scholarly journals Predictive values, uncertainty, and interpretation of serology tests for the novel coronavirus

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Naomi C. Brownstein ◽  
Yian Ann Chen
Keyword(s):  
Disease Burden ◽  
False Negative ◽  
False Negative Rate ◽  
Supplementary Information ◽  
The Novel ◽  
Positive Serology ◽  
Predictive Values ◽  
Infected People ◽  
Novel Coronavirus ◽  
Different Levels

AbstractAntibodies testing in the coronavirus era is frequently promoted, but the underlying statistics behind their validation has come under more scrutiny in recent weeks. We provide calculations, interpretations, and plots of positive and negative predictive values under a variety of scenarios. Prevalence, sensitivity, and specificity are estimated within ranges of values from researchers and antibodies manufacturers. Illustrative examples are highlighted, and interactive plots are provided in the Supplementary Information. Implications are discussed for society overall and across diverse locations with different levels of disease burden. Specifically, the proportion of positive serology tests that are false can differ drastically from up to 3%–88% for people from different places with different proportions of infected people in the populations while the false negative rate is typically under 10%.

scholarly journals Are antibodies tests accurate? Understanding predictive values and uncertainty of serology tests for the novel coronavirus

2020 ◽  
Author(s):  
Naomi C Brownstein ◽  
Yian Ann Chen
Keyword(s):  
Disease Burden ◽  
False Negative ◽  
False Negative Rate ◽  
The Novel ◽  
Positive Serology ◽  
Predictive Values ◽  
Infected People ◽  
Supplementary Material ◽  
Novel Coronavirus ◽  
Different Levels

ABSTRACTAntibodies testing in the coronavirus era is frequently promoted, but the underlying statistics behind their validation has come under more scrutiny in recent weeks. We provide calculations, interpretations, and plots of positive and negative predictive values under a variety of scenarios. Prevalence, sensitivity, and specificity are estimated within ranges of values from researchers and antibodies manufacturers. Illustrative examples are highlighted, and interactive plots are provided in the Supplementary Material. Implications are discussed for society overall and across diverse locations with different levels of disease burden. Specifically, the proportion of positive serology tests that are false can differ drastically from up to 3% to 88% for people from different places with different proportions of infected people in the populations while the false negative rate is typically under 10%.

The Challenges of Biomedical Waste Management During the Ongoing Coronavirus Disease-19 (COVID-19) Pandemic: The Current Scenario

2021 ◽  
Vol 13 ◽  
Author(s):  
Sabitha Vadakedath ◽  
Venkataramana Kandi ◽  
Tarun Kumar Suvvari ◽  
L V Simhachalam Kutikuppala ◽  
Vikram Godishala ◽  
...  
Keyword(s):  
Healthcare Workers ◽  
Complex Nature ◽  
The Novel ◽  
Waste Collection ◽  
Biomedical Waste ◽  
Infected People ◽  
Life Threatening ◽  
Current Scenario ◽  
Constant Observation ◽  
Novel Coronavirus

: The novel Coronavirus (SARS-CoV-2) that has emerged and spread throughout the world causing CoV disease-19 (COVID-19) has since its discovery affected not only humans and animals but also the environment. Because of the highly infectious nature of the virus, and the respiratory aerosol transmission route, face masks and personal protective equipment have become mandatory for public and healthcare workers, respectively. Also, the complex nature of the pathogenicity of the virus, wherein, it has been associated with mild, moderate, and severe life-threatening infections, has warranted increased laboratory testing and placing the infected people in isolation and under constant observation in quarantine centers or at dedicated hospitals. Some infected people, who are generally healthy, and do not show symptoms have been placed in home quarantines. At this juncture, there has been increased amount of biomedical waste (BMW), and infectious general waste along with plastic disposable recyclable and non-recyclable waste. The increased BMW along with the potentially hazardous plastic waste collection, segregation, transport, and disposal has assumed increased significance during the ongoing pandemic. Therefore, this review attempts to investigate the current scenario of BMW management and strategies to minimize BMW and prevent potential environmental pollution.

scholarly journals Prospective Study Comparing Deep Throat Saliva With Other Respiratory Tract Specimens in the Diagnosis of Novel Coronavirus Disease 2019

2020 ◽  
Vol 222 (10) ◽  
pp. 1612-1619 ◽  
Author(s):  
Christopher K C Lai ◽  
Zigui Chen ◽  
Grace Lui ◽  
Lowell Ling ◽  
Timothy Li ◽  
...  
Keyword(s):  
Prospective Study ◽  
Pearson Correlation ◽  
False Negative ◽  
False Negative Rate ◽  
Productive Cough ◽  
Rt Pcr ◽  
Virus Shedding ◽  
Positive Rate ◽  
Novel Coronavirus ◽  
Rna Concentration

Abstract Background Self-collected specimens have been advocated to avoid infectious exposure to healthcare workers. Self-induced sputum in those with a productive cough and saliva in those without a productive cough have been proposed, but sensitivity remains uncertain. Methods We performed a prospective study in 2 regional hospitals in Hong Kong. Results We prospectively examined 563 serial samples collected during the virus shedding periods of 50 patients: 150 deep throat saliva (DTS), 309 pooled-nasopharyngeal (NP) and throat swabs, and 104 sputum. Deep throat saliva had the lowest overall reverse-transcriptase polymerase chain reaction (RT-PCR)-positive rate (68.7% vs 89.4% [sputum] and 80.9% [pooled NP and throat swabs]) and the lowest viral ribonucleic acid (RNA) concentration (mean log copy/mL 3.54 vs 5.03 [sputum] and 4.63 [pooled NP and throat swabs]). Analyses with respect to time from symptom onset and severity also revealed similar results. Virus yields of DTS correlated with that of sputum (Pearson correlation index 0.76; 95% confidence interval, 0.62–0.86). We estimated that the overall false-negative rate of DTS could be as high as 31.3% and increased 2.7 times among patients without sputum. Conclusions Deep throat saliva produced the lowest viral RNA concentration and RT-PCR-positive rate compared with conventional respiratory specimens in all phases of illness. Self-collected sputum should be the choice for patients with sputum.

scholarly journals SARS2020: an integrated platform for identification of novel coronavirus by a consensus sequence-function model

2020 ◽  
Author(s):  
Dachuan Zhang ◽  
Tong Zhang ◽  
Sheng Liu ◽  
Dandan Sun ◽  
Shaozhen Ding ◽  
...  
Keyword(s):  
Biological Function ◽  
Consensus Sequence ◽  
Rapid Identification ◽  
Data Driven ◽  
Supplementary Information ◽  
Respiratory Syndrome Virus ◽  
The Novel ◽  
Function Model ◽  
Catalytic Function ◽  
Novel Coronavirus

Abstract Motivation The 2019 novel coronavirus outbreak has significantly affected global health and society. Thus, predicting biological function from pathogen sequence is crucial and urgently needed. However, little work has been conducted to identify viruses by the enzymes that they encode, and which are key to pathogen propagation. Results We built a comprehensive scientific resource, SARS2020, which integrates coronavirus-related research, genomic sequences and results of anti-viral drug trials. In addition, we built a consensus sequence-catalytic function model from which we identified the novel coronavirus as encoding the same proteinase as the severe acute respiratory syndrome virus. This data-driven sequence-based strategy will enable rapid identification of agents responsible for future epidemics. Availabilityand implementation SARS2020 is available at http://design.rxnfinder.org/sars2020/. Supplementary information Supplementary data are available at Bioinformatics online.

scholarly journals Screening for Major Depression in the Early Stages of Multiple Sclerosis

1995 ◽  
Vol 22 (3) ◽  
pp. 228-231 ◽  
Author(s):  
Michael J.L. Sullivan ◽  
Brian Weinshenker ◽  
Samuel Mikail ◽  
Scott R. Bishop
Keyword(s):  
Multiple Sclerosis ◽  
Major Depression ◽  
Clinical Utility ◽  
False Negative ◽  
False Negative Rate ◽  
Adjustment Disorder ◽  
Structured Interview ◽  
Newly Diagnosed ◽  
Predictive Values ◽  
Screening Measure

AbstractBackgroundMultiple Sclerosis (MS) is associated with a high risk of developing major depression, but depression in MS patients frequently goes undetected and untreated. The current study examined the clinical utility of the Beck Depression Inventory (BDI) as a screening measure for major depression in newly diagnosed MS patients.MethodsForty-six new referrals to an MS clinic completed the BDI and participated in a structured interview for major depression, within 2 months of the diagnosis of MS.ResultsAccording to DSM-III-R criteria, 40% of patients were diagnosed with major depression, 22% had adjustment disorder with depressed mood, and 37% showed no evidence of mood disorder. Sensitivity and specificity values, and positive and negative predictive values are reported for every BDI cut-off score between 9 and 21.ConclusionsA BDI cut-off score of 13 (sensitivity = .71, specificity = .79) is recommended as optimal for use in screening for major depression in newly diagnosed MS patients. The use of the BDI as a screening measure for major depression must proceed with caution given that a cut-off score of 13 still yielded a false-negative rate of 30%.

scholarly journals A Deep-Learning-Based Framework for Automated Diagnosis of COVID-19 Using X-ray Images

Information ◽  
2020 ◽  
Vol 11 (9) ◽  
pp. 419 ◽  
Author(s):  
Irfan Ullah Khan ◽  
Nida Aslam
Keyword(s):  
Deep Learning ◽  
False Negative ◽  
False Negative Rate ◽  
Complex Nature ◽  
Learning Models ◽  
Daily Lives ◽  
X Ray ◽  
High False Negative Rate ◽  
Diagnosis Method ◽  
Novel Coronavirus

The emergence and outbreak of the novel coronavirus (COVID-19) had a devasting effect on global health, the economy, and individuals’ daily lives. Timely diagnosis of COVID-19 is a crucial task, as it reduces the risk of pandemic spread, and early treatment will save patients’ life. Due to the time-consuming, complex nature, and high false-negative rate of the gold-standard RT-PCR test used for the diagnosis of COVID-19, the need for an additional diagnosis method has increased. Studies have proved the significance of X-ray images for the diagnosis of COVID-19. The dissemination of deep-learning techniques on X-ray images can automate the diagnosis process and serve as an assistive tool for radiologists. In this study, we used four deep-learning models—DenseNet121, ResNet50, VGG16, and VGG19—using the transfer-learning concept for the diagnosis of X-ray images as COVID-19 or normal. In the proposed study, VGG16 and VGG19 outperformed the other two deep-learning models. The study achieved an overall classification accuracy of 99.3%.

scholarly journals Reducing the Number of Unnecessary Thyroid Biopsies While Improving Diagnostic Accuracy: Toward the “Right” TIRADS

2018 ◽  
Vol 104 (1) ◽  
pp. 95-102 ◽  
Author(s):  
Giorgio Grani ◽  
Livia Lamartina ◽  
Valeria Ascoli ◽  
Daniela Bosco ◽  
Marco Biffoni ◽  
...  
Keyword(s):  
Risk Stratification ◽  
Thyroid Nodules ◽  
False Negative ◽  
False Negative Rate ◽  
Needle Aspiration ◽  
Classification Systems ◽  
American Thyroid Association ◽  
Predictive Values ◽  
Korean Society ◽  
The Right

Abstract Context The prevalence of thyroid nodules in the general population is increasingly high, and at least half of those biopsied prove to be benign. Sonographic risk-stratification systems are being proposed as “rule-out” tests that can identify nodules that do not require fine-needle aspiration (FNA) cytology. Objective To comparatively assess the performances of five internationally endorsed sonographic classification systems [those of the American Thyroid Association, the American Association of Clinical Endocrinologists, the American College of Radiology (ACR), the European Thyroid Association, and the Korean Society of Thyroid Radiology] in identifying nodules whose FNAs can be safely deferred and to estimate their negative predictive values (NPVs). Design Prospective study of thyroid nodules referred for FNA. Setting Single academic referral center. Patients Four hundred seventy-seven patients (358 females, 75.2%); mean (SD) age, 55.9 (13.9) years. Main Outcome Measures Number of biopsies classified as unnecessary, false-negative rate (FNR), sensitivity, specificity, predictive values, and diagnostic ORs for each system. Results Application of the systems’ FNA criteria would have reduced the number of biopsies performed by 17.1% to 53.4%. The ACR Thyroid Imaging Reporting and Data System (TIRADS) allowed the largest reduction (268 of 502) with the lowest FNR (NPV, 97.8%; 95% CI, 95.2% to 99.2%). Except for the Korean Society of Thyroid Radiology TIRADS, all other systems exhibited significant discriminatory performance but produced significantly smaller reductions in the number of procedures. Conclusions Internationally endorsed sonographic risk stratification systems vary widely in their ability to reduce the number of unnecessary thyroid nodule FNAs. The ACR TIRADS outperformed the others, classifying more than half the biopsies as unnecessary with a FNR of 2.2%.

scholarly journals An assessment of the accuracy of contrast enema for the diagnosis of Hirschsprung disease at a South African tertiary hospital

2017 ◽  
Vol 21 (1) ◽  
Author(s):  
Monica S. Msomi ◽  
Hansraj Mangray ◽  
Vicci Du Plessis
Keyword(s):  
Diagnostic Accuracy ◽  
South African ◽  
False Negative ◽  
False Negative Rate ◽  
Hirschsprung Disease ◽  
Contrast Enema ◽  
Initial Screening ◽  
Tertiary Referral Hospital ◽  
Predictive Values ◽  
Picture Archiving And Communication

Objectives: To compare radiological findings with the histological diagnosis of Hirschsprung disease (HD) to establish the usefulness of contrast enema as an initial screening and diagnostic tool. To correlate accuracy of radiological diagnosis at Grey’s Hospital with international standards.Materials and methods: Systematic searches were conducted through the Picture Archiving and Communication System and the National Health Laboratory Service records for patients aged 0–12 years, with clinically suspected HD, for whom both contrast enemas and rectal biopsies were performed between 01 January 2011 and 31 August 2015 in a tertiary-level hospital. A total of 54 such patients were identified. Diagnostic accuracy levels were calculated by comparing radiological results with histology results, which is the gold standard.Results: Diagnostic accuracy of contrast enema was 78%, sensitivity was 94.4% and the negative predictive value was 95.7%. Specificity (68.8%) and positive predictive values (63%) were considerably lower. A lower false-negative rate of 5.6% was obtained at Grey’s Hospital as compared with the international reports of up to 30%.Conclusion: Contrast enema remains useful as an initial screening and diagnostic test for HD. Results of this South African tertiary referral hospital were consistent with the best international results for sensitivity of the contrast enema (approximately 80% – 88% in excluding the disease).

Secondary Complete Cytoreduction in Recurrent Ovarian Cancer: Benefit of Optimal Patient Selection Using Scoring System

2014 ◽  
Vol 24 (2) ◽  
pp. 238-246 ◽  
Author(s):  
Enora Laas ◽  
Mathieu Luyckx ◽  
Marjolein De Cuypere ◽  
Frederic Selle ◽  
Emile Daraï ◽  
...  
Keyword(s):  
Ovarian Cancer ◽  
Patient Selection ◽  
Positive Impact ◽  
False Negative ◽  
False Negative Rate ◽  
Recurrent Ovarian Cancer ◽  
Complete Resection ◽  
Predictive Values ◽  
Independent Population ◽  
The Impact

ObjectiveComplete tumor cytoreduction seems to be beneficial for patients with recurrent epithelial ovarian cancer (REOC). The challenge is to identify patients eligible for such surgery. Several scores based on simple clinical parameters have attempted to predict resectability and help in patient selection for surgery in REOC.The aims of this study were to assess the performance of these models in an independent population and to evaluate the impact of complete resection.Materials and MethodsA total of 194 patients with REOC between January 2000 and December 2010 were included in 2 French centers. Two scores were used: the AGO DESKTOP OVAR trial score and a score from Tian et al.The performance (sensitivity, specificity, and predictive values) of these scores was evaluated in our population. Survival curves were constructed to evaluate the survival impact of surgery on recurrence.ResultsPositive predictive values for complete resection were 80.6% and 74.0% for the DESKTOP trial score and the Tian score, respectively. The false-negative rate was high for both models (65.4% and 71.4%, respectively). We found a significantly higher survival in the patients with complete resection (59.4 vs 17.9 months,P< 0.01) even after adjustment for the confounding variables (hazard ratio [HR], 2.53; 95% confidence interval, 1.01–6.3;P= 0.04).ConclusionsIn REOC, surgery seems to have a positive impact on survival, if complete surgery can be achieved. However, factors predicting complete resection are not yet clearly defined. Recurrence-free interval and initial resection seem to be the most relevant factors. Laparoscopic evaluation could help to clarify the indications for surgery.

scholarly journals COVID-19 automatic diagnosis with CT images using the novel Transformer architecture

2021 ◽  
Author(s):  
Gabriel Sousa Silva Costa ◽  
Anselmo C. Paiva ◽  
Geraldo Braz Júnior ◽  
Marco Melo Ferreira
Keyword(s):  
Intelligent System ◽  
State Of The Art ◽  
False Negative ◽  
False Negative Rate ◽  
Ct Images ◽  
The Novel ◽  
Chain Reaction ◽  
High False Negative Rate ◽  
Polymerase Chain ◽  
Low Sensitivity

Even though vaccines are already in use worldwide, the COVID-19 pandemic is far from over, with some countries re-establishing the lockdown state, the virus has taken over 2 million lives until today, being a serious health issue. Although real-time reverse transcription-polymerase chain reaction (RTPCR) is the first tool for COVID-19 diagnosis, its high false-negative rate and low sensitivity might delay accurate diagnosis. Therefore, fast COVID-19 diagnosis and quarantine, combined with effective vaccination plans, is crucial for the pandemic to be over as soon as possible. To that end, we propose an intelligent system to classify computed tomography (CT) of lung images between a normal, pneumonia caused by something other than the coronavirus or pneumonia caused by the coronavirus. This paper aims to evaluate a complete selfattention mechanism with a Transformer network to capture COVID-19 pattern over CT images. This approach has reached the state-of-the-art in multiple NLP problems and just recently is being applied for computer vision tasks. We combine vision transformer and performer (linear attention transformers), and also a modified vision transformer, reaching 96.00% accuracy.

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