scholarly journals Applying mixture model methods to SARS-CoV-2 serosurvey data from the SEROCoV-POP study

2021 ◽  
Author(s):  
Judith A Bouman ◽  
Sarah Kadelka ◽  
Silvia Stringhini ◽  
Francesco Pennacchio ◽  
Benjamin Meyer ◽  
...  
Keyword(s):  
Disease Severity ◽  
Mixture Model ◽  
Cumulative Incidence ◽  
Age Classes ◽  
Individual Values ◽  
Validation Data ◽  
Additional Information ◽  
Indirect Indicator ◽  
Antibody Levels

Serosurveys are an important tool to estimate the true extent of the current SARS-CoV-2 pandemic. So far, most serosurvey data have been analysed with cut-off based methods, which dichotomize individual measurements into sero-positives or negatives based on a predefined cutoff. However, mixture model methods can gain additional information from the same serosurvey data. Such methods refrain from dichotomizing individual values and instead use the full distribution of the serological measurements from pre-pandemic and COVID-19 controls to estimate the cumulative incidence. This study presents an application of mixture model methods to SARS-CoV-2 serosurvey data from the SEROCoV-POP study from April and May 2020 (2766 individuals). Besides estimating the total cumulative incidence in these data (8.1% (95% CI: 6.8% - 9.8%)), we applied extended mixture model methods to estimate an indirect indicator of disease severity, which is the fraction of cases with a distribution of antibody levels similar to hospitalised COVID-19 patients. This fraction is 51.2% (95% CI: 15.2% - 79.5%) across the full serosurvey, but differs between three age classes: 21.4% (95% CI: 0% - 59.6%) for individuals between 5 and 40 years old, 60.2% (95% CI: 21.5% - 100%) for individuals between 41 and 65 years old and 100% (95% CI: 20.1% - 100%) for individuals between 66 and 90 years old. Additionally, we find a mismatch between the inferred negative distribution of the serosurvey and the validation data of pre-pandemic controls. Overall, this study illustrates that mixture model methods can provide additional insights from serosurvey data.

scholarly journals Gaia Data Release 2

2018 ◽  
Vol 616 ◽  
pp. A13 ◽  
Author(s):  
◽  
F. Spoto ◽  
P. Tanga ◽  
F. Mignard ◽  
J. Berthier ◽  
...  
Keyword(s):  
Solar System ◽  
A Priori ◽  
European Space Agency ◽  
Dramatic Improvement ◽  
Individual Values ◽  
Data Set ◽  
Position Information ◽  
Additional Information ◽  
Space Agency ◽  
Data Release

Context. The Gaia spacecraft of the European Space Agency (ESA) has been securing observations of solar system objects (SSOs) since the beginning of its operations. Data Release 2 (DR2) contains the observations of a selected sample of 14,099 SSOs. These asteroids have been already identified and have been numbered by the Minor Planet Center repository. Positions are provided for each Gaia observation at CCD level. As additional information, complementary to astrometry, the apparent brightness of SSOs in the unfiltered G band is also provided for selected observations. Aims. We explain the processing of SSO data, and describe the criteria we used to select the sample published in Gaia DR2. We then explore the data set to assess its quality. Methods. To exploit the main data product for the solar system in Gaia DR2, which is the epoch astrometry of asteroids, it is necessary to take into account the unusual properties of the uncertainty, as the position information is nearly one-dimensional. When this aspect is handled appropriately, an orbit fit can be obtained with post-fit residuals that are overall consistent with the a-priori error model that was used to define individual values of the astrometric uncertainty. The role of both random and systematic errors is described. The distribution of residuals allowed us to identify possible contaminants in the data set (such as stars). Photometry in the G band was compared to computed values from reference asteroid shapes and to the flux registered at the corresponding epochs by the red and blue photometers (RP and BP). Results. The overall astrometric performance is close to the expectations, with an optimal range of brightness G ~ 12 − 17. In this range, the typical transit-level accuracy is well below 1 mas. For fainter asteroids, the growing photon noise deteriorates the performance. Asteroids brighter than G ~ 12 are affected by a lower performance of the processing of their signals. The dramatic improvement brought by Gaia DR2 astrometry of SSOs is demonstrated by comparisons to the archive data and by preliminary tests on the detection of subtle non-gravitational effects.

scholarly journals Improving SARS-CoV-2 cumulative incidence estimation through mixture modelling of antibody levels

2021 ◽  
Author(s):  
C. Bottomley ◽  
M. Otiende ◽  
S. Uyoga ◽  
K. Gallagher ◽  
E.W. Kagucia ◽  
...  
Keyword(s):  
Sensitivity And Specificity ◽  
Antibody Level ◽  
Cumulative Incidence ◽  
Model Estimate ◽  
Mixture Modelling ◽  
Seroprevalence Data ◽  
Incidence Estimation ◽  
Using Data ◽  
Serological Data ◽  
Antibody Levels

AbstractAs countries decide on vaccination strategies and how to ease movement restrictions, estimates of cumulative incidence of SARS-CoV-2 infection are essential in quantifying the extent to which populations remain susceptible to COVID-19. Cumulative incidence is usually estimated from seroprevalence data, where seropositives are defined by an arbitrary threshold antibody level, and adjusted for sensitivity and specificity at that threshold. This does not account for antibody waning nor for lower antibody levels in asymptomatic or mildly symptomatic cases. Mixture modelling can estimate cumulative incidence from antibody-level distributions without requiring adjustment for sensitivity and specificity. To illustrate the bias in standard threshold-based seroprevalence estimates, we compared both approaches using data from several Kenyan serosurveys. Compared to the mixture model estimate, threshold analysis underestimated cumulative incidence by 31% (IQR: 11 to 41) on average. Until more discriminating assays are available, mixture modelling offers an approach to reduce bias in estimates of cumulative incidence.One-Sentence SummaryMixture models reduce biases inherent in the standard threshold-based analysis of SARS-CoV-2 serological data.

scholarly journals Dynamic Alterations of Anti-S-Protein Igg Subclasses and of Th1/Th2 Responses are Hallmarks of Acute Severe COVID-19 Disease

2021 ◽  
Author(s):  
Yun Shan Goh ◽  
Siew-Wai Fong ◽  
Siti Naqiah Amrun ◽  
Cheryl Lee ◽  
Pei Xiang Hor ◽  
...  
Keyword(s):  
Disease Severity ◽  
Severe Disease ◽  
Th2 Response ◽  
S Protein ◽  
Th1 Response ◽  
Humoral Immune ◽  
Mild Disease ◽  
Humoral Immune Responses ◽  
Disease Spectrum ◽  
Antibody Levels

Abstract PurposeCOVID-19, caused by Severe Acute Respiratory Syndrome Coronavirus (SARS-CoV-2), has a wide disease spectrum ranging from asymptomatic to severe. While it is widely accepted that specific humoral immune responses are critical in controlling the infection, the relationship between the humoral immune response and disease severity is currently unclear.MethodsUsing a flow cytometry-based assay to detect specific antibodies against full length S protein, we compared the antibody levels between patients from different severity groups. We also analysed the cytokine profiles of patients from different severity groups by multiplex microbead-based immunoassay.ResultsWe found an association between specific IgM, IgA and IgG against the spike protein and disease severity. By comparing the ratio of Th1 IgG1 and IgG3 to Th2 IgG2 and IgG4, we observed that all severity groups exhibited a ratio that was skewed towards a stronger Th1 response over Th2 response. In addition to the strong Th1 response, patients with severe disease also developed a Th2 response, as exemplified by the smaller ratio of IgG1 and IgG3 over IgG2 and IgG4 and the smaller Th1/Th2 cytokine ratios, compared to patients with mild disease severity. ConclusionThe results suggest that acute severity or disease resolution is associated with a specific immunological phenotype. A smaller skew towards a Th1 response over Th2 response, during infection, may contribute to disease progression, while a greater skew towards a Th1 response over Th2 response may contribute to a better disease outcome. This may suggest potential therapeutic approaches to COVID-19 disease management.

scholarly journals Incidence and Risk Factors for Second Malignancies after Transplant in Long Term Survivors of Allogeneic Haematopoietic Stem Cell Transplant: A Single Centre Experience

Blood ◽  
2018 ◽  
Vol 132 (Supplement 1) ◽  
pp. 3417-3417
Author(s):  
Mohammed Snober ◽  
Richard Syzdlo ◽  
Jane Apperley ◽  
Aristeidis Chaidos ◽  
Edward Kanfer ◽  
...  
Keyword(s):  
Stem Cell ◽  
Cumulative Incidence ◽  
Haematopoietic Stem Cell ◽  
Cell Transplant ◽  
Second Malignancy ◽  
Second Malignancies ◽  
Additional Information ◽  
Increased Risk ◽  
High Index Of Suspicion

Abstract Second malignancies are well recognised complications of haematopoietic stem cell transplantation (HCT). The incidence increases with time after HCT with no evidence of plateau with follow up times of 15-20 years. In this study we have investigated patients over a 37-year period to include all patients transplanted at The Hammersmith hospital since 1979 who survived a minimum of two years after transplant. We aimed to describe the post-transplant malignancies (PTM) that occurred and calculate the cumulative incidence with time. Methods Data was gathered through internal databases and supplemented with case notes with all patients giving consent for their data to be used in clinical studies. Additional information on patients who had died at the time of analysis included review of death certificates for evidence of a second malignancy. If a patient had not been seen within 5 years evidence of death was sought on the NHS Spine and if apparently still alive, the date of last follow up was taken as follow up time. Second malignancies included second solid neoplasms (SSN), non-melanoma skin cancer (NMSC) and leukemias/lymphomas. These were recorded and categorised in accordance with the international classification of disease for oncology (ICD-O). Results 697 patients survived a minimum of two years after HCT between 1979-2018, 60% of whom were male. Follow up was prolonged with 20% of our 2-year survivors followed up for more than 20 years. The majority of patient (80%) were aged between 20-50 at time of HCT. (median age 35.6y, range 4-69) with only 7 patients < 10 y at HCT. The most frequent diagnoses were CML (n=463) or AML (n=103). The majority of patients (n=538, 77%) had received TBI, and the most frequently used conditioning was Cyclo-TBI (479 patients, 69%). At the time of analysis, 222 patients had died and of the remaining 475, 107 were lost to follow up. We identified 97 PTM in 87 patients a median of 14.2 years post HCT (range 0.8-35.9 years). These included 58 cases of SSN, 28 cases of NMSC and 11 cases of leukemia or lymphoma. The most frequent SSN were breast (n=12), tongue (n=7), colorectal (n=6), melanoma (n=5), bladder (n=4), thyroid (n=3) and oesophagus (n=3). Of 28 patients with NMSC, 19 developed one or more BCC and 9 developed SCC. The cumulative incidence of PTMs did not plateau with time. Cumulative incidences were as follows with 95% confidence intervals (CI) in parentheses: 4.9% (3.3-7.3) at 10 years, 12.2% (9.1-16.2) at 15 years, 22.5% (17.6-28.9) at 20 years, 39% (30.3-48.4) at 25 years and 53% (41.6-64.1) at 30 years. These data reflected the substantial increases in the CI of SSN and NMSC between these time points. For SSN the cumulative incidence increased from 3% (1.8-5) at 10 years to 37.9% (27.4-49.6) at 30 years; for NMSC the cumulative incidence increased from 1.3% (0.6-2.7) at 10 years 16.6% (9.2-28.2) at 30 years. In multivariate analyses older age (>50) at time of transplant was associated with significantly increased (p<0.01) risk of PTM with a relative risk (RR) of 4.53 (2.1-9.6). On subgroup analysis this was only relevant to SSN where the RR was 5.17 (2.2-12.1). Patient/donor sex combinations other than male patient/male donor were also at increased risk of PTM, RR 1.797 (1.1-2.9), p=0.033, and again this was only significant for SSN (RR 2.11, 1.13-3.93). Discussion and conclusions In this predominantly adult study, the cumulative incidence of SSN and NMSC increased substantially with time after HCT beyond a 10-year follow-up period. The risk was increased in patients who were >50 at time of HCT. Prolonged expert follow-up with a high index of suspicion for second malignancy in these patients is recommended to facilitate early diagnosis. Disclosures Apperley: Novartis: Honoraria, Research Funding, Speakers Bureau; Pfizer: Honoraria, Speakers Bureau; BMS: Honoraria, Speakers Bureau; Incyte: Honoraria, Speakers Bureau. Milojkovic:Incyte: Honoraria, Speakers Bureau; BMS: Honoraria, Speakers Bureau; Pfizer: Honoraria, Speakers Bureau; Novartis: Honoraria, Speakers Bureau.

scholarly journals The Effects of Yoga Practice on Practitioners' Environmental Behaviours & Sustainability

2021 ◽  
Vol 10 (3) ◽  
pp. 76
Author(s):  
Aglaia Zafeiroudi ◽  
Mathildi Pipinia ◽  
Georgia Yfantidou ◽  
Sotiriοs Georgomanos
Keyword(s):  
Codes Of Conduct ◽  
Leisure Activity ◽  
Yoga Practice ◽  
Individual Values ◽  
Test Analysis ◽  
Environmental Behaviour ◽  
Additional Information ◽  
Responsible Behaviour ◽  
The Individual ◽  
Environmental Behaviours

Yoga philosophy includes ethical codes of conduct, guidelines, meditation and other practices that respect the Earth, its natural resources, humans and other living beings. The purpose of the present study was to investigate the effects of yoga practice on practitioners' environmental behaviours and sustainability. A total of 195 adults (66 men and 129 women) from two cities in Greece participated in this study. The participants completed the General Environmental Responsible Behaviour scale (Zafeiroudi & Hatzigeorgiadis, 2013) and provided additional information about their personal lifestyles, leisure activity preferences and frequency of participation in outdoor activities. Independent sample T-test analysis was used to investigate differences between practitioners' demographics and the General Environmental Responsible Behaviour scale as the dependent variable. The results indicated statistically significant differences in environmental behaviour scores among practitioners in different yoga demographics. On the basis of yoga philosophy, the study findings suggested that participation in yoga practices strengthens beliefs, behaviours and awareness regarding the environment. The individual values taught by the philosophy of yoga also foster friendlier attitudes and behaviours towards the environment. Moreover, the findings indicated that yoga practice might be an effective supplement and tool to promote green sustainable programs currently run by environmental and social organizations.

Repeated Anticitrullinated Protein Antibody and Rheumatoid Factor Assessment Is Not Necessary in Early Arthritis: Results from the ESPOIR Cohort

2013 ◽  
Vol 41 (1) ◽  
pp. 41-46 ◽  
Author(s):  
Laure Gossec ◽  
Simon Paternotte ◽  
Bernard Combe ◽  
Olivier Meyer ◽  
Maxime Dougados
Keyword(s):  
Rheumatoid Factor ◽  
Early Arthritis ◽  
Repeated Measurements ◽  
Symptom Duration ◽  
Undifferentiated Arthritis ◽  
Additional Information ◽  
American College Of Rheumatology ◽  
European League Against Rheumatism ◽  
Antibody Levels ◽  
Citrullinated Peptide

Objective.Presence and levels of anticyclic citrullinated peptide antibodies (anti-CCP) and rheumatoid factor (RF) contribute to the classification and prognosis of rheumatoid arthritis (RA). The objective was to determine the usefulness of repeating anti-CCP/RF measurements during the first 2 years of followup in patients with early arthritis.Methods.In patients with early undifferentiated arthritis, serial anti-CCP and RF were measured using automated second-generation assays every 6 months for 2 years. Frequencies of seroconversions (from negative to positive or the reverse) and changes in antibody levels during followup were determined.Results.In all, 775 patients, mean (SD) age 48.2 (12.5) years, mean symptom duration 3.4 (1.7) months, 76.6% female, were analyzed; 614 (79.2%) satisfied the American College of Rheumatology/European League Against Rheumatism 2010 classification criteria for RA at baseline. At baseline, respectively for anti-CCP and RF, 318 (41.0%) and 181 (23.4%) patients were positive, of whom 298 (93.7% of the positive) and 111 (61.3% of the positive) were highly positive (above 3 × upper limit of the norm). There were only 12 anti-CCP seroconversions toward the positive (i.e., 2.6% of the anti-CCP–negative), 21 seroconversions toward the negative (6.6% of the anti-CCP–positive), and 8 (1.0%) changes to a higher anti-CCP level category during the 2-year followup; respectively for RF, 27 (4.6%), 95 (52.5%), and 13 (1.7%).Conclusion.In this cohort of patients with early arthritis, including in the subset of patients who did not fulfill the RA criteria, antibody status showed little increase over a 2-year period. Repeated measurements of anti-CCP/RF very infrequently offer significant additional information.

Axisymmetric afterbody experiments for CFD validation

1994 ◽  
Vol 98 (974) ◽  
pp. 137-146
Author(s):  
P. Miller ◽  
J. Agrell ◽  
J. Olsson ◽  
K. Sjörs
Keyword(s):  
Cost Effective ◽  
Cfd Validation ◽  
Validation Data ◽  
Additional Information ◽  
Flow Features ◽  
The Mean ◽  
Flow Components ◽  
Jet Plumes ◽  
Spatial Locations ◽  
Proper Account

Summary An experiment is described which was undertaken specifically to provide CFD validation data for the case of transonic flow over nozzle afterbodies. The tests were undertaken with the AGARD standard 10° and 15° axisymmetric boat-tail geometries. Onset Mach numbers in the range 0·80-0·99 and subsonic and under-expanded jet plumes were employed in the tests. Test conditions were selected which provided a range of afterbody flow features from largely attached to shock-induced separated flows. A uniquely detailed set of surface pressure and flowfield data are presented. The flow data were acquired with a two-component laser Doppler anemometer (LDA) and define the mean and fluctuating flow components at about 500 spatial locations for each of these complex transonic flowfields. Additional information was recorded which fully defines the required computational boundary conditions. Also presented is a detailed study of the necessary attributes of windtunnel CFD validation data. It is demonstrated that relatively high blockage experiments using cost-effective windtunnels can be used to generate CFD validation data if proper account is taken of the model/tunnel interference.

scholarly journals Lymphocyte–monocyte–neutrophil index: a predictor of severity of coronavirus disease 2019 patients produced by sparse principal component analysis

2021 ◽  
Vol 18 (1) ◽  
Author(s):  
Yingjie Qi ◽  
Jian-an Jia ◽  
Huiming Li ◽  
Nagen Wan ◽  
Shuqin Zhang ◽  
...  
Keyword(s):  
Principal Component Analysis ◽  
Prediction Model ◽  
Disease Severity ◽  
Prediction Models ◽  
Principal Component ◽  
Component Analysis ◽  
Sparse Principal Component Analysis ◽  
Validation Data ◽  
Severity Prediction ◽  
Prediction Efficiency

Abstract Background It is important to recognize the coronavirus disease 2019 (COVID-19) patients in severe conditions from moderate ones, thus more effective predictors should be developed. Methods Clinical indicators of COVID-19 patients from two independent cohorts (Training data: Hefei Cohort, 82 patients; Validation data: Nanchang Cohort, 169 patients) were retrospected. Sparse principal component analysis (SPCA) using Hefei Cohort was performed and prediction models were deduced. Prediction results were evaluated by receiver operator characteristic curve and decision curve analysis (DCA) in above two cohorts. Results SPCA using Hefei Cohort revealed that the first 13 principal components (PCs) account for 80.8% of the total variance of original data. The PC1 and PC12 were significantly associated with disease severity with odds ratio of 4.049 and 3.318, respectively. They were used to construct prediction model, named Model-A. In disease severity prediction, Model-A gave the best prediction efficiency with area under curve (AUC) of 0.867 and 0.835 in Hefei and Nanchang Cohort, respectively. Model-A’s simplified version, named as LMN index, gave comparable prediction efficiency as classical clinical markers with AUC of 0.837 and 0.800 in training and validation cohort, respectively. According to DCA, Model-A gave slightly better performance than others and LMN index showed similar performance as albumin or neutrophil-to-lymphocyte ratio. Conclusions Prediction models produced by SPCA showed robust disease severity prediction efficiency for COVID-19 patients and have the potential for clinical application.

scholarly journals A Competing Risk Nomogram for Predicting Cancer-Specific Death of Patients With Maxillary Sinus Carcinoma

2021 ◽  
Vol 11 ◽  
Author(s):  
Mingbin Hu ◽  
Xiancai Li ◽  
Weiguo Gu ◽  
Jinhong Mei ◽  
Dewu Liu ◽  
...  
Keyword(s):  
Maxillary Sinus ◽  
Cumulative Incidence ◽  
External Validation ◽  
Competing Risk ◽  
Validation Data ◽  
Data Set ◽  
Internal Validation ◽  
Data Resource ◽  
Seer Data ◽  
Risk Of Cancer

ObjectivesHerein, we purposed to establish and verify a competing risk nomogram for estimating the risk of cancer-specific death (CSD) in Maxillary Sinus Carcinoma (MSC) patients.MethodsThe data of individuals with MSC used in this study was abstracted from the (SEER) Surveillance, Epidemiology, and End Results data resource as well as from the First Affiliated Hospital of Nanchang University (China). The risk predictors linked to CSD were identified using the CIF (cumulative incidence function) along with the Fine-Gray proportional hazards model on the basis of univariate analysis coupled with multivariate analysis implemented in the R-software. After that, a nomogram was created and verified to estimate the three- and five-year CSD probability.ResultsOverall, 478 individuals with MSC were enrolled from the SEER data resource, with a 3- and 5-year cumulative incidence of CSD after diagnosis of 42.1% and 44.3%, respectively. The Fine-Gray analysis illustrated that age, histological type, N stage, grade, surgery, and T stage were independent predictors linked to CSD in the SEER-training data set (n = 343). These variables were incorporated in the prediction nomogram. The nomogram was well calibrated and it demonstrated a remarkable estimation accuracy in the internal validation data set (n = 135) abstracted from the SEER data resource and the external validation data set (n = 200). The nomograms were well-calibrated and had a good discriminative ability with concordance indexes (c-indexes) of 0.810, 0.761, and 0.755 for the 3- and 5-year prognosis prediction of MSC-specific mortality in the training cohort, internal validation, and external validation cohort, respectively.ConclusionsThe competing risk nomogram constructed herein proved to be an optimal assistant tool for estimating CSD in individuals with MSC.

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