Routine Metagenomics Service for ICU Patients with Respiratory Infection.

Rationale: Respiratory metagenomics (RMg) needs evaluation in a pilot service setting to determine utility and inform implementation into routine clinical practice. Objectives: Feasibility, performance, and clinical impacts on antimicrobial prescribing and infection control were recorded during a pilot RMg service. Methods: RMg was performed on 128 samples from 87 patients with suspected lower respiratory tract infection (LRTI) on two general and one specialist respiratory ICUs at Guy's and St Thomas' NHS Foundation Trust, London. Measurements and Main Results: During the first 15 weeks, RMg provided same-day results for 110 samples (86%), with a median turnaround time of 6.7 hours (interquartile range = 6.1-7.5 h). RMg was 93% sensitive and 81% specific for clinically relevant pathogens compared with routine testing. Forty-eight percent of RMg results informed antimicrobial prescribing changes (22% escalation; 26% deescalation) with escalation based on speciation in 20 out of 24 cases and detection of acquired-resistance genes in 4 out of 24 cases. Fastidious or unexpected organisms were reported in 21 samples, including anaerobes (n = 12), Mycobacterium tuberculosis, Tropheryma whipplei, cytomegalovirus, and Legionella pneumophila ST1326, which was subsequently isolated from the bedside water outlet. Application to consecutive severe community-acquired LRTI cases identified Staphylococcus aureus (two with SCCmec and three with luk F/S virulence determinants), Streptococcus pyogenes (emm1-M1uk clone), S. dysgalactiae subspecies equisimilis (STG62647A), and Aspergillus fumigatus with multiple treatments and public health impacts. Conclusions: This pilot study illustrates the potential of RMg testing to provide benefits for antimicrobial treatment, infection control, and public health when provided in a real-world critical care setting. Multicenter studies are now required to inform future translation into routine service.

Real-Time Whole Genome Sequencing to Guide Patient-Tailored Therapy of Severe Acute Respiratory Syndrome Coronavirus 2 Infection.

The management of coronavirus disease 2019 has become more complex due to the expansion of available therapies. The presence of severe acute respiratory syndrome coronavirus 2 variants and mutations further complicates treatment due to their differing susceptibilities to therapies. Here we outline the use of real-time whole genome sequencing to detect persistent infection, evaluate for mutations confering resistance to treatments, and guide treatment decisions.

Risk prediction models for colorectal cancer in people with symptoms: a systematic review.

BACKGROUND: Colorectal cancer (CRC) is the fourth leading cause of cancer-related death in Europe and the United States. Detecting the disease at an early stage improves outcomes. Risk prediction models which combine multiple risk factors and symptoms have the potential to improve timely diagnosis. The aim of this review is to systematically identify and compare the performance of models that predict the risk of primary CRC among symptomatic individuals. METHODS: We searched Medline and EMBASE to identify primary research studies reporting, validating or assessing the impact of models. For inclusion, models needed to assess a combination of risk factors that included symptoms, present data on model performance, and be applicable to the general population. Screening of studies for inclusion and data extraction were completed independently by at least two researchers. RESULTS: Twelve thousand eight hundred eight papers were identified from the literature search and three through citation searching. 18 papers describing 15 risk models were included. Nine were developed in primary care populations and six in secondary care. Four had good discrimination (AUROC > 0.8) in external validation studies, and sensitivity and specificity ranged from 0.25 and 0.99 to 0.99 and 0.46 depending on the cut-off chosen. CONCLUSIONS: Models with good discrimination have been developed in both primary and secondary care populations. Most contain variables that are easily obtainable in a single consultation, but further research is needed to assess clinical utility before they are incorporated into practice.

A Multinational Case Series Describing Successful Treatment of Persistent Severe Acute Respiratory Syndrome Coronavirus 2 Infection Caused by Omicron Sublineages With Prolonged Courses of Nirmatrelvir/Ritonavir.

The optimum treatment for persistent infection with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is not known. Our case series, across 5 hospitals in 3 countries, describes 11 cases where persistent SARS-CoV-2 infection was successfully treated with prolonged courses (median, 10 days [range, 10-18 days]) of nirmatrelvir/ritonavir (Paxlovid). Most cases (9/11) had hematological malignancy and 10 (10/11) had received CD20-depleting therapy. The median duration of infection was 103 days (interquartile range, 85-138 days). The majority (10/11) were hospitalized, and 7 (7/11) had severe/critical disease. All survived and 9 of 11 demonstrated viral clearance, almost half (4/9) of whom received nirmatrelvir/ritonavir as monotherapy. This case series suggests that prolonged nirmatrelvir/ritonavir has a role in treating persistent infection.

Feasibility and clinical utility of local rapid Nanopore influenza A virus whole genome sequencing for integrated outbreak management, genotypic resistance detection and timely surveillance.

Rapid respiratory viral whole genome sequencing (WGS) in a clinical setting can inform real-time outbreak and patient treatment decisions, but the feasibility and clinical utility of influenza A virus (IAV) WGS using Nanopore technology has not been demonstrated. A 24 h turnaround Nanopore IAV WGS protocol was performed on 128 reverse transcriptase PCR IAV-positive nasopharyngeal samples taken over seven weeks of the 2022-2023 winter influenza season, including 25 from patients with nosocomial IAV infections and 102 from patients attending the Emergency Department. WGS results were reviewed collectively alongside clinical details for interpretation and reported to clinical teams. All eight segments of the IAV genome were recovered for 97/128 samples (75.8 %) and the haemagglutinin gene for 117/128 samples (91.4 %). Infection prevention and control identified nosocomial IAV infections in 19 patients across five wards. IAV WGS revealed two separate clusters on one ward and excluded transmission across different wards with contemporaneous outbreaks. IAV WGS also identified neuraminidase inhibitor resistance in a persistently infected patient and excluded avian influenza in a sample taken from an immunosuppressed patient with a history of travel to Singapore which had failed PCR subtyping. Accurate IAV genomes can be generated in 24 h using a Nanopore protocol accessible to any laboratory with SARS-CoV-2 Nanopore sequencing capacity. In addition to replicating reference laboratory surveillance results, IAV WGS can identify antiviral resistance and exclude avian influenza. IAV WGS also informs management of nosocomial outbreaks, though molecular and clinical epidemiology were concordant in this study, limiting the impact on decision-making.

The ongoing Streptococcus pyogenes (Group A Streptococcus) outbreak in London, United Kingdom, in December 2022: a molecular epidemiology study.

OBJECTIVES: Epidemiological and whole-genome sequencing analysis of an ongoing outbreak of Streptococcus pyogenes (Group A Streptococcus) in London (United Kingdom). METHODS: Prospective identification of Group A Streptococcus cases from a diagnostic laboratory serving central and south London between 27 November and 10 December 2022. Case notes were reviewed and isolates were retrieved. Case numbers were compared with the previous 5 years. Whole-genome sequencing was performed with long-read, nanopore technology for emm typing and identification of superantigen genes. Associations of pathogen-related factors with an invasive disease were assessed by single-variable and multi-variable logistic regression. RESULTS: Case numbers began increasing in October 2022 from a baseline of 2.0 cases per day, and in December 2022, the average daily case numbers reached 10.8 cases per day, four-fold the number usually seen in winter. A total of 113 cases were identified during the prospective study period. Three quarters (86/113, 76%) were paediatric cases, including 2 deaths. Of 113 cases, 11 (10%) were invasive. In total, 56 isolates were successfully sequenced, including 10 of 11 (91%) invasive isolates. The emm12 (33/56, 59%) and emm1 (9/56, 16%) types were predominant, with 7 of 9 (78%) emm1 isolates being from the M1uk clone. The majority of invasive isolates had superantigen genes spea (7/10, 70%) and spej (8/10, 80%), whereas, in non-invasive isolates, these superantigen genes were found less frequently (spea: 5/46, 11% and spej: 7/46, 15%). By multivariable analysis of pathogen-related factors, spea (OR 8.9, CI 1.4-57, p 0.020) and spej (OR 12, CI 1.8-78, p 0.011) were associated with invasive disease. CONCLUSIONS: emm12 and emm1 types predominate in the ongoing outbreak, which mainly affects children. In this outbreak, the spea and spej superantigen genes are associated with the severity of presentation.

Evaluating the potential for respiratory metagenomics to improve treatment of secondary infection and detection of nosocomial transmission on expanded COVID-19 intensive care units.

BACKGROUND: Clinical metagenomics (CMg) has the potential to be translated from a research tool into routine service to improve antimicrobial treatment and infection control decisions. The SARS-CoV-2 pandemic provides added impetus to realise these benefits, given the increased risk of secondary infection and nosocomial transmission of multi-drug-resistant (MDR) pathogens linked with the expansion of critical care capacity. METHODS: CMg using nanopore sequencing was evaluated in a proof-of-concept study on 43 respiratory samples from 34 intubated patients across seven intensive care units (ICUs) over a 9-week period during the first COVID-19 pandemic wave. RESULTS: An 8-h CMg workflow was 92% sensitive (95% CI, 75-99%) and 82% specific (95% CI, 57-96%) for bacterial identification based on culture-positive and culture-negative samples, respectively. CMg sequencing reported the presence or absence of ß-lactam-resistant genes carried by Enterobacterales that would modify the initial guideline-recommended antibiotics in every case. CMg was also 100% concordant with quantitative PCR for detecting Aspergillus fumigatus from 4 positive and 39 negative samples. Molecular typing using 24-h sequencing data identified an MDR-K. pneumoniae ST307 outbreak involving 4 patients and an MDR-C. striatum outbreak involving 14 patients across three ICUs. CONCLUSION: CMg testing provides accurate pathogen detection and antibiotic resistance prediction in a same-day laboratory workflow, with assembled genomes available the next day for genomic surveillance. The provision of this technology in a service setting could fundamentally change the multi-disciplinary team approach to managing ICU infections. The potential to improve the initial targeted treatment and rapidly detect unsuspected outbreaks of MDR-pathogens justifies further expedited clinical assessment of CMg.