A metagenomic prospective cohort study on gut microbiome composition and clinical infection in small bowel transplantation.

Two-thirds of small-bowel transplantation (SBT) recipients develop bacteremia, with the majority of infections occurring within 3 months post-transplant. Sepsis-related mortality occurs in 31% of patients and is commonly caused by bacteria of gut origin, which are thought to translocate across the implanted organ. Serial post-transplant surveillance endoscopies provide an opportunity to study whether the composition of the ileal and colonic microbiota can predict the emergence as well as the pathogen of subsequent clinical infections in the SBT patient population. Five participants serially underwent aspiration of ileal and colonic bowel effluents at transplantation and during follow-up endoscopy either until death or for up to 3 months post-SBT. We performed whole-metagenome sequencing (WMS) of 40 bowel effluent samples and compared the results with clinical infection episodes. Microbiome composition was concordant between participants and timepoint-matched ileal and colonic samples. Four out of five (4/5) participants had clinically significant infections thought to be of gut origin. Bacterial translocation from the gut was observed in 3/5 patients with bacterial infectious etiologies. In all three cases, the pathogens had demonstrably colonized the gut between 1-10 days prior to invasive clinical infection. Recipients with better outcomes received donor grafts with higher alpha diversity. There was an increase in the number of antimicrobial resistance genes associated with longer hospital stay for all participants. This metagenomic study provides preliminary evidence to support the pathogen translocation hypothesis of gut-origin sepsis in the SBT cohort. Ileal and colonic microbiome compositions were concordant; therefore, fecal metagenomic analysis could be a useful surveillance tool for impeding infection with specific gut-residing pathogens.

Respiratory infectious burden in a cohort of antibody deficiency patients treated with immunoglobulin replacement therapy: The impact of lung pathology and gastroesophageal reflux disease.

Background: Antibody deficiencies result from reduced immunoglobulin levels and function, increasing susceptibility to, primarily, bacterial infection. Primary antibody deficiencies comprise intrinsic defects in B-cell physiology, often due to inherited errors. Hematological malignancies or B-cell suppressive therapy are major causes of secondary antibody deficiency. Although immunoglobulin replacement therapy (IGRT) reduces infectious burden in antibody deficiency patients, respiratory tract infections remain a significant health burden. We hypothesize that lung pathology and gastroesophageal reflux disease (GORD) increase the risk of pneumonia in antibody deficiency patients, as in the general population. Objective: For our cohort of patients with primary antibody deficiency and secondary antibody deficiency, we reviewed their respiratory infectious burden and the impact of lung pathologies and GORD. Methods: The medical records of 231 patients on IGRT at a tertiary referral center, from October 26, 2014, to February 19, 2021, were reviewed to determine microbial isolates from sputum samples and prevalence of common lung pathologies and GORD. Results: Haemophilus and Pseudomonas species represent a large infectious burden, being identified in 30.2% and 21.4% of sputum samples demonstrating growth, respectively; filamentous fungal and mycobacterial infections were rare. Diagnosed lung pathology increased the proportion of patients with Pseudomonas, Klebsiella, Stenotrophomonas, and Candida species isolated in their sputum, and diagnosed GORD increased the proportion with Enterobacter and Candida species isolated. Conclusions: Bacterial respiratory infectious burden remains in primary antibody deficiency and secondary antibody deficiency despite IGRT. Lung pathologies encourage growth of species less susceptible to IGRT, so specialist respiratory medicine input and additional treatments such as inhaled antibiotics are indicated to optimize respiratory outcomes.

A pipeline to further enhance quality, integrity and reusability of the NCCID clinical data.

The National COVID-19 Chest Imaging Database (NCCID) is a centralized UK database of thoracic imaging and corresponding clinical data. It is made available by the National Health Service Artificial Intelligence (NHS AI) Lab to support the development of machine learning tools focused on Coronavirus Disease 2019 (COVID-19). A bespoke cleaning pipeline for NCCID, developed by the NHSx, was introduced in 2021. We present an extension to the original cleaning pipeline for the clinical data of the database. It has been adjusted to correct additional systematic inconsistencies in the raw data such as patient sex, oxygen levels and date values. The most important changes will be discussed in this paper, whilst the code and further explanations are made publicly available on GitLab. The suggested cleaning will allow global users to work with more consistent data for the development of machine learning tools without being an expert. In addition, it highlights some of the challenges when working with clinical multi-center data and includes recommendations for similar future initiatives.

Feasibility of using intermittent active monitoring of vital signs by smartphone users to predict SARS-CoV-2 PCR positivity.

Early detection of highly infectious respiratory diseases, such as COVID-19, can help curb their transmission. Consequently, there is demand for easy-to-use population-based screening tools, such as mobile health applications. Here, we describe a proof-of-concept development of a machine learning classifier for the prediction of a symptomatic respiratory disease, such as COVID-19, using smartphone-collected vital sign measurements. The Fenland App study followed 2199 UK participants that provided measurements of blood oxygen saturation, body temperature, and resting heart rate. Total of 77 positive and 6339 negative SARS-CoV-2 PCR tests were recorded. An optimal classifier to identify these positive cases was selected using an automated hyperparameter optimisation. The optimised model achieved an ROC AUC of 0.695 ± 0.045. The data collection window for determining each participant's vital sign baseline was increased from 4 to 8 or 12 weeks with no significant difference in model performance (F(2) = 0.80, p = 0.472). We demonstrate that 4 weeks of intermittently collected vital sign measurements could be used to predict SARS-CoV-2 PCR positivity, with applicability to other diseases causing similar vital sign changes. This is the first example of an accessible, smartphone-based remote monitoring tool deployable in a public health setting to screen for potential infections.

Clinical features and management of individuals admitted to hospital with monkeypox and associated complications across the UK: a retrospective cohort study.

BACKGROUND: The scale of the 2022 global mpox (formerly known as monkeypox) outbreak has been unprecedented. In less than 6 months, non-endemic countries have reported more than 67 000 cases of a disease that had previously been rare outside of Africa. Mortality has been reported as rare but hospital admission has been relatively common. We aimed to describe the clinical and laboratory characteristics and outcomes of individuals admitted to hospital with mpox and associated complications, including tecovirimat recipients. METHODS: In this cohort study, we undertook retrospective review of electronic clinical records and pathology data for all individuals admitted between May 6, and Aug 3, 2022, to 16 hospitals from the Specialist and High Consequence Infectious Diseases Network for Monkeypox. The hospitals were located in ten cities in England and Northern Ireland. Inclusion criteria were clinical signs consistent with mpox and MPXV DNA detected from at least one clinical sample by PCR testing. Patients admitted solely for isolation purposes were excluded from the study. Key outcomes included admission indication, complications (including pain, secondary infection, and mortality) and use of antibiotic and anti-viral treatments. Routine biochemistry, haematology, microbiology, and virology data were also collected. Outcomes were assessed in all patients with available data. FINDINGS: 156 individuals were admitted to hospital with complicated mpox during the study period. 153 (98%) were male and three (2%) were female, with a median age of 35 years (IQR 30-44). Gender data were collected from electronic patient records, which encompassed full formal review of clincian notes. The prespecified options for data collection for gender were male, female, trans, non-binary, or unknown. 105 (71%) of 148 participants with available ethnicity data were of White ethnicity and 47 (30%) of 155 were living with HIV with a median CD4 count of 510 cells per mm3 (IQR 349-828). Rectal or perianal pain (including proctitis) was the most common indication for hospital admission (44 [28%] of 156). Severe pain was reported in 89 (57%) of 156, and secondary bacterial infection in 82 (58%) of 142 individuals with available data. Median admission duration was 5 days (IQR 2-9). Ten individuals required surgery and two cases of encephalitis were reported. 38 (24%) of the 156 individuals received tecovirimat with early cessation in four cases (two owing to hepatic transaminitis, one to rapid treatment response, and one to patient choice). No deaths occurred during the study period. INTERPRETATION: Although life-threatening mpox appears rare in hospitalised populations during the current outbreak, severe mpox and associated complications can occur in immunocompetent individuals. Analgesia and management of superimposed bacterial infection are priorities for patients admitted to hospital. FUNDING: None.

Point of care SARS-CoV-2 nucleic acid testing in schools improves school attendance.

Background: National lockdowns have led to significant interruption to children's education globally. In the Autumn term in 2020, school absence in England and Wales was almost five times higher than the same period in 2019. Transmission of SARS-CoV-2 in schools and ongoing interruption to education remains a concern. However, evaluation of rapid point of care (POC) polymerase chain reaction (PCR) testing in British schools has not been undertaken. Methods: This is a survey of secondary schools in England that implemented PCR-based rapid POC testing. The study aims to measure the prevalence of SARS-CoV-2 infection in schools, to assess the impact of this testing on school attendance and closures, and to describe schools experiences with testing. All schools utilised the SAMBA II SARS-CoV-2 testing platform. Results: 12 fee-paying secondary schools in England were included. Between September 1 st 2020 and December 16 th 2020, 697 on site rapid POC PCR tests were performed and 6.7% of these were positive for SARS-CoV-2 infection. There were five outbreaks in three schools during this time which were contained. Seven groups of close contacts within the school known as bubbles had to quarantine but there were no school closures. 84% of those tested were absent from school for less than one day whilst awaiting their test result. This potentially saved between 1047 and 1570 days off school in those testing negative compared to the NHS PCR laboratory test. Schools reported a positive impact of having a rapid testing platform as it allowed them to function as fully as possible during this pandemic. Conclusions: Rapid POC PCR testing platforms should be widely available and utilised in school settings. Reliable positive tests will prevent outbreaks and uncontrolled spread of infection within school settings. Reliable negative test results will reassure students, parents and staff and prevent disruption to education.

Immunodeficiency, autoimmunity, and increased risk of B cell malignancy in humans with TRAF3 mutations.

Tumor necrosis factor receptor-associated factor 3 (TRAF3) is a central regulator of immunity. TRAF3 is often somatically mutated in B cell malignancies, but its role in human immunity is not defined. Here, in five unrelated families, we describe an immune dysregulation syndrome of recurrent bacterial infections, autoimmunity, systemic inflammation, B cell lymphoproliferation, and hypergammaglobulinemia. Affected individuals each had monoallelic mutations in TRAF3 that reduced TRAF3 expression. Immunophenotyping showed that patients' B cells were dysregulated, exhibiting increased nuclear factor-κB 2 activation, elevated mitochondrial respiration, and heightened inflammatory responses. Patients had mild CD4+ T cell lymphopenia, with a reduced proportion of naïve T cells but increased regulatory T cells and circulating T follicular helper cells. Guided by this clinical phenotype, targeted analyses demonstrated that common genetic variants, which also reduce TRAF3 expression, are associated with an increased risk of B cell malignancies, systemic lupus erythematosus, higher immunoglobulin levels, and bacterial infections in the wider population. Reduced TRAF3 conveys disease risks by driving B cell hyperactivity via intrinsic activation of multiple intracellular proinflammatory pathways and increased mitochondrial respiration, with a likely contribution from dysregulated T cell help. Thus, we define monogenic TRAF3 haploinsufficiency syndrome and demonstrate how common TRAF3 variants affect a range of human diseases.

The development, validation and application of remote blood sample collection in telehealth programmes.

INTRODUCTION: The ability to collect blood samples remotely without the involvement of healthcare professionals is a key element of future telehealth applications. We developed and validated the application of the Drawbridge OneDraw device for use at home for blood sample collection. The device was then applied in a large population-based remote monitoring study to assess changes in SARS-CoV-2 IgG antibody levels. METHODS: We tested: (1) feasibility of participants using the device at home without a healthcare professional on the upper arm and thigh sites (2) stability of the dried blood sample collected remotely (3) participant acceptability of the device compared with finger-prick and venous blood samples and the validity of SARS-CoV-2 virus antibody measurement versus venous blood sample (4) application to the Fenland COVID-19 study in which 4023 participants at 3 timepoints across 6 months. RESULTS: Participant acceptability was high, with a significantly lower median perceived pain score and 76% of participants preferring the OneDraw device over the other blood collection methods. There was high level of agreement in SARS-CoV-2 virus antibody results with venous blood samples in 120 participants (Cohen's kappa 0.68 (95% CI 0.56, 0.83). In the Fenland COVID-19 study, 92% of participants returned a sample at baseline (3702/4023), 89% at 3 months (3492/3918) and 93% at 6 months (3453/3731), with almost all samples received successfully processed (99.9%). DISCUSSION: The OneDraw device enables a standardised blood sample collection at home by participants themselves. Due to its ease-of-use and acceptability the OneDraw device is particularly useful in telehealth approaches where multiple samples need to be collected.

A2B-COVID: A Tool for Rapidly Evaluating Potential SARS-CoV-2 Transmission Events.

Identifying linked cases of infection is a critical component of the public health response to viral infectious diseases. In a clinical context, there is a need to make rapid assessments of whether cases of infection have arrived independently onto a ward, or are potentially linked via direct transmission. Viral genome sequence data are of great value in making these assessments, but are often not the only form of data available. Here, we describe A2B-COVID, a method for the rapid identification of potentially linked cases of COVID-19 infection designed for clinical settings. Our method combines knowledge about infection dynamics, data describing the movements of individuals, and evolutionary analysis of genome sequences to assess whether data collected from cases of infection are consistent or inconsistent with linkage via direct transmission. A retrospective analysis of data from two wards at Cambridge University Hospitals NHS Foundation Trust during the first wave of the pandemic showed qualitatively different patterns of linkage between cases on designated COVID-19 and non-COVID-19 wards. The subsequent real-time application of our method to data from the second epidemic wave highlights its value for monitoring cases of infection in a clinical context.

ESCMID rapid guidelines for assessment and management of long COVID.

SCOPE: The aim of these guidelines is to provide evidence-based recommendations for the assessment and management of individuals with persistent symptoms after acute COVID-19 infection and to provide a definition for this entity, termed 'long COVID'. METHODS: We performed a search of the literature on studies addressing epidemiology, symptoms, assessment, and treatment of long COVID. The recommendations were grouped by these headings and by organ systems for assessment and treatment. An expert opinion definition of long COVID is provided. Symptoms were reviewed by a search of the available literature. For assessment recommendations, we aimed to perform a diagnostic meta-analysis, but no studies provided relevant results. For treatment recommendations we performed a systematic review of the literature in accordance with the PRISMA statement. We aimed to evaluate patient-related outcomes, including quality of life, return to baseline physical activity, and return to work. Quality assessment of studies included in the systematic review is provided according to study design. RECOMMENDATIONS: Evidence was insufficient to provide any recommendation other than conditional guidance. The panel recommends considering routine blood tests, chest imaging, and pulmonary functions tests for patients with persistent respiratory symptoms at 3 months. Other tests should be performed mainly to exclude other conditions according to symptoms. For management, no evidence-based recommendations could be provided. Physical and respiratory rehabilitation should be considered. On the basis of limited evidence, the panel suggests designing high-quality prospective clinical studies/trials, including a control group, to further evaluate the assessment and management of individuals with persistent symptoms of COVID-19.

The Removal of Airborne Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) and Other Microbial Bioaerosols by Air Filtration on Coronavirus Disease 2019 (COVID-19) Surge Units.

Airborne severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) was detected in a coronavirus disease 19 (COVID-19) ward before activation of HEPA-air filtration but not during filter operation; SARS-CoV-2 was again detected following filter deactivation. Airborne SARS-CoV-2 was infrequently detected in a COVID-19 intensive care unit. Bioaerosol was also effectively filtered.

Development and validation of a dynamic 48-hour in-hospital mortality risk stratification for COVID-19 in a UK teaching hospital: a retrospective cohort study.

OBJECTIVES: To develop a disease stratification model for COVID-19 that updates according to changes in a patient's condition while in hospital to facilitate patient management and resource allocation. DESIGN: In this retrospective cohort study, we adopted a landmarking approach to dynamic prediction of all-cause in-hospital mortality over the next 48 hours. We accounted for informative predictor missingness and selected predictors using penalised regression. SETTING: All data used in this study were obtained from a single UK teaching hospital. PARTICIPANTS: We developed the model using 473 consecutive patients with COVID-19 presenting to a UK hospital between 1 March 2020 and 12 September 2020; and temporally validated using data on 1119 patients presenting between 13 September 2020 and 17 March 2021. PRIMARY AND SECONDARY OUTCOME MEASURES: The primary outcome is all-cause in-hospital mortality within 48 hours of the prediction time. We accounted for the competing risks of discharge from hospital alive and transfer to a tertiary intensive care unit for extracorporeal membrane oxygenation. RESULTS: Our final model includes age, Clinical Frailty Scale score, heart rate, respiratory rate, oxygen saturation/fractional inspired oxygen ratio, white cell count, presence of acidosis (pH <7.35) and interleukin-6. Internal validation achieved an area under the receiver operating characteristic (AUROC) of 0.90 (95% CI 0.87 to 0.93) and temporal validation gave an AUROC of 0.86 (95% CI 0.83 to 0.88). CONCLUSIONS: Our model incorporates both static risk factors (eg, age) and evolving clinical and laboratory data, to provide a dynamic risk prediction model that adapts to both sudden and gradual changes in an individual patient's clinical condition. On successful external validation, the model has the potential to be a powerful clinical risk assessment tool. TRIAL REGISTRATION: The study is registered as 'researchregistry5464' on the Research Registry (www.researchregistry.com).

Influenza: epidemiology and hospital management.

Influenza is a cause of significant morbidity, mortality, economic and social disruption. Annual seasonal influenza epidemics result in 290,000-650,000 deaths worldwide, while influenza pandemics have resulted in many more - the A(H1N1) pandemic of 1918-1919 caused 20-50 million deaths. Healthcare systems struggle to effectively manage the constant threat because of the evolving nature of the virus. Since the start of 2021, there have been four events of concern related to influenza reported by the World Health Organization. To reduce the burden of disease and protect our global health security, it is essential that clinicians effectively identify and manage cases of influenza, as well as understand and collaborate with the wider public and global health systems. In particular, the rapid identification and management of novel influenza strains of concern is critical. The COVID-19 pandemic has instigated improvements in influenza preparedness guidelines and management protocols. It has accelerated healthcare innovation, with novel tools to manage respiratory disease more effectively. Innovative technologies, new pharmaceuticals and improved global surveillance are changing the way healthcare systems respond to influenza and other diseases to ensure global health resilience and effective management of future outbreaks.

Superspreaders drive the largest outbreaks of hospital onset COVID-19 infections.

SARS-CoV-2 is notable both for its rapid spread, and for the heterogeneity of its patterns of transmission, with multiple published incidences of superspreading behaviour. Here, we applied a novel network reconstruction algorithm to infer patterns of viral transmission occurring between patients and health care workers (HCWs) in the largest clusters of COVID-19 infection identified during the first wave of the epidemic at Cambridge University Hospitals NHS Foundation Trust, UK. Based upon dates of individuals reporting symptoms, recorded individual locations, and viral genome sequence data, we show an uneven pattern of transmission between individuals, with patients being much more likely to be infected by other patients than by HCWs. Further, the data were consistent with a pattern of superspreading, whereby 21% of individuals caused 80% of transmission events. Our study provides a detailed retrospective analysis of nosocomial SARS-CoV-2 transmission, and sheds light on the need for intensive and pervasive infection control procedures.

The COVID-19 pandemic, caused by the SARS-CoV-2 virus, presents a global public health challenge. Hospitals have been at the forefront of this battle, treating large numbers of sick patients over several waves of infection. Finding ways to manage the spread of the virus in hospitals is key to protecting vulnerable patients and workers, while keeping hospitals running, but to generate effective infection control, researchers must understand how SARS-CoV-2 spreads. A range of factors make studying the transmission of SARS-CoV-2 in hospitals tricky. For instance, some people do not present any symptoms, and, amongst those who do, it can be difficult to determine whether they caught the virus in the hospital or somewhere else. However, comparing the genetic information of the SARS-CoV-2 virus from different people in a hospital could allow scientists to understand how it spreads. Samples of the genetic material of SARS-CoV-2 can be obtained by swabbing infected individuals. If the genetic sequences of two samples are very different, it is unlikely that the individuals who provided the samples transmitted the virus to one another. Illingworth, Hamilton et al. used this information, along with other data about how SARS-CoV-2 is transmitted, to develop an algorithm that can determine how the virus spreads from person to person in different hospital wards. To build their algorithm, Illingworth, Hamilton et al. collected SARS-CoV-2 genetic data from patients and staff in a hospital, and combined it with information about how SARS-CoV-2 spreads and how these people moved in the hospital . The algorithm showed that, for the most part, patients were infected by other patients (20 out of 22 cases), while staff were infected equally by patients and staff. By further probing these data, Illingworth, Hamilton et al. revealed that 80% of hospital-acquired infections were caused by a group of just 21% of individuals in the study, identifying a 'superspreader' pattern. These findings may help to inform SARS-CoV-2 infection control measures to reduce spread within hospitals, and could potentially be used to improve infection control in other contexts.

Multidrug-resistant tuberculosis imported into low-incidence countries-a GeoSentinel analysis, 2008-2020.

BACKGROUND: Early detection of imported multidrug-resistant tuberculosis (MDR-TB) is crucial, but knowledge gaps remain about migration- and travel-associated MDR-TB epidemiology. The aim was to describe epidemiologic characteristics among international travellers and migrants with MDR-TB. METHODS: Clinician-determined and microbiologically confirmed MDR-TB diagnoses deemed to be related to travel or migration were extracted from GeoSentinel, a global surveillance network of travel and tropical medicine clinics, from January 2008 through December 2020. MDR-TB was defined as resistance to both isoniazid and rifampicin. Additional resistance to either a fluoroquinolone or a second-line injectable drug was categorized as pre-extensively drug-resistant (pre-XDR) TB, and as extensively drug-resistant (XDR) TB when resistance was detected for both. Sub-analyses were performed based on degree of resistance and country of origin. RESULTS: Of 201 patients, 136 had MDR-TB (67.7%), 25 had XDR-TB (12.4%), 23 had pre-XDR TB (11.4%) and 17 had unspecified MDR- or XDR-TB (8.5%); 196 (97.5%) were immigrants, of which 92 (45.8%) originated from the former Soviet Union. The median interval from arrival to presentation was 154 days (interquartile range [IQR]: 10-751 days); 34.3% of patients presented within 1 month after immigration, 30.9% between 1 and 12 months and 34.9% after ≥1 year. Pre-XDR- and XDR-TB patients from the former Soviet Union other than Georgia presented earlier than those with MDR-TB (26 days [IQR: 8-522] vs. 369 days [IQR: 84-827]), while patients from Georgia presented very early, irrespective of the level of resistance (8 days [IQR: 2-18] vs. 2 days [IQR: 1-17]). CONCLUSIONS: MDR-TB is uncommon in traditional travellers. Purposeful medical migration may partly explain differences in time to presentation among different groups. Public health resources are needed to better understand factors contributing to cross-border MDR-TB spread and to develop strategies to optimize care of TB-infected patients in their home countries before migration.