scholarly journals Analysis of cutoff point estimation for determining seropositivity in the context of SARS-CoV-2 infections

2021 ◽  
Author(s):  
Tiago Dias Domingues ◽  
Helena Mourino ◽  
Nuno Sepulveda
Keyword(s):  
Mixture Models ◽  
Performance Measures ◽  
Simulation Study ◽  
A Priori ◽  
Point Estimation ◽  
Cutoff Point ◽  
Infection Status ◽  
Virus Antigens ◽  
True Infection ◽  
Sensitivity Specificity

In this work will apply mixture models based on distributions from the SMSN family to antibody data against four SARS-CoV-2 virus antigens. Furthermore, since the true infection status of individuals is known a priori, performance measures will be calculated for the methods proposed for cutoff point estimation such as sensitivity, specificity and accuracy. The results of a simulation study will also be presented.

scholarly journals 468. Specimen pooling conserves additional testing resources when patients’ infection status is correlated: A simulation study

2020 ◽  
Vol 7 (Supplement_1) ◽  
pp. S300-S300
Author(s):  
Jeffrey Rewley
Keyword(s):  
Internal Medicine ◽  
Simulation Study ◽  
No Reduction ◽  
Optimal Size ◽  
Infection Status ◽  
Heat Map ◽  
Population Prevalence ◽  
Additional Testing ◽  
Batch Sizes ◽  
Pooled Sample

Abstract Background In the early stages of a novel pandemic, testing is simultaneously in high need but low supply, making efficient use of tests of paramount importance. One approach to improve the efficiency of tests is to mix samples from multiple individuals, only testing individuals when the pooled sample returns a positive. Methods I build on current models which assume patients’ sero-status is independent by allowing for correlation betweenconsecutive tests (e.g. if a family were all infected and were all tested together). In this model, I simulate 10,000 patients being tested in sequence, with population sero-prevalence ranging from 1% to 25%, using batch sizes from 3 to 10, and assuming the increased probability of consecutive infections ranged from 0% to 50%. Results I find that as the likelihood of consecutive infected patients increases, the efficiency of specimen pooling increases. As well, the optimal size of the batch increases in the presence of clustered sequences of infected patients. Heat map indicating the manner in which the number of tests needed is reduced as population prevalence and correlation between cases changes. Red indicates that there is no reduction in the number of tests, and blue indicates a near 100% reduction in the number of tests, with intermediate colors indicating intermediate fractions. Conclusion This analysis indicates further improvements in specimen pooling efficiency can begained by taking advantage of the pattern of patient testing. Disclosures Jeffrey Rewley, PhD, MS, American Board of Internal Medicine (Employee)

scholarly journals Identification of Cytokines in Whole Blood for Differential Diagnosis of Tuberculosis versus Pneumonia

2010 ◽  
Vol 17 (5) ◽  
pp. 771-777 ◽  
Author(s):  
Wen-Lin Su ◽  
Wann-Cherng Perng ◽  
Ching-Hui Huang ◽  
Cheng-Yu Yang ◽  
Chin-Pyng Wu ◽  
...  
Keyword(s):  
Whole Blood ◽  
Blood Cells ◽  
Cutoff Point ◽  
Interleukin 12 ◽  
Operating Characteristics ◽  
Percent Change ◽  
Ifn Γ ◽  
Sensitivity Specificity ◽  
Whole Blood Cells ◽  
Stimulation Of

ABSTRACT Differentiating tuberculosis (TB) from pneumonia remains a challenge. We evaluated the cytokine profiles of whole blood cells from patients with TB (n = 38) or pneumonia (n = 30) and from healthy individuals (n = 30) before and after stimulating cells with ESAT-6 or lipopolysaccharide (LPS). When the percent change in the levels of gamma interferon (IFN-γ) after stimulation with ESAT-6 was used in receiver operating characteristics (ROC) analysis (a graphic method to determine the diagnostic accuracy of a test) to identify a patient with TB, the area under the curve (AUC) was 90.4%, and a cutoff point of a 3.59% change produced a corresponding sensitivity, specificity, and accuracy of over 80%. When the change in IFN-γ after stimulation of blood cells with LPS was used to identify a patient with pneumonia, the AUC reached 89.1%, and a cutoff point of 3.59% produced a sensitivity, specificity, and accuracy of approximately 80% each. When the change in interleukin-12 (IL-12) after stimulation of blood cells with LPS was selected to define a patient with pneumonia, the AUC was 85.2%, and a cutoff point of 2.08% gave a sensitivity, specificity, and accuracy of 80.0%, 78.9%, and 79.4%, respectively. We conclude that the percent change in IFN-γ after stimulation of whole blood cells with ESAT-6 may differentiate patients with TB from patients with pneumonia. The percent change in IFN-γ and IL-12 after LPS stimulation of whole blood cells could differentiate patients with pneumonia from patients with TB.

scholarly journals An Associational Examination of the CaptialCube Effect Context for the MPV over the Linguistic Partitions: Testing Sensitivity & Specificity

2017 ◽  
Vol 6 (2) ◽  
pp. 1
Author(s):  
Edward J. Lusk ◽  
Michael Halperin
Keyword(s):  
A Priori ◽  
Market Performance ◽  
Random Processes ◽  
Random Selection ◽  
Testing Model ◽  
Performance Variables ◽  
Market Effects ◽  
Median Split ◽  
Sensitivity Specificity ◽  
Testing Protocols

In this third examination of the CapitalCubeÔ Market Navigation Platform [CCMNP] we have selected the previously vetted set of embedded variables: Market Performance Variables [MPV] for their Linguistic Qualifiers [LQ] considering their directional market effects or MPV[LQ[{Neutral: Unfavorable: Favorable}]]. In the testing, we are interested in the Sensitivity and the Specificity of these vetted variables over the annual S&P500 Panel from 2005 to 2013. The inference framework employed a Median Split: High or Low for each of the 13 MPV tested and a random selection to avoid the FPE-jeopardy that is part of the Chi2 testing model. We used the Tamhane & Dunlop cut-off to identify Chi2 cells effects of interest and used these to develop the Sensitivity and the Specificity tests. Results: We were able to reject the a priori Nulls proffered for the testing protocols indicating that one may reject the supposition that the labeling of the LQ is formed by random processes in the CCMNP.     

Modeling the crashes count using finite mixture models

2019 ◽  
Vol 7 (1) ◽  
pp. 13-27
Author(s):  
Safaa K. Kadhem ◽  
Sadeq A. Kadhim
Keyword(s):  
Bayesian Inference ◽  
Mixture Models ◽  
Gibbs Sampler ◽  
Simulation Study ◽  
Finite Mixture Models ◽  
Synthetic Data ◽  
Finite Mixture Model ◽  
Finite Mixture ◽  
Model Parameters ◽  
Mcmc Method

"This paper aims at the modeling the crashes count in Al Muthanna governance using finite mixture model. We use one of the most common MCMC method which is called the Gibbs sampler to implement the Bayesian inference for estimating the model parameters. We perform a simulation study, based on synthetic data, to check the ability of the sampler to find the best estimates of the model. We use the two well-known criteria, which are the AIC and BIC, to determine the best model fitted to the data. Finally, we apply our sampler to model the crashes count in Al Muthanna governance.

scholarly journals Construct and Criterion Validity of the Postmenopause Sexuality Questionnaire – PMSQ

2020 ◽  
Vol 42 (01) ◽  
pp. 026-034
Author(s):  
Maria José Ferreira Lima ◽  
Marília Duarte Valim ◽  
Sebastião Freitas de Medeiros
Keyword(s):  
Factor Analysis ◽  
Sexual Function ◽  
Postmenopausal Women ◽  
Strong Correlation ◽  
Criterion Validity ◽  
Cutoff Point ◽  
Questionnaire Validation ◽  
Future Studies ◽  
Different Populations ◽  
Sensitivity Specificity

Abstract Objective To assess the construct and criterion validity of the Postmenopause Sexuality Questionnaire (PMSQ). Methods The present methodological questionnaire validation study included postmenopausal women. The construct validity was tested by factor analysis and the criterion validity was performed using the correlation between the PMSQ and the Female Sexual Function Index (FSFI). The ROC curve was used to verify sensitivity, specificity and to determine the cutoff point of the PMSQ. Results A total of 181 women with a mean age of 56.4 ± 5.7 years old were evaluated. The exploratory factor analysis showed that the PMSQ presented Kaiser test = 0.88 and χ2 = 3293.7 (p < 0.001), commonalities ≥ 0.5, and extraction of 9 factors with eigenvalue ≥ 1; explaining 66.3% of the total variance. The PMSQ presented factor loadings between 0.4 and 0.8. A strong correlation between the 2 questionnaires (r = 0.79; p = 0.000) was shown. The cutoff point of the PMSQ was ≤ 55.5, assuming 87.9% sensitivity and 78.9% specificity (p < 0.001). Conclusion Since the PMSQ showed a strong correlation with the FSFI questionnaire, it presented good psychometric properties to assess the sexuality in postmenopausal women. Based on these results, the PMSQ could be widely tested as a specific instrument to examine the sexual function in postmenopausal women. Future studies, designed to examine the PMSQ instrument in different populations, are needed.

scholarly journals The influence of a priori grouping on inference of genetic clusters: simulation study and literature review of the DAPC method

Heredity ◽  
2020 ◽  
Vol 125 (5) ◽  
pp. 269-280 ◽  
Author(s):  
Joshua M. Miller ◽  
Catherine I. Cullingham ◽  
Rhiannon M. Peery
Keyword(s):  
Discriminant Analysis ◽  
Literature Review ◽  
Simulation Study ◽  
De Novo ◽  
A Priori ◽  
Principal Component ◽  
Migration Rates ◽  
Genetic Clusters ◽  
Genetic Clustering ◽  
Structure Versus

Abstract Inference of genetic clusters is a key aim of population genetics, sparking development of numerous analytical methods. Within these, there is a conceptual divide between finding de novo structure versus assessment of a priori groups. Recently developed, Discriminant Analysis of Principal Components (DAPC), combines discriminant analysis (DA) with principal component (PC) analysis. When applying DAPC, the groups used in the DA (specified a priori or described de novo) need to be carefully assessed. While DAPC has rapidly become a core technique, the sensitivity of the method to misspecification of groups and how it is being empirically applied, are unknown. To address this, we conducted a simulation study examining the influence of a priori versus de novo group designations, and a literature review of how DAPC is being applied. We found that with a priori groupings, distance between genetic clusters reflected underlying FST. However, when migration rates were high and groups were described de novo there was considerable inaccuracy, both in terms of the number of genetic clusters suggested and placement of individuals into those clusters. Nearly all (90.1%) of 224 studies surveyed used DAPC to find de novo clusters, and for the majority (62.5%) the stated goal matched the results. However, most studies (52.3%) omit key run parameters, preventing repeatability and transparency. Therefore, we present recommendations for standard reporting of parameters used in DAPC analyses. The influence of groupings in genetic clustering is not unique to DAPC, and researchers need to consider their goal and which methods will be most appropriate.

Polynomial regression with heteroscedastic measurement errors in both axes: Estimation and hypothesis testing

2018 ◽  
Vol 28 (9) ◽  
pp. 2681-2696
Author(s):  
Chi-Lun Cheng ◽  
Jia-Ren Tsai ◽  
Hans Schneeweiss
Keyword(s):  
Hypothesis Testing ◽  
Simulation Study ◽  
Measurement Errors ◽  
Polynomial Regression ◽  
Least Squares Method ◽  
Structural Models ◽  
Point Estimation ◽  
Equation Error ◽  
Adjusted Least Squares ◽  
Polynomial Regression Model

This article investigates point estimation and hypothesis testing in a polynomial regression model with heteroscedastic measurement errors present in both response and regressor variables. For point estimation, the adjusted least squares method and its modifications are developed. These methods can treat both functional and structural models, and models with or without an equation error. For hypothesis testing, the Wald-type and score-type tests are discussed. Their performance is investigated in a simulation study. Applications of these methods are also illustrated with real datasets.

scholarly journals Nuclear imaging does not have clear added value in patients with low a priori chance of periprosthetic joint infection. A retrospective single-center experience

2022 ◽  
Vol 7 (1) ◽  
pp. 1-9
Author(s):  
Karsten D. Ottink ◽  
Stefan J. Gelderman ◽  
Marjan Wouthuyzen-Bakker ◽  
Joris J. W. Ploegmakers ◽  
Andor W. J. M. Glaudemans ◽  
...  
Keyword(s):  
Diagnostic Accuracy ◽  
Revision Surgery ◽  
Periprosthetic Joint Infection ◽  
Joint Infection ◽  
A Priori ◽  
Nuclear Imaging ◽  
Added Value ◽  
Low Grade ◽  
Predictive Values ◽  
Sensitivity Specificity

Abstract. Background: A low-grade periprosthetic joint infection (PJI) may present without specific symptoms, and its diagnosis remains a challenge. Three-phase bone scintigraphy (TPBS) and white blood cell (WBC) scintigraphy are incorporated into recently introduced diagnostic criteria for PJI, but their exact value in diagnosing low-grade PJI in patients with nonspecific symptoms remains unclear. Methods: In this retrospective study, we evaluated patients with a prosthetic joint of the hip or knee who underwent TPBS and/or WBC scintigraphy between 2009 and 2016 because of nonspecific symptoms. We reviewed and calculated diagnostic accuracy of the TPBS and/or WBC scintigraphy to diagnose or exclude PJI. PJI was defined based on multiple cultures obtained during revision surgery. In patients who did not undergo revision surgery, PJI was ruled out by clinical follow-up of at least 2 years absent of clinical signs of infection based on MSIS 2011 criteria. Results: A total of 373 patients were evaluated, including 340 TPBSs and 142 WBC scintigraphies. Thirteen patients (3.5 %) were diagnosed with a PJI. TPBS sensitivity, specificity, and positive and negative predictive values (PPV, NPV) were 71 %, 65 %, 8 % and 98 %, respectively. Thirty-five percent of TPBS showed increased uptake. Stratification for time intervals between the index arthroplasty and the onset of symptoms did not alter its diagnostic accuracy. WBC scintigraphy sensitivity, specificity, PPV and NPV were 30 %, 90 %, 25 % and 94 %, respectively. Conclusion: Nuclear imaging does not have clear added value in patients with low a priori chance of periprosthetic joint infection.

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