Lancet Microbe最新文献

{"title":"Rapid multiplex PCR panel for pneumonia in hospitalised patients with suspected pneumonia in the USA: a single-centre, open-label, pragmatic, randomised controlled trial.","authors":"Abinash Virk, Angel P Strasburg, Kami D Kies, Alexander D Donadio, Jay Mandrekar, William S Harmsen, Ryan W Stevens, Lynn L Estes, Aaron J Tande, Douglas W Challener, Douglas R Osmon, Madiha Fida, Paschalis Vergidis, Gina A Suh, John W Wilson, Nipunie S Rajapakse, Bijan J Borah, Ruchita Dholakia, Katelyn A Reed, Lisa M Hines, Audrey N Schuetz, Robin Patel","doi":"10.1016/S2666-5247(24)00170-8","DOIUrl":"https://doi.org/10.1016/S2666-5247(24)00170-8","url":null,"abstract":"<p><strong>Background: </strong>The clinical utility of rapid multiplex respiratory specimen PCR panels for pneumonia for patients with suspected pneumonia is undefined. We aimed to compare the effect of the BioFire FilmArray pneumonia panel (bioMérieux, Salt Lake City, UT, USA) with standard of care testing on antibiotic use in a real-world hospital setting.</p><p><strong>Methods: </strong>We conducted a single-centre, open-label, pragmatic, randomised controlled trial at the Mayo Clinic, Rochester, MN, USA. Hospitalised patients (aged ≥18 years) with suspected pneumonia, from whom expectorated or induced sputum, tracheal secretions, or bronchoalveolar lavage fluid respiratory culture samples (one per individual) could be collected during index hospitalisation, were eligible for inclusion. Samples from eligible participants were randomly assigned (1:1) with a computerised tool to undergo testing with either the BioFire FilmArray pneumonia panel, conventional culture, and antimicrobial susceptibility testing (intervention group) or conventional culture and antimicrobial susceptibility testing alone (control group). Antimicrobial stewardship review in both groups involved an assessment and recommendations for antibiotic modifications based on clinical data and the results from the BioFire FilmArray pneumonia panel, conventional culture, or both. The primary outcome was median time to first antibiotic modification (ie, escalation or de-escalation of antibiotics against Gram-negative and Gram-positive bacteria) within 96 h of randomisation, assessed with the Wilcoxon rank-sum test and analysed in a modified intention-to-treat population. This trial is registered with ClinicalTrials.gov (NCT05937126).</p><p><strong>Findings: </strong>Between Sept 15, 2020, and Sept 19, 2022, 1547 patients were screened for eligibility, of whom 1181 (76·3%) were randomly assigned: 582 (49·3%) to the intervention group and 599 (50·7%) to the control group. In total, 1152 participants were included in the modified intention-to-treat analysis, 589 (51·1%) in the control group and 563 (48·9%) in the intervention group. For the modified intention-to-treat population, median time to any first antibiotic modification was 20·4 h (95% CI 18·0-20·4) in the intervention group and 25·8 h (22·0-28·7) in the control group (p=0·076). Median time to any antibiotic escalation was 13·8 h (9·2-19·0) in the intervention group and 24·1 h (19·5-29·6) in the control group (p=0·0022). Median time to escalation of antibiotics against Gram-positive organisms was 10·3 h (6·2-30·9) in the intervention group and 24·6 h (19·5-37·2) in the control group (p=0·044); median time to escalation of antibiotics against Gram-negative organisms was 17·3 h (10·8-23·3) in the intervention group and 27·2 h (21·3-33·9) in the control group (p=0·010). Median time to any antibiotic de-escalation did not differ between groups (p=0·37). Median time to first de-escalation of antibiotics against Gram-positive organis","PeriodicalId":46633,"journal":{"name":"Lancet Microbe","volume":" ","pages":"100928"},"PeriodicalIF":20.9,"publicationDate":"2024-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142477430","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Viral concentrations in unpasteurised milk from avian influenza-infected cattle.","authors":"Amir Ghaemi","doi":"10.1016/j.lanmic.2024.101009","DOIUrl":"https://doi.org/10.1016/j.lanmic.2024.101009","url":null,"abstract":"","PeriodicalId":46633,"journal":{"name":"Lancet Microbe","volume":" ","pages":"101009"},"PeriodicalIF":20.9,"publicationDate":"2024-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142477432","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Intersection of artificial intelligence, microbes, and bone and joint infections: a new frontier for improving management outcomes.","authors":"Mohamed A Imam, Atef Abdelrahman, Adam Zumla, Rizwan Ahmed, Giovanni Satta, Alimuddin Zumla","doi":"10.1016/j.lanmic.2024.101008","DOIUrl":"https://doi.org/10.1016/j.lanmic.2024.101008","url":null,"abstract":"","PeriodicalId":46633,"journal":{"name":"Lancet Microbe","volume":" ","pages":"101008"},"PeriodicalIF":20.9,"publicationDate":"2024-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142477427","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Development of an all-in-one pan-sarbecovirus ferritin nanoparticle vaccine in humans.","authors":"Liuying Li, Hao Zhou","doi":"10.1016/j.lanmic.2024.100974","DOIUrl":"https://doi.org/10.1016/j.lanmic.2024.100974","url":null,"abstract":"","PeriodicalId":46633,"journal":{"name":"Lancet Microbe","volume":" ","pages":"100974"},"PeriodicalIF":20.9,"publicationDate":"2024-10-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142477423","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Genomic cluster formation among invasive group A streptococcal infections in the USA: a whole-genome sequencing and population-based surveillance study.","authors":"Yuan Li, Joy Rivers, Saundra Mathis, Zhongya Li, Sopio Chochua, Benjamin J Metcalf, Bernard Beall, Lesley McGee","doi":"10.1016/S2666-5247(24)00169-1","DOIUrl":"https://doi.org/10.1016/S2666-5247(24)00169-1","url":null,"abstract":"<p><strong>Background: </strong>Clusters of invasive group A streptococcal (iGAS) infection, linked to genomically closely related group A streptococcal (GAS) isolates (referred to as genomic clusters), pose public health threats, and are increasingly identified through whole-genome sequencing (WGS) analysis. In this study, we aimed to assess the risk of genomic cluster formation among iGAS cases not already part of existing genomic clusters.</p><p><strong>Methods: </strong>In this WGS and population-based surveillance study, we analysed iGAS case isolates from the Active Bacterial Core surveillance (ABCs), which is part of the US Centers for Disease Control and Prevention's Emerging Infections Program, in ten US states from Jan 1, 2015, to Dec 31, 2019. We included all residents in ABCs sites with iGAS infections meeting the case definition and excluded non-conforming GAS infections and cases with whole-genome assemblies of the isolate containing fewer than 1·5 million total bases or more than 150 contigs. For iGAS cases we collected basic demographics, underlying conditions, and risk factors for infection from medical records, and for isolates we included emm types, antimicrobial resistance, and presence of virulence-related genes. Two iGAS cases were defined as genomically clustered if their isolates differed by three or less single-nucleotide variants. An iGAS case not clustered with any previous cases at the time of detection, with a minimum trace-back time of 1 year, was defined as being at risk of cluster formation. We monitored each iGAS case at risk for a minimum of 1 year to identify any cluster formation event, defined as the detection of a subsequent iGAS case clustered with the case at risk. We used the Kaplan-Meier method to estimate the cumulative incidence of cluster formation events over time. We used Cox regression to assess associations between features of cases at risk upon detection and subsequent cluster formation. We developed a random survival forest machine-learning model based on a derivation cohort (random selection of 50% of cases at risk) to predict cluster formation risk. This model was validated using a validation cohort consisting of the remaining 50% of cases at risk.</p><p><strong>Findings: </strong>We identified 2764 iGAS cases at risk from 2016 to 2018, of which 656 (24%) formed genomic clusters by the end of 2019. Overall, the cumulative incidence of cluster formation was 0·057 (95% CI 0·048-0·066) at 30 days after detection, 0·12 (0·11-0·13) at 90 days after detection, and 0·16 (0·15-0·18) at 180 days after detection. A higher risk of cluster formation was associated with emm type (adjusted hazard ratio as compared with emm89 was 2·37 [95% CI 1·71-3·30] for emm1, 2·72 [1·82-4·06] for emm3, 2·28 [1·49-3·51] for emm6, 1·47 [1·05-2·06] for emm12, and 2·21 [1·38-3·56] for emm92), homelessness (1·42 [1·01-1·99]), injection drug use (2·08 [1·59-2·72]), residence in a long-term care facility (1·78 [1·29-2·45]), and ","PeriodicalId":46633,"journal":{"name":"Lancet Microbe","volume":" ","pages":"100927"},"PeriodicalIF":20.9,"publicationDate":"2024-10-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142477425","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Epidemiology of periportal fibrosis and relevance of current Schistosoma mansoni infection within the context of repeated mass drug administration in rural Uganda: a population-based, cross-sectional study.","authors":"Seun Anjorin, Betty Nabatte, Simon Mpooya, Benjamin Tinkitina, Christopher K Opio, Narcis B Kabatereine, Goylette F Chami","doi":"10.1016/j.lanmic.2024.07.007","DOIUrl":"https://doi.org/10.1016/j.lanmic.2024.07.007","url":null,"abstract":"<p><strong>Background: </strong>WHO guidelines for schistosomiasis-related morbidity control and elimination rely on current infection as a proxy indicator for morbidity. We evaluated these guidelines within the context of repeated mass drug administration and periportal fibrosis attributable to chronic intestinal schistosomiasis.</p><p><strong>Methods: </strong>We examined 1442 households randomly sampled from 38 villages in Buliisa, Pakwach, and Mayuge districts of Uganda within the SchistoTrack cohort. Periportal fibrosis was diagnosed in 2834 individuals aged 5-90 years using ultrasound and image patterns C-F from the Niamey protocol. Schistosoma mansoni status and intensity were diagnosed by Kato-Katz microscopy and point-of-care circulating cathodic antigen tests. Schistosome infection, co-infections, and comorbidities were examined as exposures for periportal fibrosis. Multivariable logistic regressions were run with SEs clustered by household.</p><p><strong>Findings: </strong>Between Jan 6 and Feb 3, 2022, 342 (12·1%) of 2834 participants were diagnosed with periportal fibrosis. By Kato-Katz microscopy, 1229 (43·4%) of 2834 participants were infected. 1863 (65·7%) of 2834 participants had trace positive point-of-care circulating cathodic antigen tests, which was higher than prevalence by Kato-Katz microscopy, and 1158 (40·9%) of 2834 participants had trace negative point-of-care circulating cathodic antigen tests. Individual schistosome status, intensity, and prevalence of heavy intensity infections of less than 1% and less than 5% were not correlated with periportal fibrosis likelihood or village prevalence. Periportal fibrosis likelihood linearly increased with age from age 5 years to age 25 years, non-linearly increased from age 26 years to age 45 years, attenuated or remained unchanged from age 46 years to age 60 years, and steadily decreased past 60 years of age. History of liver diseases, HIV, and ultrasound-detected chronic hepatitis or early cirrhosis-like disease were associated with more than two-times increased periportal fibrosis likelihood.</p><p><strong>Interpretation: </strong>WHO guidelines reliant on current schistosome status and intensity are uninformative for identifying probable cases or communities with periportal fibrosis. History of HIV and underlying chronic hepatitis or early cirrhosis-like disease are risk factors that could be investigated for periportal fibrosis surveillance and management.</p><p><strong>Funding: </strong>NDPH Pump Priming Fund, Wellcome Trust, John Fell Fund, Robertson Foundation, and UK Research and Innovation Engineering and Physical Sciences Research Council.</p>","PeriodicalId":46633,"journal":{"name":"Lancet Microbe","volume":" ","pages":"100944"},"PeriodicalIF":20.9,"publicationDate":"2024-10-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142477424","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Pandemic risk characterisation of zoonotic influenza A viruses using the Tool for Influenza Pandemic Risk Assessment (TIPRA).","authors":"Reina Yamaji, Wenqing Zhang, Akiko Kamata, Cornelia Adlhoch, David E Swayne, Dmitriy Pereyaslov, Dayan Wang, Gabriele Neumann, Gounalan Pavade, Ian G Barr, Malik Peiris, Richard J Webby, Ron A M Fouchier, Sophie Von Dobschütz, Thomas Fabrizio, Yuelong Shu, Magdi Samaan","doi":"10.1016/j.lanmic.2024.100973","DOIUrl":"https://doi.org/10.1016/j.lanmic.2024.100973","url":null,"abstract":"<p><p>A systematic risk assessment approach is essential for evaluating the relative risk of influenza A viruses (IAVs) with pandemic potential. To achieve this, the Tool for Influenza Pandemic Risk Assessment (TIPRA) was developed under the Global Influenza Programme of WHO. Since its release in 2016 and update in 2020, TIPRA has been used to assess the pandemic risk of 11 zoonotic IAVs across ten evaluation rounds. Notably, A(H7N9), A(H9N2), and A(H5) clade 2.3.4.4 viruses were re-evaluated owing to changes in epidemiological characteristics or virus properties. A(H7N9) viruses had the highest relative risk at the time of assessment, highlighting the importance of continuous monitoring and reassessment as changes in epidemiological trends within animal and human populations can alter risk profiles. The knowledge gaps identified throughout the ten risk assessments should help to guide the efficient use of resources for future research, including surveillance. The TIPRA tool reflects the One Health approach and has proven crucial for closely monitoring virus dynamics in both human and non-human populations to enhance preparedness for potential IAV pandemics.</p>","PeriodicalId":46633,"journal":{"name":"Lancet Microbe","volume":" ","pages":"100973"},"PeriodicalIF":20.9,"publicationDate":"2024-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142477429","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Wastewater monitoring of human and avian influenza A viruses in Northern Ireland: a genomic surveillance study.","authors":"Andrew J Lee, Stephen Carson, Marina I Reyne, Andrew Marshall, Daniel Moody, Danielle M Allen, Pearce Allingham, Ashley Levickas, Arthur Fitzgerald, Stephen H Bell, Jonathan Lock, Jonathon D Coey, Cormac McSparron, Behnam F Nejad, Evan P Troendle, David A Simpson, David G Courtney, Gisli G Einarsson, James P McKenna, Derek J Fairley, Tanya Curran, Jennifer M McKinley, Deirdre F Gilpin, Ken Lemon, John W McGrath, Connor G G Bamford","doi":"10.1016/S2666-5247(24)00175-7","DOIUrl":"https://doi.org/10.1016/S2666-5247(24)00175-7","url":null,"abstract":"<p><strong>Background: </strong>Influenza A viruses (IAVs) are significant pathogens of humans and other animals. Although endemic in humans and birds, novel IAV strains can emerge, jump species, and cause epidemics, like the latest variant of H5N1. Wastewater-based epidemiology (WBE) has been shown capable of detecting human IAVs. We aimed to assess whether whole-genome sequencing (WGS) of IAVs from wastewater is possible and can be used to discriminate between circulating strains of human and any non-human IAVs, such as those of avian origin.</p><p><strong>Methods: </strong>Using a pan-IAV RT-quantitative PCR assay, six wastewater treatment works (WWTWs) across Northern Ireland were screened from Aug 1 to Dec 5, 2022. A nanopore WGS approach was used to sequence RT-qPCR-positive samples. Phylogenetic analysis of sequences relative to currently circulating human and non-human IAVs was performed. For comparative purposes, clinical data (PCR test results) were supplied by The Regional Virus Laboratory, Belfast Health and Social Care Trust (Belfast, Northern Ireland, UK).</p><p><strong>Findings: </strong>We detected a dynamic IAV signal in wastewater from Sept 5, 2022, onwards across Northern Ireland, which did not show a clear positive relationship with the clinical data obtained for the region. Meta (mixed strain) whole-genome sequences were generated from wastewater samples displaying homology to only human and avian IAV strains. The relative proportion of IAV reads of human versus avian origin differed across time and sample site. A diversity in subtypes and lineages was detected (eg, H1N1, H3N2, and several avian). Avian segment 8 related to those found in recent H5N1 clade 2.3.4.4b was identified.</p><p><strong>Interpretation: </strong>WBE affords a means to monitor circulating human and avian IAV strains and provide crucial genetic information. As such, WBE can provide rapid, cost-effective, year-round One Health surveillance to help control IAV epidemic and pandemic-related threats. However, optimisation of WBE protocols are necessary to ensure observed wastewater signals not only correlate with clinical case data, but yield information on the wider environmental pan-influenz-ome.</p><p><strong>Funding: </strong>Department of Health for Northern Ireland.</p>","PeriodicalId":46633,"journal":{"name":"Lancet Microbe","volume":" ","pages":"100933"},"PeriodicalIF":20.9,"publicationDate":"2024-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142477433","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Implementing a national programme of pathogen genomics for public health: the Australian Pathogen Genomics Program (AusPathoGen).","authors":"Jessica R Webb, Patiyan Andersson, Eby Sim, Alireza Zahedi, Angela Donald, Tuyet Hoang, Anne E Watt, Jessica E Agius, Celeste M Donato, Max L Cummins, Tehzeeb Zulfiqar, Son Nghiem, Chantel Lin, Dimitrios Menouhos, Lex E X Leong, Rob Baird, Karina Kennedy, Louise Cooley, David Speers, Chuan Kok Lim, Joep de Ligt, Angeline Ferdinand, Katie Glass, Martyn D Kirk, Steven P Djordjevic, Clare Sloggett, Kristy Horan, Torsten Seemann, Vitali Sintchenko, Amy V Jennison, Benjamin P Howden","doi":"10.1016/j.lanmic.2024.100969","DOIUrl":"https://doi.org/10.1016/j.lanmic.2024.100969","url":null,"abstract":"<p><p>Delivering large-scale routine pathogen genomics surveillance for public health is of considerable interest, although translational research models that promote national-level implementation are not well defined. We describe the development and deployment of the Australian Pathogen Genomics Program (AusPathoGen), a comprehensive national partnership between academia, public health laboratories, and public health agencies that commenced in January, 2021. Successfully establishing and delivering a national programme requires inclusive and transparent collaboration between stakeholders, defined and clear focus on public health priorities, and support for strengthening national genomics capacity. Major enablers for delivering such a programme include technical solutions for data integration and analysis, such as the genomics surveillance platform AusTrakka, standard bioinformatic analysis methods, and national ethics and data sharing agreements that promote nationally integrated surveillance systems. Training of public health officials to interpret and act on genomic data is crucial, and evaluation and cost-effectiveness programmes will provide a benchmark and evidence for sustainable investment in genomics nationally and globally.</p>","PeriodicalId":46633,"journal":{"name":"Lancet Microbe","volume":" ","pages":"100969"},"PeriodicalIF":20.9,"publicationDate":"2024-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142401599","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Mpox genomics in outbreak control: challenges and limitations.","authors":"Kathryn Edenborough, Ammar Aziz, Nicola Sexton-Oates, Ivana Savic, Eike Steinig, Brendan Quinn, Mihaela Ivan, Alicia Arnott, Leon Caly, Chuan Kok Lim","doi":"10.1016/j.lanmic.2024.100999","DOIUrl":"https://doi.org/10.1016/j.lanmic.2024.100999","url":null,"abstract":"","PeriodicalId":46633,"journal":{"name":"Lancet Microbe","volume":" ","pages":"100999"},"PeriodicalIF":20.9,"publicationDate":"2024-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142401600","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}