scholarly journals Use of serology immunoassays for predicting SARS-CoV-2 infection: a serology-based diagnostic algorithm

2021 ◽  
Author(s):  
Alejandro Lazo-Langner ◽  
Benjamin Chin-Yee ◽  
Jaryd Tong ◽  
Lori Lowes ◽  
Benjamin D. Hedley ◽  
...  
Keyword(s):  
Validation Cohort ◽  
Diagnostic Algorithm ◽  
Roc Curves ◽  
Control Measures ◽  
Nucleic Acid Amplification ◽  
Diagnostic Strategy ◽  
Roc Curve Analysis ◽  
Potential Cost ◽  
Derivation Cohort ◽  
Infection Control Measures

Background. Detection of viral RNA by nucleic acid amplification testing (NAAT) remains the gold standard for diagnosis of SARS-CoV-2 infection but is limited by high cost and other factors. Whether serology-based assays can be effectively incorporated into a diagnostic algorithm remains to be determined. Herein we describe the development of a serology-based testing algorithm for SARS-CoV-2 infection. Patients and Methods. Between July 2020 and February 2021, we included symptomatic unvaccinated patients evaluated in the Emergency Department of our institution for suspected SARS-CoV-2. All patients had testing by real-time Reverse Transcription Polymerase Chain Reaction. The performance characteristics of five commercial enzymatic serology assays testing for different antibody isotypes were evaluated in a derivation cohort and the assay with the best performance was further tested on a validation cohort. Optimal cut-off points were determined using receiver operating characteristic (ROC) curves and further tested using logistic regression. Results. The derivation and validations cohorts included 72 and 319 patients, respectively. Based on its initial performance, the Elecsys Anti-SARS-CoV-2 assay (Roche Diagnostics) was further tested in the validation cohort. Using ROC curve analysis, we estimated the diagnostic performance for different cut-off points assuming a prevalence of positive tests of 5%. At any given cut-off point the NPV was over 97%. Discussion. This study suggests that an initial diagnostic strategy using the Elecsys Anti-SARS-CoV-2 serology test in symptomatic unvaccinated patients could help to rule out an acute SARS-CoV2 infection and potentially lead to appropriately tailored infection control measures or rational guidance for further testing with a potential cost reduction and increased availability

scholarly journals A novel severity score to predict inpatient mortality in COVID-19 patients

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
David J. Altschul ◽  
Santiago R. Unda ◽  
Joshua Benton ◽  
Rafael de la Garza Ramos ◽  
Phillip Cezayirli ◽  
...  
Keyword(s):  
Severity Score ◽  
Clinical Decision Making ◽  
Risk Model ◽  
Validation Cohort ◽  
Clinical Decision ◽  
International Normalized Ratio ◽  
Severe Illness ◽  
Roc Curve Analysis ◽  
Derivation Cohort ◽  
Mortality Incidence

Abstract COVID-19 is commonly mild and self-limiting, but in a considerable portion of patients the disease is severe and fatal. Determining which patients are at high risk of severe illness or mortality is essential for appropriate clinical decision making. We propose a novel severity score specifically for COVID-19 to help predict disease severity and mortality. 4711 patients with confirmed SARS-CoV-2 infection were included. We derived a risk model using the first half of the cohort (n = 2355 patients) by logistic regression and bootstrapping methods. The discriminative power of the risk model was assessed by calculating the area under the receiver operating characteristic curves (AUC). The severity score was validated in a second half of 2356 patients. Mortality incidence was 26.4% in the derivation cohort and 22.4% in the validation cohort. A COVID-19 severity score ranging from 0 to 10, consisting of age, oxygen saturation, mean arterial pressure, blood urea nitrogen, C-Reactive protein, and the international normalized ratio was developed. A ROC curve analysis was performed in the derivation cohort achieved an AUC of 0.824 (95% CI 0.814–0.851) and an AUC of 0.798 (95% CI 0.789–0.818) in the validation cohort. Furthermore, based on the risk categorization the probability of mortality was 11.8%, 39% and 78% for patient with low (0–3), moderate (4–6) and high (7–10) COVID-19 severity score. This developed and validated novel COVID-19 severity score will aid physicians in predicting mortality during surge periods.

A prospective validation cohort study of baseline plasma cell-free DNA (cfDNA) as a prognostic biomarker in newly diagnosed glioblastoma (GBM).

2020 ◽  
Vol 38 (15_suppl) ◽  
pp. 2508-2508
Author(s):  
Stephen Joseph Bagley ◽  
Seyed Ali Nabavizadeh ◽  
Jacob Till ◽  
Aseel Abdalla ◽  
Hareena Sanga ◽  
...  
Keyword(s):  
Cox Regression ◽  
Validation Cohort ◽  
Performance Status ◽  
Survival Outcomes ◽  
Prognostic Impact ◽  
Newly Diagnosed ◽  
Roc Curve Analysis ◽  
Optimal Cutoff ◽  
Derivation Cohort ◽  
Mutational Status

2508 Background: Due to significant interpatient heterogeneity, survival outcomes vary widely in patients with GBM. Novel prognostic biomarkers are needed. We aimed to determine the prognostic impact of baseline plasma cfDNA concentration in patients with GBM. Methods: We analyzed 84 patients with newly diagnosed GBM and at least 7 months of follow-up time. The first 41 patients comprised a previously published derivation cohort (Bagley, Clin Cancer Res 2020). The subsequent 43 patients served as an independent validation cohort. cfDNA was extracted from plasma collected prior to initial surgical resection and quantified by qPCR for a 115 bp amplicon of the human ALU repeat element. Receiver operating characteristic (ROC) curve analysis was used in the derivation cohort to (1) assess the accuracy of plasma cfDNA concentration for predicting progression-free survival status at 7 months (PFS-7), a landmark based on the median PFS for newly diagnosed GBM (Stupp, N Engl J Med 2005), and (2) derive the optimal cutoff for dichotomizing patients into high- and low-cfDNA groups. In the validation cohort, logistic regression was used to measure the association of plasma cfDNA concentration (high vs. low) with PFS-7, adjusted for age, isocitrate dehydrogenase ( IDH) 1/2 mutational status, 0-6-methylguanine-methyltransferase ( MGMT) methylation, extent of resection, and performance status. Multivariate Cox regression was used for overall survival (OS) analysis. Results: In the derivation cohort, the optimal cutoff for plasma cfDNA was 25.0 ng/mL (area under the curve [AUC] = 0.663), with inferior PFS and OS in patients with cfDNA above this cutoff (PFS, median 4.9 vs. 9.5 months, log-rank p = 0.001; OS, median 8.5 vs. 15.5 months, log-rank p = 0.03). In the validation cohort, baseline plasma cfDNA concentration over the cutoff was independently associated with a lower likelihood of being alive and progression-free at 7 months (adjusted OR 0.13, 95% CI 0.02 – 0.75, p = 0.02). OS was also worse in in the validation cohort in patients with high plasma cfDNA (adjusted HR 3.0, 95% CI 1.1 – 8.0, p = 0.03). Conclusions: In patients with newly diagnosed GBM, high baseline plasma cfDNA concentration is associated with worse survival outcomes independent of other prognostic factors. Further validation in a larger, multicenter study is warranted.

scholarly journals The novel proteomic signature for the detection of cardiac allograft vasculopathy

2021 ◽  
Vol 42 (Supplement_1) ◽  
Author(s):  
D M Wei ◽  
T Trenson ◽  
J M Van Keer ◽  
J Melgarejo ◽  
L Thijs ◽  
...  
Keyword(s):  
Heart Transplantation ◽  
Validation Cohort ◽  
Roc Curves ◽  
Cardiac Allograft Vasculopathy ◽  
Cardiac Allograft ◽  
Allograft Vasculopathy ◽  
Derivation Cohort ◽  
Net Reclassification Improvement ◽  
Noninvasive Biomarkers ◽  
Public Grant

Abstract Background Cardiac allograft vasculopathy (CAV) is the major long-term complications after heart transplantation, leading to mortality and re-transplantation. As available noninvasive biomarkers are scarce for CAV screening, we aimed to identify a proteomic signature for CAV detection. Methods Urinary proteome was measured by capillary electrophoresis coupled to mass spectrometry in 217 heart transplantation recipients. Participants were further randomly and evenly divided into the derivation cohort and validation cohort. The proteomic signature for CAV was identified by decision tree-based machine learning in the derivation cohort and further tested in the validation cohort. The pathway analysis was investigated with Reactome Pathway Database. Results We identified a proteomic signature with 27 urinary peptides, which yielded areas under the curve (AUC) of 0.83 and 0.71 in the derivation and validation cohort, respectively. In the validation cohort, it had a sensitivity of 68.4%, specificity of 73.2%, accuracy of 71.6%, negative predictive value of 81.3%. Including the proteomic signature into the basic model further improved the diagnostic accuracy with an relative integrated discrimination improvement of 25.9% and the continuous net reclassification improvement of 83.3% (p≤0.023). The pathways analysis on revealed that collagen turnover, platelet aggregation and coagulation, cell adhesion and motility might involve in the pathogenesis of CAV. Conclusions The proteomic signature might be valuable for the surveillance of CAV thereby reduce the frequency of invasive procedures after HTx. Moreover, the highlighted pathways might provide insights in the potential novel treatment targets for CAV. FUNDunding Acknowledgement Type of funding sources: Public grant(s) – EU funding. Main funding source(s): European Research Council Advanced Researcher Grant and Proof-of-Concept Grant ROC curves of the urinary proteomic The 25 highlighted enrichment pathways

scholarly journals Mycobacteriosis and Tuberculosis: Laboratory Diagnosis

2018 ◽  
Vol 12 (1) ◽  
pp. 41-58 ◽  
Author(s):  
Davood Azadi ◽  
Tahereh Motallebirad ◽  
Kazem Ghaffari ◽  
Hasan Shojaei
Keyword(s):  
Nucleic Acid ◽  
Case Reports ◽  
Diagnostic Algorithm ◽  
Laboratory Diagnosis ◽  
Etiologic Agent ◽  
Control Measures ◽  
Nucleic Acid Amplification ◽  
Nucleic Acid Hybridization ◽  
Original Research ◽  
Mycobacterial Infections

Background:Tuberculosis is one of the most important infectious diseases that has claimed its victims throughout much of known human history. With Koch's discovery of the tubercle bacillus as the etiologic agent of the disease, his sanitary and hygienic measures, which were based on his discovery and the development of a vaccine against tuberculosis by Albert Calmette and Camille Guérin in 1921, an attenuatedMycobacterium bovisstrain, bacilli Calmette-Guérin (BCG), and the discovery of the first antibiotic against tuberculosis, streptomycin by Selman Waksman in 1943, soon led to the opinion that appropriate control measures had become available for tuberculosis and it had been assumed that the disease could ultimately be eradicated.The emergence of resistant strains of this bacteria and widespread distribution of the disease in the world, and the emergence of the AIDS epidemic destroyed any possibility of global control of tuberculosis in the foreseeable future.Objectives:The purpose of this review is to highlight the current scientific literature on mycobacterial infections and provide an overview on the laboratory diagnosis of tuberculosis and non-tuberculosis infections based on conventional phenotypic and modern molecular assays.Method:In this study, a number of 65 papers comprising 20 reviews, 9 case reports, and 36 original research in association with mycobacteriosis and the laboratory diagnosis of mycobacterial infections, were reviewed.Results:Based on our analysis on the published documents methods applied for the laboratory diagnosis of tuberculosis are continually assessed and developed in order to achieve more rapid, less expensive, and accurate results. Acid-fast staining and culture for mycobacteria remain at the core of any diagnostic algorithm with the sensitivity of 20-70% and specificity of 95-98% for AFB microscopy and the sensitivity of 95% and the specificity of 98% for culture based diagnosis. Following growth in culture, molecular tests such as nucleic acid hybridization probes and DNA sequencing may be used for definitive species identification. Nucleic acid amplification methods provide the means for direct detection ofMycobacterium tuberculosisin respiratory specimens without the prerequisite to isolate or culture the organism, leading to more rapid diagnosis and better patient care.Conclusion:As the researchers in a developing country, we strongly believe that despite significant advances in laboratory capacity, in many countries reliable confirmation of suspected mycobacterial diseases is hindered by a lack of knowledge on proper standardized methods, sufficient funds, suitably trained staff and laboratory supplies.

scholarly journals A Diagnostic Algorithm Based on a Simple Clinical Prediction Rule for the Diagnosis of Cranial Giant Cell Arteritis

2021 ◽  
Vol 10 (6) ◽  
pp. 1163
Author(s):  
Michael Czihal ◽  
Christian Lottspeich ◽  
Christoph Bernau ◽  
Teresa Henke ◽  
Ilaria Prearo ◽  
...  
Keyword(s):  
Diagnostic Accuracy ◽  
Giant Cell Arteritis ◽  
Giant Cell ◽  
Validation Cohort ◽  
Prediction Rule ◽  
Diagnostic Algorithm ◽  
Clinical Prediction Rule ◽  
Ischemic Optic Neuropathy ◽  
Clinical Prediction ◽  
Derivation Cohort

Background: Risk stratification based on pre-test probability may improve the diagnostic accuracy of temporal artery high-resolution compression sonography (hrTCS) in the diagnostic workup of cranial giant cell arteritis (cGCA). Methods: A logistic regression model with candidate items was derived from a cohort of patients with suspected cGCA (n = 87). The diagnostic accuracy of the model was tested in the derivation cohort and in an independent validation cohort (n = 114) by receiver operator characteristics (ROC) analysis. The clinical items were composed of a clinical prediction rule, integrated into a stepwise diagnostic algorithm together with C-reactive protein (CRP) values and hrTCS values. Results: The model consisted of four clinical variables (age > 70, headache, jaw claudication, and anterior ischemic optic neuropathy). The diagnostic accuracy of the model for discrimination of patients with and without a final clinical diagnosis of cGCA was excellent in both cohorts (area under the curve (AUC) 0.96 and AUC 0.92, respectively). The diagnostic algorithm improved the positive predictive value of hrCTS substantially. Within the algorithm, 32.8% of patients (derivation cohort) and 49.1% (validation cohort) would not have been tested by hrTCS. None of these patients had a final diagnosis of cGCA. Conclusion: A diagnostic algorithm based on a clinical prediction rule improves the diagnostic accuracy of hrTCS.

scholarly journals A Novel Severity Score to Predict Inpatient Mortality in COVID-19 patients

2020 ◽  
Author(s):  
David Altschul ◽  
Santiago R Unda ◽  
Joshua Benton ◽  
Rafael de La Garza Ramos ◽  
Mark Mehler ◽  
...  
Keyword(s):  
Severity Score ◽  
Clinical Decision Making ◽  
Risk Model ◽  
Validation Cohort ◽  
Clinical Decision ◽  
International Normalized Ratio ◽  
Severe Illness ◽  
Roc Curve Analysis ◽  
Derivation Cohort ◽  
Mortality Incidence

Abstract IntroductionCOVID-19 is commonly mild and self-limiting, but in a considerable portion of patients the disease is severe and fatal. Determining which patients are at high risk of severe illness or mortality is essential for appropriate clinical decision making. We propose a novel severity score specifically for COVID-19 to help predict disease severity and mortality.Methods4,711 patients with confirmed SARS-CoV-2 infection were included. We derived a risk model using the first half of the cohort (n=2,355 patients) by logistic regression and bootstrapping methods. The discriminative power of the risk model was assessed by calculating the area under the receiver operating characteristic curves (AUC). The severity score was validated in a second half of 2,356 patients.ResultsMortality incidence was 26.4% in the derivation cohort and 22.4% in the validation cohort. A COVID-19 severity score ranging from 0 to 10, consisting of age, oxygen saturation, mean arterial pressure, blood urea nitrogen, C-Reactive protein, and the international normalized ratio was developed. A ROC curve analysis was performed in the derivation cohort achieved an AUC of 0.824 (95% CI 0.814-0.851) and an AUC of 0.798 (95% CI 0.789-0.818) in the validation cohort. Furthermore, based on the risk categorization the probability of mortality was 11.8%, 39% and 78% for patient with low (0-3), moderate (4-6) and high (7-10) COVID-19 severity score.ConclusionThis developed and validated novel COVID-19 severity score will aid physicians in predicting mortality during surge periods.

scholarly journals A Diagnostic Algorithm Based on a Simple Clinical Prediction Rule for the Diagnosis of Cranial Giant Cell Arteritis

2021 ◽  
Author(s):  
Michael Czihal ◽  
Christian Lottspeich ◽  
Christoph Bernau ◽  
Theresa Henke ◽  
Ilaria Prearo ◽  
...  
Keyword(s):  
Diagnostic Accuracy ◽  
Giant Cell ◽  
Validation Cohort ◽  
Prediction Rule ◽  
Diagnostic Algorithm ◽  
Clinical Prediction Rule ◽  
Temporal Artery ◽  
Ischemic Optic Neuropathy ◽  
Clinical Prediction ◽  
Derivation Cohort

Background: Risk tratification based on pre-test probability may improve the diagnostic accuracy of temporal artery high-resolution compression sonography (hrTCS) in the diagnostic workup of cranial giant cell arteriitis (cGCA). Methods: A logistic regression model with candidate items was derived from a cohort of patients with suspected cGCA (n = 87). The diagnostic accuracy of the model was tested in the derivation cohort and in an independent validation cohort (n = 114) by receiver operator characteristics (ROC)-analysis. The clinical items were composed to a clinical prediction rule, integrated into a stepwise diagnostic algorithm together with CRP-values and hrTCS-values. Results: The model consisted of 4 clinical variables (age > 70, headache, jaw claudication, anterior ischemic optic neuropathy). The diagnostic accuracy of the model for discrimination of patients with and without a final clinical diagnosis of cGCA was excellent in both cohorts (AUC 0.96 and AUC 0.92, respectively). The diagnostic algorithm improved the positive predictive value of hrCTS substantially. Within the algorithm, 32.8% of patients (derivation cohort) and 49.1% (validation cohort) would not have been tested by hrtCS. None of these patients had a final diagnosis of cGCA. Conclusion: A diagnostic algorithm based on a clinical prediction rule improves the diagnostic accuracy of hrTCS.

Coronavirus: Towards controlling of the pandemic - Indian scenario

2020 ◽  
Vol 11 (SPL1) ◽  
pp. 462-468
Author(s):  
Latika kothari ◽  
Sanskruti Wadatkar ◽  
Roshni Taori ◽  
Pavan Bajaj ◽  
Diksha Agrawal
Keyword(s):  
Control Measures ◽  
The Novel ◽  
Medical Treatments ◽  
Health Crisis ◽  
The Public ◽  
Infection Control Measures ◽  
The Social ◽  
Asking Questions ◽  
The Government ◽  
Novel Coronavirus

Coronavirus disease 2019 (COVID-19) is a communicable infection caused by the novel coronavirus resulting in severe acute respiratory syndrome coronavirus 2 (SARS-CoV). It was recognized to be a health crisis for the general population of international concern on 30th January 2020 and conceded as a pandemic on 11th March 2020. India is taking various measures to fight this invisible enemy by adopting different strategies and policies. To stop the COVID-19 from spreading, the Home Affairs Ministry and the health ministry, of India, has issued the nCoV 19 guidelines on travel. Screening for COVID-19 by asking questions about any symptoms, recent travel history, and exposure. India has been trying to get testing kits available. The government of India has enforced various laws like the social distancing, Janata curfew, strict lockdowns, screening door to door to control the spread of novel coronavirus. In this pandemic, innovative medical treatments are being explored, and a proper vaccine is being hunted to deal with the situation. Infection control measures are necessary to prevent the virus from further spreading and to help control the current situation. Thus, this review illustrates and explains the criteria provided by the government of India to the awareness of the public to prevent the spread of COVID-19.

Sign in / Sign up

Export Citation Format

Share Document