitate the profiling of a large repertoire of ND-related genes. Due to the technical limitations inherent in NGS and TGPs, short tandem repeat (STR) variations are often ignored. However, STR expansions are known to cause such NDs as Huntington\u27s disease and spinocerebellar ataxias type 3 (SCA3). Here, we studied the clinical utility of a custom-made TGP that targets 199 NDs and 311 ND-associated genes on 118 undiagnosed patients. At least one known or likely pathogenic variation was found in 54 patients; 27 patients demonstrated clinical profiles that matched the variants; and 16 patients whose original diagnosis were refined. A high concordance of variant calling were observed when comparing the results from TGP and whole-exome sequencing of four patients. Our in-house STR detection algorithm has reached a specificity of 0.88 and a sensitivity of 0.82 in our SCA3 cohort. This study also uncovered a trove of novel and recurrent variants that may enrich the repertoire of ND-related genetic markers. We propose that a combined comprehensive TGPs-bioinformatics pipeline can improve the clinical diagnosis of NDs

    Cost-efficient optical network architectures

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    Abstract We conduct a throughput-cost study of several (hybrid) multi-tiered optical network architectures comprising two large groups of users, each in a distinct MAN, which wish to communicate over a WAN. Introduction We address the question of how to best use traditional electronic and emergent optical technology to create a terrestrial network with desirable scalability properties: a decreasing cost per user, per unit of traffic, as the number of users and individual user bandwidth demand increase. We conduct a throughput-cost comparison of several prominent network architectures, and hybrids of these architectures: optical flow switching (OFS), Tell-andGo (TaG), Electronic Packet Switching (EPS), and Generalized MultiProtocol Label/Lambda Switching (EPS/GMPLS). The context for comparison is two large groups of users, located in different MANs, which communicate over a WAN. Our network model, though simple in that it only considers the communication of two sets of users across a WAN, is a building block for more complex network topologies, and more importantly, captures the essence of the throughput-cost tradeoffs of more complex networks

    Multiple Systems Estimation for Sparse Capture Data: Inferential Challenges When There Are Nonoverlapping Lists

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    © 2020 American Statistical Association. Multiple systems estimation strategies have recently been applied to quantify hard-to-reach populations, particularly when estimating the number of victims of human trafficking and modern slavery. In such contexts, it is not uncommon to see sparse or even no overlap between some of the lists on which the estimates are based. These create difficulties in model fitting and selection, and we develop inference procedures to address these challenges. The approach is based on Poisson log-linear regression modeling. Issues investigated in detail include taking proper account of data sparsity in the estimation procedure, as well as the existence and identifiability of maximum likelihood estimates. A stepwise method for choosing the most suitable parameters is developed, together with a bootstrap approach to finding confidence intervals for the total population size. We apply the strategy to two empirical datasets of trafficking in US regions, and find that the approach results in stable, reasonable estimates. An accompanying R software implementation has been made publicly available. Supplementary materials for this article are available online

    CORRECTION Open Access

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    tumor progression enhances the oncogenic capacity of advanced ovarian cance

    The impact of positron emission tomography on primary tumour delineation and dosimetric outcome in intensity modulated radiotherapy of early T-stage nasopharyngeal carcinoma

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    Background: In intensity modulated radiotherapy (IMRT) of nasopharyngeal carcinoma (NPC), accurate delineation of the gross tumour volume (GTV) is important. Image registration of CT and MRI has been routinely used in treatment planning. With recent development of positron emission tomography (PET), the aims of this study were to evaluate the impact of PET on GTV delineation and dosimetric outcome in IMRT of early stage NPC patients.Methods: Twenty NPC patients with T1 or T2 disease treated by IMRT were recruited. For each patient, 2 sets of NP GTVs were delineated separately, in which one set was performed using CT and MRI registration only (GTVCM), while the other set was carried out using PET, CT and MRI information (GTVCMP). A 9-field IMRT plan was computed based on the target volumes generated from CT and MRI (PTVCM). To assess the geometric difference between the GTVCM and GTVCMP, GTV volumes and DICE similarity coefficient (DSC), which measured the geometrical similarity between the two GTVs, were recorded. To evaluate the dosimetric impact, the Dmax, Dmin, Dmean and D95 of PTVs were obtained from their dose volume histograms generated by the treatment planning system.Results: The overall mean volume of GTVCMP was greater than GTVCM by 4.4 %, in which GTVCMP was slightly greater in the T1 group but lower in the T2 group. The mean DSC of the whole group was 0.79 ± 0.05. Similar mean DSC values were also obtained from the T1 and T2 groups separately. The dosimetric parameters of PTVCM fulfilled the planning requirements. When applying this plan to the PTVCMP, the average Dmin (56.9 Gy) and D95 (68.6 Gy) of PTVCMP failed to meet the dose requirements and demonstrated significant differences from the PTVCM (p = 0.001 and 0.016 respectively), whereas the doses to GTVCMP did not show significant difference with the GTVCM.Conclusion: In IMRT of early stage NPC, PET was an important imaging modality in radiotherapy planning so as to avoid underdosing the PTV, although its effect on GTV delineation was not significant. It was recommended that PET images should be included in the treatment planning of NPC patients.Department of Health Technology and Informatic

    Effect of real-time computer-aided polyp detection system (ENDO-AID) on adenoma detection in endoscopists-in-training: a randomized trial

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    Background The effect of computer-aided polyp detection (CADe) on adenoma detection rate (ADR) among endoscopists-in-training remains unknown. Methods We performed a single-blind, parallel-group, randomized controlled trial in Hong Kong between April 2021 and July 2022 (NCT04838951). Eligible subjects undergoing screening/surveillance/diagnostic colonoscopies were randomized 1:1 to receive colonoscopies with CADe (ENDO-AID(OIP-1), Olympus Co., Japan) or not (control) during withdrawal. Procedures were performed by endoscopists-in-training with <500 procedures and <3 years’ experience. Randomization was stratified by patient age, sex, and endoscopist experience (beginner vs intermediate-level, <200 vs 200-500 procedures). Image enhancement and distal attachment devices were disallowed. Subjects with incomplete colonoscopies or inadequate bowel preparation were excluded. Treatment allocation was blinded to outcome assessors. The primary outcome was ADR. Secondary outcomes were ADR for different adenoma sizes and locations, mean number of adenomas, and non-neoplastic resection rate. Results 386 and 380 subjects were randomized to CADe and control groups, respectively. The overall ADR was significantly higher in CADe than control group (57.5% vs 44.5%, adjusted relative risk 1.41, 95%CI 1.17-1.72, p<0.001). The ADRs for <5mm (40.4% vs 25.0%) and 5-10mm adenomas (36.8% vs 29.2%) were higher in CADe group. The ADRs were higher in CADe group in both right (42.0% vs 30.8%) and left colon (34.5% vs 27.6%), but there was no significant difference in advanced ADR. The ADRs were higher in CADe group among beginners (60.0% vs 41.9%) and intermediate-level endoscopists (56.5% vs 45.5%). Mean number of adenomas (1.48 vs 0.86) and non-neoplastic resection rate were higher in CADe group (52.1% vs 35.0%). Conclusions Among endoscopists-in-training, the use of CADe during colonoscopies was associated with increased overall ADR. (ClinicalTrials.gov: NCT04838951

    Association between statins and the risk of suicide attempt, depression, anxiety, and seizure: A population-based, self-controlled case series study

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    Background: Risk of suicide attempt, depression, anxiety and seizure and the association with statins is an ongoing debate. We aim to investigate the association between statins and the above neuropsychological outcomes, in specific pre- and post-exposure time windows./ Methods: We identified patients aged 40–75 years old who were dispensed a statin between January 1, 2003 and December 31, 2012 from the Hong Kong Clinical Data Analysis & Reporting System (CDARS), an electronic medical records database. Patients with new onset of suicide attempt, depression, anxiety and seizure were derived from the original dataset separately, in a self-controlled case series study design. A non-parametric spline-based self-controlled case series model was built to measure continuous changes of risk./ Results: We identified 396,614 statin users. The risk of each outcome was elevated prior to statin initiation with incidence rate ratios of 1.38 (95 % CI, 1.09–1.74) for suicide attempt, 1.29 (95 % CI, 1.15–1.45) for depression, 1.35 (95 % CI, 1.19–1.53) for anxiety, and 1.45 (95 % CI, 1.21–1.73) for seizure. The incidence rate ratios remained elevated after the initiation of statins during the first 90 and 91–365 days after statin prescription and decreased to the baseline level after 1 year of continuous prescription./ Limitations: CDARS includes prescription data but not adherence data, which could lead to misclassification of exposure periods./ Conclusions: Our study does not support a direct association between statin use and suicide attempt, depression, anxiety and seizure, whose risks could be explained by cardiovascular events, for which statins were prescribed
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