Systematic comparison of published host gene expression signatures for bacterial/viral discrimination.

BACKGROUND: Measuring host gene expression is a promising diagnostic strategy to discriminate bacterial and viral infections. Multiple signatures of varying size, complexity, and target populations have been described. However, there is little information to indicate how the performance of various published signatures compare to one another. METHODS: This systematic comparison of host gene expression signatures evaluated the performance of 28 signatures, validating them in 4589 subjects from 51 publicly available datasets. Thirteen COVID-specific datasets with 1416 subjects were included in a separate analysis. Individual signature performance was evaluated using the area under the receiving operating characteristic curve (AUC) value. Overall signature performance was evaluated using median AUCs and accuracies. RESULTS: Signature performance varied widely, with median AUCs ranging from 0.55 to 0.96 for bacterial classification and 0.69-0.97 for viral classification. Signature size varied (1-398 genes), with smaller signatures generally performing more poorly (P < 0.04). Viral infection was easier to diagnose than bacterial infection (84% vs. 79% overall accuracy, respectively; P < .001). Host gene expression classifiers performed more poorly in some pediatric populations (3 months-1 year and 2-11 years) compared to the adult population for both bacterial infection (73% and 70% vs. 82%, respectively; P < .001) and viral infection (80% and 79% vs. 88%, respectively; P < .001). We did not observe classification differences based on illness severity as defined by ICU admission for bacterial or viral infections. The median AUC across all signatures for COVID-19 classification was 0.80 compared to 0.83 for viral classification in the same datasets. CONCLUSIONS: In this systematic comparison of 28 host gene expression signatures, we observed differences based on a signature's size and characteristics of the validation population, including age and infection type. However, populations used for signature discovery did not impact performance, underscoring the redundancy among many of these signatures. Furthermore, differential performance in specific populations may only be observable through this type of large-scale validation.

Tocilizumab for patients with COVID-19 pneumonia. The single-arm TOCIVID-19 prospective trial.

BACKGROUND: Tocilizumab blocks pro-inflammatory activity of interleukin-6 (IL-6), involved in pathogenesis of pneumonia the most frequent cause of death in COVID-19 patients. METHODS: A multicenter, single-arm, hypothesis-driven trial was planned, according to a phase 2 design, to study the effect of tocilizumab on lethality rates at 14 and 30 days (co-primary endpoints, a priori expected rates being 20 and 35%, respectively). A further prospective cohort of patients, consecutively enrolled after the first cohort was accomplished, was used as a secondary validation dataset. The two cohorts were evaluated jointly in an exploratory multivariable logistic regression model to assess prognostic variables on survival. RESULTS: In the primary intention-to-treat (ITT) phase 2 population, 180/301 (59.8%) subjects received tocilizumab, and 67 deaths were observed overall. Lethality rates were equal to 18.4% (97.5% CI: 13.6-24.0, P = 0.52) and 22.4% (97.5% CI: 17.2-28.3, P < 0.001) at 14 and 30 days, respectively. Lethality rates were lower in the validation dataset, that included 920 patients. No signal of specific drug toxicity was reported. In the exploratory multivariable logistic regression analysis, older age and lower PaO2/FiO2 ratio negatively affected survival, while the concurrent use of steroids was associated with greater survival. A statistically significant interaction was found between tocilizumab and respiratory support, suggesting that tocilizumab might be more effective in patients not requiring mechanical respiratory support at baseline. CONCLUSIONS: Tocilizumab reduced lethality rate at 30 days compared with null hypothesis, without significant toxicity. Possibly, this effect could be limited to patients not requiring mechanical respiratory support at baseline. Registration EudraCT (2020-001110-38); clinicaltrials.gov (NCT04317092).

The Production of Standardized Samples with Known Concentrations for Severe Acute Respiratory Syndrome Coronavirus 2 RT-qPCR Testing Validation for Developing Countries in the Period of the Pandemic Era.

BACKGROUND: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has caused a pandemic of pneumonia spreading around the world, leading to serious threats to public health and attracting enormous attention. There is an urgent need for sensitive diagnostic testing implementation to control and manage SARS-CoV-2 in public health laboratories. The quantitative reverse transcription PCR (RT-qPCR) assay is the gold standard method, but the sensitivity and specificity of SARS-CoV-2 testing are dependent on a number of factors. METHODS: We synthesized RNA based on the genes published to estimate the concentration of inactivated virus samples in a biosafety level 3 laboratory. The limit of detection (LOD), linearity, accuracy, and precision were evaluated according to the bioanalytical method validation guidelines. RESULTS: We found that the LOD reached around 3 copies/reaction. Furthermore, intra-assay precision, accuracy, and linearity met the accepted criterion with an RSD for copies of less than 25%, and linear regression met the accepted R 2 of 0.98. CONCLUSIONS: We suggest that synthesized RNA based on the database of the NCBI gene bank for estimating the concentration of inactivated virus samples provides a potential opportunity for reliable testing to diagnose coronavirus disease 2019 (COVID-19) as well as limit the spread of the disease. This method may be relatively quick and inexpensive, and it may be useful for developing countries during the pandemic era. In the long term, it is also applicable for evaluation, verification, validation, and external quality assessment.

Validation Checklist for Massive Vaccination Centers.

Abstract: Starting from the minimum requirements indicated by Lombardy Region, a validation checklist has been developed by experts in design, healthcare layout planning, hygiene and public health, planning and compliance, in order to provide managers of COVID-19 massive vaccination centers with a useful and easy-to-use tool to ensure quality, safety and efficiency of the different activities performed.

Actives from MMV Open Access Boxes? A suggested way forward.

It is estimated that more than 1 billion people across the world are affected by a neglected tropical disease (NTD) that requires medical intervention. These diseases tend to afflict people in areas with high rates of poverty and cost economies billions of dollars every year. Collaborative drug discovery efforts are required to reduce the burden of these diseases in endemic regions. The release of "Open Access Boxes" is an initiative launched by Medicines for Malaria Venture (MMV) in collaboration with its partners to catalyze new drug discovery in neglected diseases. These boxes are mainly requested by biology researchers across the globe who may not otherwise have access to compounds to screen nor knowledge of the workflow that needs to be followed after identification of actives from their screening campaigns. Here, we present guidelines on how to move such actives beyond the hit identification stage, to help in capacity strengthening and enable a greater impact of the initiative.

Antibody (Serology) Tests for COVID-19: a Case Study.

Serology (antibody) tests to detect previous SARS-CoV-2 infection have been in high demand from the beginning of the COVID-19 pandemic. The initial shortage of diagnostic tests coupled with asymptomatic infections led to a significant demand for serology tests to identify past infections. Despite serious limitations on the interpretation of a positive antibody test in terms of immunity to SARS-CoV-2, antibody testing was initially considered for release from social distancing, return to employment, and "immunity passports." The regulatory approach to antibody tests was limited; manufacturers were encouraged to develop and market antibody tests without submitting validation data to the FDA. FDA guidance grew more stringent, but many poor-quality tests were already on the market-potentially inappropriately used for individual decision-making. This is a case study describing COVID-19 serology tests and the U.S. market and describes lessons learned for a future health security crisis.

Comparing Methods for Record Linkage for Public Health Action: Matching Algorithm Validation Study.

BACKGROUND: Many public health departments use record linkage between surveillance data and external data sources to inform public health interventions. However, little guidance is available to inform these activities, and many health departments rely on deterministic algorithms that may miss many true matches. In the context of public health action, these missed matches lead to missed opportunities to deliver interventions and may exacerbate existing health inequities. OBJECTIVE: This study aimed to compare the performance of record linkage algorithms commonly used in public health practice. METHODS: We compared five deterministic (exact, Stenger, Ocampo 1, Ocampo 2, and Bosh) and two probabilistic record linkage algorithms (fastLink and beta record linkage [BRL]) using simulations and a real-world scenario. We simulated pairs of datasets with varying numbers of errors per record and the number of matching records between the two datasets (ie, overlap). We matched the datasets using each algorithm and calculated their recall (ie, sensitivity, the proportion of true matches identified by the algorithm) and precision (ie, positive predictive value, the proportion of matches identified by the algorithm that were true matches). We estimated the average computation time by performing a match with each algorithm 20 times while varying the size of the datasets being matched. In a real-world scenario, HIV and sexually transmitted disease surveillance data from King County, Washington, were matched to identify people living with HIV who had a syphilis diagnosis in 2017. We calculated the recall and precision of each algorithm compared with a composite standard based on the agreement in matching decisions across all the algorithms and manual review. RESULTS: In simulations, BRL and fastLink maintained a high recall at nearly all data quality levels, while being comparable with deterministic algorithms in terms of precision. Deterministic algorithms typically failed to identify matches in scenarios with low data quality. All the deterministic algorithms had a shorter average computation time than the probabilistic algorithms. BRL had the slowest overall computation time (14 min when both datasets contained 2000 records). In the real-world scenario, BRL had the lowest trade-off between recall (309/309, 100.0%) and precision (309/312, 99.0%). CONCLUSIONS: Probabilistic record linkage algorithms maximize the number of true matches identified, reducing gaps in the coverage of interventions and maximizing the reach of public health action.

Specificity testing by point prevalence as a simple assessment strategy using the Roche Elecsys® anti-SARS-CoV-2 immunoassay.

BACKGROUND: The detection of antibodies to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is mandatory for the diagnosis, retrospective assessment of disease progression, and correct evaluation of the current infection situation in the population. Many such assays have been launched by various manufacturers. Unfortunately, the new US Food and Drug Administration emergency use regulations have resulted in a situation where laboratories have to perform their own validation studies but many of these laboratories do not have the biobank needed to conduct the studies. METHODS: We introduce a method that allows institutions to quickly perform a verification study in a low-prevalence infection situation. As proof of concept, we used the Roche Elecsys® anti-SARS-CoV-2 electrochemiluminescence immunoassay and an SAP-based hospital information system. The Shenzhen YHLO Biotech IgM and IgG assay targeting other surface patterns was used as a confirmatory test. RESULTS: The Roche assay demonstrated a limit of detection of 0.069 cutoff index and successfully passed the performance validation according to Clinical and Laboratory Standards Institute EP15-A3. The study population of 627 inpatients has a median age of 64 years, and approximately 13% of the group were under intensive care at the respective time point. All patients included tested negative for SARS-CoV-2 infection by quantitative reverse transcription polymerase chain reaction (cobas® 6800, Roche, Mannheim, Germany). Only one false-positive result was obtained, resulting in a specificity for the Roche Elecsys anti-SARS-CoV-2 test of 99.84% and a negative predictive value of 99.98%. CONCLUSIONS: The anonymized use of residual material enables quick evaluation of anti-SARS-CoV-2 immunoassays, as shown in this work with the Roche Elecsys assay. Comparison of the control population with economic data makes it possible to validate the sampling set and therefore to determine diagnostic specificity. By use of the approach chosen, it was shown that the Roche test achieved very good results in terms of diagnostic specificity, reproducibility, and limit of detection.

Research protocol for the validation of a new portable technology for real-time continuous monitoring of Early Warning Score (EWS) in hospital practice and for an early-stage multistakeholder assessment.

INTRODUCTION: The real-time continuous monitoring of vital parameters in patients affected by multiple chronic conditions and/or COVID-19 can lead to several benefits to the Italian National Healthcare System (IT-NHS). The UBiquitous Integrated CARE (UBICARE) technology is a novel health digital platform at the validation stage in hospital setting. UBICARE might support the urgent need for digitalisation and early intervention, as well as minimise the face-to-face delivery of care in both hospital and community-based care settings. This research protocol aims to design an early-stage assessment of the multidimensional impact induced by UBICARE within the IT-NHS alongside technology validation in a hospital ward. METHODS AND ANALYSIS: The targeted patients will be medium/high-risk hypertensive individuals as an illustrative first example of how UBICARE might bring benefits to susceptible patients. A mixed-method study will be applied to incorporate to the validation study a multistakeholder perspective, including perceived patient experiences and preferences, and facilitate technology adoption. First, semistructured interviews will be undertaken with a variety of stakeholders including clinicians, health managers and policy-makers to capture views on the likely technology utility, economic sustainability, impact of adoption in hospital practice and alternative adoption scenarios. Second, a monocentric, non-randomised and non-comparative clinical study, supplemented by the administration of standardised usability questionnaires to patients and health professionals, will validate the use of UBICARE in hospital practice. Finally, the results of the previous stages will be discussed in a multidisciplinary-facilitated workshop with IT-NHS relevant stakeholders to reconcile stakeholders' perspectives. Limitations include a non-random recruitment strategy in the clinical study, small sample size of the key stakeholders and potential stakeholder recruitment bias introduced by the research technique. ETHICS AND DISSEMINATION: The Ethics Committee for Clinical Experimentation of Tuscany Region approved the protocol. Participation in this study is voluntary. Study results will be disseminated through peer-reviewed publications and academic conferences.