499 research outputs found
Meta-analysis and meta-modelling for diagnostic problems
No full textBackgroundA proportional hazards measure is suggested in the context of analyzing SROC curves that arise in the meta–analysis of diagnostic studies. The measure can be motivated as a special model: the Lehmann model for ROC curves. The Lehmann model involves study–specific sensitivities and specificities and a diagnostic accuracy parameter which connects the two.MethodsA study–specific model is estimated for each study, and the resulting study-specific estimate of diagnostic accuracy is taken as an outcome measure for a mixed model with a random study effect and other study-level covariates as fixed effects. The variance component model becomes estimable by deriving within-study variances, depending on the outcome measure of choice. In contrast to existing approaches – usually of bivariate nature for the outcome measures – the suggested approach is univariate and, hence, allows easily the application of conventional mixed modelling.ResultsSome simple modifications in the SAS procedure proc mixed allow the fitting of mixed models for meta-analytic data from diagnostic studies. The methodology is illustrated with several meta–analytic diagnostic data sets, including a meta–analysis of the Mini–Mental State Examination as a diagnostic device for dementia and mild cognitive impairment.ConclusionsThe proposed methodology allows us to embed the meta-analysis of diagnostic studies into the well–developed area of mixed modelling. Different outcome measures, specifically from the perspective of whether a local or a global measure of diagnostic accuracy should be applied, are discussed as well. In particular, variation in cut-off value is discussed together with recommendations on choosing the best cut-off value. We also show how this problem can be addressed with the proposed methodology
Leveraging waveform complexity for confident detection of gravitational waves
No full textThe recent completion of Advanced LIGO suggests that gravitational waves (GWs) may soon be directly observed. Past searches for gravitational-wave transients have been impacted by transient noise artifacts, known as glitches, introduced into LIGO data due to instrumental and environmental effects. In this work, we explore how waveform complexity, instead of signal-to-noise ratio, can be used to rank event candidates and distinguish short duration astrophysical signals from glitches. We test this framework using a new hierarchical pipeline that directly compares the Bayesian evidence of explicit signal and glitch models. The hierarchical pipeline is shown to have strong performance, and in particular, allows high-confidence detections of a range of waveforms at realistic signal-to-noise ratio with a two detector network
Cataclysmic variables are a key population of gravitational wave sources for LISA
No full textThe gravitational wave (GW) signals from the Galactic population of
cataclysmic variables (CVs) have yet to be carefully assessed. Here we estimate
these signals and evaluate their significance for LISA. First, we find that at
least three known systems are expected to produce strong enough signals to be
individually resolved within the first four years of LISA's operation. Second,
CVs will contribute significantly to the LISA Galactic binary background,
limiting the mission's sensitivity in the relevant frequency band. Third, we
predict a spike in the unresolved GW background at a frequency corresponding to
the CV minimum orbital period. This excess noise may impact the detection of
other systems near this characteristic frequency. Fourth, we note that the
excess noise spike amplitude and location associated with
can be used to measure the CV space density
and period bounce location with complementary and simple GW biases compared to
the biases and selection effects plaguing samples selected from electromagnetic
signals. Our results highlight the need to explicitly include the Galactic CV
population in the LISA mission planning, both as individual GW sources and
generators of background noise, as well as the exciting prospect of
characterising the CV population through their GW emission.Comment: 5 pages, 3 figures. Accepted for publication in MNRAS Letter
Multi-messenger parameter inference of gravitational-wave and electromagnetic observations of white dwarf binaries
No full textThe upcoming Laser Interferometer Space Antenna (LISA) will detect a large
gravitational-wave foreground of Galactic white dwarf binaries. These sources
are exceptional for their probable detection at electromagnetic wavelengths,
some long before LISA flies. Studies in both gravitational and electromagnetic
waves will yield strong constraints on system parameters not achievable through
measurements of one messenger alone. In this work, we present a Bayesian
inference pipeline and simulation suite in which we study potential constraints
on binaries in a variety of configurations. We show how using LISA detections
and parameter estimation can significantly improve constraints on system
parameters when used as a prior for the electromagnetic analyses. We also
provide rules of thumb for how current measurements will benefit from LISA
measurements in the future.Comment: 8 pages, 5 figures, accepted to MNRA
Recommended from our members
Rare kaon, muon, and pion decay
No full textThe author discusses the status of and prospects for the study of rare decays of kaons, muons, and pions. Studies of rare kaon decays are entering an interesting new phase wherein they can deliver important short-distance information. It should be possible to construct an alternative unitarity triangle to that determined in the B sector, and thus perform a critical check of the Standard Model by comparing the two. Rare muon decays are beginning to constrain supersymmetric models in a significant way, and future experiments should reach sensitivities which this kind of model must show effects, or become far less appealing
Construction of rugged, ultrastable optical assemblies with optical component alignment at the few microradian level
No full textA method for constructing quasimonolithic, precision-aligned optical assemblies is presented. Hydroxide-catalysis bonding is used, adapted to allow optimization of component fine alignment prior to the bond setting. We demonstrate the technique by bonding a fused silica mirror substrate to a fused silica baseplate. In-plane component placement at the submicrometer level is achieved, resulting in angular control of a reflected laser beam at the sub-10-μrad level. Within the context of the LISA Pathfinder mission, the technique has been demonstrated as suitable for use in space-flight applications. It is expected that there will also be applications in a wide range of areas where accuracy, stability, and strength of optical assemblies are important
Can Anti-Müllerian hormone predict the diagnosis of polycystic ovary syndrome? : A systematic review and meta-analysis of extracted data
No full textContext: Existing biochemical tests for polycystic ovary syndrome (PCOS) have poor sensitivity and specificity. Many women with PCOS have high anti-Müllerian hormone (AMH) concentrations; thus, this may be a useful addition to the diagnostic criteria. Objective: A systematic literature review was performed to assess the true accuracy of AMH in the prediction of PCOS and to determine the optimal diagnostic threshold. Data Sources: Published and gray literature were searched for all years until January 2013. Study Selection: Observational studies defining PCOS according to the Rotterdam criteria and assessing the value of AMH in diagnosing PCOS were selected. Ten studies of the initial 314 hits reporting AMH values in the diagnosis of PCOS were included in the meta-analysis and the construction of the summary receiver-operating characteristic curve. Four studies that plotted individual AMH serum levels of women with PCOS and controls on graphs were selected for individual data extraction. Data Extraction: Two researchers independently assessed the abstracts resulted from the initial search against the inclusion criteria, graded the papers for selection and verification biases, and selected the papers that assessed the value of AMH in diagnosing PCOS. Data were extracted from 4 studies with the plotted individual data on graphs with the help of computer software. Data Synthesis: The meta-analysis of the extracted data demonstrated the specificity and sensitivity in diagnosing PCOS in the symptomatic women of 79.4% and 82.8%, respectively, for a cutoff value of AMH of 4.7 ng/mL. The area under the curve was 0.87 (95% confidence interval 0.83–0.92), identical with the area under the curve of 0.87 for the summary receiver-operating characteristic curve involving 10 separate studies. Conclusions: AMH may be a useful initial diagnostic test for PCOS subject to validation in prospective population cohorts.Peer reviewe
Electromagnetic Characterization of the LISA Verification Binary ZTF J0526+5934
No full text© 2023. The Author(s). Published by the American Astronomical Society. cc-byWe present an analysis of new and archival data to the 20.506 minute LISA verification binary J052610.42+593445.32 (J0526+5934). Our joint spectroscopic and photometric analysis finds that the binary contains an unseen M 1 = 0.89 ± 0.11 M ⊙ CO-core white dwarf primary with an M 2 = 0.38 ± 0.07 M ⊙ post-core-burning subdwarf, or low-mass white dwarf, companion. Given the short orbital period and relatively large total binary mass, we find that LISA will detect this binary with signal-to-noise ratio 44 after 4 yr of observations. J0526+5934 is expected to merge within 1.8 ± 0.3 Myr and likely result in a D6 scenario Type Ia supernova or form a He-rich star that will evolve into a massive single white dwarf
A systematic review of evidence on malignant spinal metastases : natural history and technologies for identifying patients at high risk of vertebral fracture and spinal cord compression
No full textBackground: Spinal metastases can lead to significant morbidity and reduction in quality of life due to spinal cord compression (SCC). Between 5% and 20% of patients with spinal metastases develop metastatic spinal cord compression during the course of their disease. An early study estimated average survival for patients with SCC to be between 3 and 7 months, with a 36% probability of survival to 12 months. An understanding of the natural history and early diagnosis of spinal metastases and prediction of collapse of the metastatic vertebrae are important.
Objective: To undertake a systematic review to examine the natural history of metastatic spinal lesions and to identify patients at high risk of vertebral fracture and SCC.
Data sources: The search strategy covered the concepts of metastasis, the spine and adults. Searches were undertaken from inception to June 2011 in 13 electronic databases [MEDLINE; MEDLINE In-Process & Other Non-Indexed Citations; EMBASE; Cochrane Database of Systematic Reviews; Cochrane Central Register of Controlled Trials (CENTRAL); Database of Abstracts of Reviews of Effects (DARE), NHS Economic Evaluation Database (NHS EED), HTA databases (NHS Centre for Reviews and Dissemination); Science Citation Index and Conference Proceedings (Web of Science); UK Clinical Research Network (UKCRN) Portfolio Database; Current Controlled Trials; ClinicalTrials.gov].
Review methods: Titles and abstracts of retrieved studies were assessed by two reviewers independently. Disagreement was resolved by consensus agreement. Full data were extracted independently by one reviewer. All included studies were reviewed by a second researcher with disagreements resolved by discussion. A quality assessment instrument was used to assess bias in six domains: study population, attrition, prognostic factor measurement, outcome measurement, confounding measurement and account, and analysis. Data were tabulated and discussed in a narrative review. Each tumour type was looked at separately.
Results: In all, 2425 potentially relevant articles were identified, of which 31 met the inclusion criteria. No study examined natural history alone. Seventeen studies reported retrospective data, 10 were prospective studies, and three were other study designs. There was one systematic review. There were no randomised controlled trials (RCTs). Approximately 5782 participants were included. Sample sizes ranged from 41 to 859. The age of participants ranged between 7 and 92 years. Types of cancers reported on were lung alone (n= 3), prostate alone (n= 6), breast alone (n= 7), mixed cancers (n= 13) and unclear (n= 1). A total of 93 prognostic factors were identified as potentially significant in predicting risk of SCC or collapse. Overall findings indicated that the more spinal metastases present and the longer a patient was at risk, the greater the reported likelihood of development of SCC and collapse. There was an increased risk of developing SCC if a cancer had already spread to the bones. In the prostate cancer studies, tumour grade, metastatic load and time on hormone therapy were associated with increased risk of SCC. In one study, risk of SCC before death was 24%, and 2.37 times greater with a Gleason score 7 than with a score of < 7 (p= 0.003). Other research found that patients with six or more bone lesions were at greater risk of SCC than those with fewer than six lesions [odds ratio (OR) 2.9, 95% confidence interval (CI) 1.012 to 8.35, p= 0.047]. For breast cancer patients who received a computerised tomography (CT) scan for suspected SCC, multiple logistic regression in one study identified four independent variables predictive of a positive test: bone metastases 2 years (OR 3.0 95% CI 1.2 to 7.6; p= 0.02); metastatic disease at initial diagnosis (OR 3.4, 95% CI 1.0 to 11.4; p= 0.05); objective weakness (OR 3.8, 95% CI 1.5 to 9.5; p= 0.005); and vertebral compression fracture on spine radiograph (OR 2.6, 95% CI 1.0 to 6.5; p= 0.05). A further study on mixed cancers, among patients who received surgery for SCC, reported that vertebral body compression fractures were associated with presurgery chemotherapy (OR 2.283, 95% CI 1.064 to 4.898; p= 0.03), cancer type [primary breast cancer (OR 4.179, 95% CI 1.457 to 11.983; p= 0.008)], thoracic involvement (OR 3.505, 95% CI 1.343 to 9.143; p= 0.01) and anterior cord compression (OR 3.213, 95% CI 1.416 to 7.293; p= 0.005).
Limitations: Many of the included studies provided limited information about patient populations and selection criteria and they varied in methodological quality, rigour and transparency. Several studies identified type of cancer (e.g. breast, lung or prostate cancer) as a significant factor in predicting SCC, but it remains difficult to determine the risk differential partly because of residual bias. Consideration of quantitative results from the studies does not easily allow generation of a coherent numerical summary, studies were heterogeneous especially with regard to population, results were not consistent between studies, and study results almost universally lacked corroboration from other independent studies.
Conclusion: No studies were found which examined natural history. Overall burden of metastatic disease, confirmed metastatic bone involvement and immediate symptomatology suggestive of spinal column involvement are already well known as factors for metastatic SCC, vertebral collapse or progression of vertebral collapse. Although we identified a large number of additional possible prognostic factors, those which currently offer the most potential are unclear. Current clinical consensus favours magnetic resonance imaging and CT imaging modalities for the investigation of SCC and vertebral fracture. Future research should concentrate on: (1) prospective randomised designs to establish clinical and quality-of-life outcomes and cost-effectiveness of identification and treatment of patients at high risk of vertebral collapse and SCC; (2) Service Delivery and Organisation research on magnetic resonance imaging (MRI) scans and scanning (in tandem with research studies on use of MRI to monitor progression) in order to understand best methods for maximising use of MRI scanners; and (3) investigation of prognostic algorithms to calculate probability of a specified event using high-quality prospective studies, involving defined populations, randomly selected and clearly identified samples, and with blinding of investigators
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