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The study compares an artificial intelligence technology with traditional manual search of literature databases to assess the accuracy and efficiency of retrieving relevant articles for post-market surveillance of in vitro diagnostic and medical devices under the Medical Device Regulation and In Vitro Diagnostic Medical Device Regulation. Over a 3-year period, literature searches and technical assessment searches were performed manually or using the Huma.AI platform to retrieve relevant articles related to the safety and performance of selected in vitro diagnostic and medical devices. The manual search involved refined keyword searches, screening of titles/abstracts / full text, and extraction of relevant information. The Huma.AI search utilized advanced caching techniques and a natural language processing system to identify relevant reports. Searches were conducted on PubMed and PubMed Central. The number of identified relevant reports, precision rates, and time requirements for each approach were analyzed. The Huma.AI system outperformed the manual search in terms of the number of identified relevant articles in almost all cases. The average precision rates per year were significantly higher and more consistent with the Huma.AI search compared with the manual search. The Huma.AI system also took significantly less time to perform the searches and analyze the outputs than the manual search. The study demonstrated that the Huma.AI platform was more effective and efficient in identifying relevant articles compared with the manual approach., Competing Interests: Declaration of competing interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Joanna Reniewicz, Vinay Suryaprakash, Justyna Kowalczyk, Anna Blacha, and Davide Manissero are QIAGEN employees. Greg Kostello, Haiming Tan, Yan Wang, and Patrick Reineke are Huma.AI employees. All the work reported in this manuscript was funded by QIAGEN. No other conflicts of interest to declare., (Copyright © 2023 The Authors. Published by Elsevier B.V. All rights reserved.)

Objective: The speed at which Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) is mutating has made it necessary to frequently assess how these genomic changes impact the performance of diagnostic real-time polymerase chain reaction (RT-PCR) assays. Herein, we describe a generic three-step workflow to assess the effect of genomic mutations on inclusivity and sensitivity of RT-PCR assays., Methods: Sequences collected from the Global Initiative on Sharing All Influenza Data (GISAID) were mapped to a SARS-CoV-2 reference genome to evaluate the position and prevalence of mismatches in the oligonucleotide-binding sites of the QIAstat-Dx, an RT-PCR panel designed to detect SARS-CoV-2. The frequency of mutations and their impact on melting temperature were assessed, and sequences flagged by risk-based criteria were examined in vitro., Results: Out of 8,900,393 SARS-CoV-2 genome sequences analyzed, only 173 (0.0019%) genomes contained potentially critical mutations for the QIAstat-Dx; follow-up in-vitro testing confirmed no impact on the assays' performance., Conclusions: The current study demonstrates that SARS-CoV-2 genetic variants do not affect the performance of the QIAstat-Dx device. It is recommended that manufacturers incorporate this workflow into obligatory post-marketing surveillance activities, as this approach could potentially enhance genetic monitoring of their product., Competing Interests: I have read the journal’s policy and the authors of this manuscript have the following competing interests: All authors were QIAGEN employees at the time of writing this manuscript., (Copyright: © 2024 Kosińska-Selbi et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Background: The ability to proactively predict the epidemiological dynamics of infectious diseases such as coronavirus disease 2019 (COVID-19) would facilitate efficient public health responses and may help guide patient management. Viral loads of infected people correlate with infectiousness and, therefore, could be used to predict future case rates., Aim: In this systematic review, we determine whether there is a correlation between severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) real-time reverse-transcription polymerase chain reaction (RT-PCR) cycle threshold (Ct) values (a proxy for viral load) and epidemiological trends in patients diagnosed with COVID-19, and whether Ct values are predictive of future cases., Methods: A PubMed search was conducted on August 22 2022, based on a search strategy of studies reporting correlations between SARS-CoV-2 Ct values and epidemiological trends., Results: Data from 16 studies were relevant for inclusion. RT-PCR Ct values were measured from national (n = 3), local (n = 7), single-unit (n = 5), or closed single-unit (n = 1) samples. All studies retrospectively examined the correlation between Ct values and epidemiological trends, and seven evaluated their prediction model prospectively. Five studies used the temporal reproduction number (R t ) as the measure of the population/epidemic growth rate. Eight studies reported a prediction time in the negative cross-correlation between Ct values and new daily cases, with seven reporting a prediction time of ~1-3 weeks, and one reporting 33 days., Conclusion: Ct values are negatively correlated with epidemiological trends and may be useful in predicting subsequent peaks in variant waves of COVID-19 and other circulating pathogens., (© 2023. The Author(s).)

Recent reports from the World Health Organization regarding Influenza A cases of zoonotic origin in humans (H1v and H9N2) and publications describing emergence swine Influenza A cases in humans together with "G4" Eurasian avian-like H1N1 Influenza A virus have drawn global attention to Influenza A pandemic threat. Additionally, the current COVID-19 epidemic has stressed the importance of surveillance and preparedness to prevent potential outbreaks. One feature of the QIAstat-Dx Respiratory SARS-CoV-2 panel is the double target approach for Influenza A detection of seasonal strains affecting humans using a generic Influenza A assay plus the three specific human subtype assays. This work explores the potential use of this double target approach in the QIAstat-Dx Respiratory SARS-Co-V-2 Panel as a tool to detect zoonotic Influenza A strains. A set of recently recorded H9 and H1 spillover strains and the G4 EA Influenza A strains as example of recent zoonotic Flu A strains were subjected to detection prediction with QIAstat-Dx Respiratory SARS-CoV-2 Panel using commercial synthetic dsDNA sequences. In addition, a large set of available commercial human and non-human influenza A strains were also tested using QIAstat-Dx Respiratory SARS-CoV-2 Panel for a better understanding of detection and discrimination of Influenza A strains. Results show that QIAstat-Dx Respiratory SARS-CoV-2 Panel generic Influenza A assay detects all the recently recorded H9, H5 and H1 zoonotic spillover strains and all the G4 EA Influenza A strains. Additionally, these strains yielded negative results for the three-human seasonal IAV (H1, H3 and H1N1 pandemic) assays. Additional non-human strains corroborated those results of Flu A detection with no subtype discrimination, whereas human Influenza strains were positively discriminated. These results indicate that QIAstat-Dx Respiratory SARS-CoV-2 Panel could be a useful tool to diagnose zoonotic Influenza A strains and differentiate them from the seasonal strains commonly affecting humans., (© 2023. The Author(s).)

To estimate the costs and benefits of screening for latent tuberculosis infection (LTBI) in a migrant population in Malaysia. An economic model was developed from a Malaysian healthcare perspective to compare QuantiFERON-TB Gold Plus (QuantiFERON) with the tuberculin skin test (TST). A decision tree was used to capture outcomes relating to LTBI screening followed by a Markov model that simulated the lifetime costs and benefits of the patient cohort. The Markov model did not capture the impact of secondary infections. The model included an R shiny interactive interface to allow adaptation to other scenarios and settings. QuantiFERON is both more effective and less costly than TST (dominant). Compared with QuantiFERON, the lifetime risk of developing active TB increases by approximately 40% for TST due to missed LTBI cases during screening (i.e. a higher number of false negative cases for TST). For a migrant population in Malaysia, QuantiFERON is cost-effective when compared with TST. Further research should consider targeted LTBI screening for migrants in Malaysia based on common risk factors., (© 2023. The Author(s).)

Background: The World Health Organisation (WHO) recommends that testing and treatment for latent tuberculosis infection (LTBI) should be undertaken in high-risk groups using either interferon gamma release assays (IGRAs) or a tuberculin skin test (TST). As IGRAs are more expensive than TST, an assessment of the cost-effectiveness of IGRAs can guide decision makers on the most appropriate choice of test for different high-risk populations. This current review aimed to provide the most up to date evidence on the cost-effectiveness evidence on LTBI testing in high-risk groups-specifically evidence reporting the costs per QALY of different testing strategies., Methods: A comprehensive search of databases including MEDLINE, EMBASE and NHS-EED was undertaken from 2011 up to March 2021. Studies were screened and extracted by two independent reviewers. The study quality was assessed using the Bias in Economic Evaluation Checklist (ECOBIAS). A narrative synthesis of the included studies was undertaken., Results: Thirty-two studies reported in thirty-three documents were included in this review. Quality of included studies was generally high, although there was a weakness across all studies referencing sources correctly and/or justifying choices of parameter values chosen or assumptions where parameter values were not available. Inclusions of IGRAs in testing strategies was consistently found across studies to be cost-effective but this result was sensitive to underlying LTBI prevalence rates., Conclusion: While some concerns remain about uncertainty in parameter values used across included studies, the evidence base since 2010 has grown with modelling approaches addressing the weakness pointed out in previous reviews but still reaching the same conclusion that IGRAs are likely to be cost-effective in high-income countries for high-risk populations. Evidence is also required on the cost-effectiveness of different strategies in low to middle income countries and countries with high TB burden., (© 2022. The Author(s).)