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Summary Background Novel skin-based tests for tuberculosis infection might present suitable alternatives to current tests; however, diagnostic performance of new tests compared with the purified protein derivative-tuberculin skin test (TST) or interferon-γ release assays (IGRA) needs systematic assessment. Methods In this systematic review and meta-analysis, we searched English (Medline OVID), Chinese (Chinese Biomedical Literature Database and the China National Knowledge Infrastructure), and Russian (e-library) databases from the inception of each database to May 15, 2019, (with updated search of the Russian and English databases on Oct, 20 2020) using terms “ESAT6” OR “CFP10” AND “skin test” AND “Tuberculosis” OR “C-Tb” OR “Diaskintest”. We included studies reporting on the performance of index tests alone or compared with a comparator. Inclusion criteria varied according to review objectives and performance outcome, but reporting of test cut-offs for positivity applied to study population was required from all studies. We used a hierarchy of reference standards for tuberculosis infection consistent with the 2020 WHO framework to evaluate diagnostic performance. Two authors independently reviewed the titles and abstracts for English and Chinese (LF and MK) and Russian studies (MK and VN). Study quality was assessed with QUADAS-2. Pooled random-effects estimates are presented when appropriate for total agreement proportion, sensitivity in microbiologically confirmed tuberculosis and specificity in cohorts with low risk of tuberculosis infection. This study is registered with PROSPERO, CRD42019135572. Findings We identified 1466 original articles, of which 37 (2·5%) studies, including 10 915 individuals (7111 Diaskintest, 2744 C-Tb, 887 EC, 173 DPPD), were included in the qualitative analysis (29 [78%] studies of Diaskintest, five [15%] studies of C-Tb, two [5%] studies of EC-skintest, and one [3%] study of DPPD). 22 (1·5%) studies including 5810 individuals (3143 Diaskintest, 2129 C-Tb, 538 EC-skintest) were included in the quantitative analysis: 15 (68%) of Diaskintest, five (23%) of C-Tb, and two (9%) of EC-skintest. Tested sub-populations included individuals with HIV, children (0–18 years), and individuals exposed to tuberculosis. Studies were heterogeneous with moderate to high risk of bias. Nine head-to-head studies of index test versus TST and IGRA permitted direct comparisons and pooling. In a mixed cohort of people with and without tuberculosis, Diaskintest pooled agreement with IGRA was 87·16% (95% CI 79·47–92·24) and 55·45% (46·08–64·45) with TST-5 mm cut-off (TST5 mm). Diaskintest sensitivity was 91·18% (95% CI 81·72–95·98) compared with 88·24% (78·20–94·01) for TST5 mm, 89·66 (78·83–95·28) for IGRA QuantiFERON, and 90·91% (79·95–96·16) for TSPOT.TB. C-Tb agreement with IGRA in individuals with active tuberculosis was 79·80% (95% CI 76·10–83·07) compared with 78·92% (74·65–82·63) for TST5 mm/15 mm cut-off (TST5 mm/15 mm). TST5/15mm reflects threshold in cohorts that applied stratified cutoffs: 5 mm for HIV-infected, immunocompromised, or BCG-naive individuals, and 15mm for BCG-vaccinated immunocompetent individuals. C-Tb sensitivity was 74·52% (95% CI 70·39–78·25) compared with a sensitivity of 78·18% (67·75–85·94) for TST5 mm/15 mm, and 71·67% (63·44–78·68) for IGRA. Specificity was 97·85% (95% CI 93·96–99·25) for C-Tb versus 93·31% (90·22–95·48) for TST 15 mm cut-off and 99·15% (79·66–99·97) for IGRA. EC-skintest sensitivity was 86·06% (95% CI 82·39–89·07). Interpretation Novel skin-based tests for tuberculosis infection appear to perform similarly to IGRA or TST; however, study quality varied. Evaluation of test performance, patient-important outcomes, and diagnostic use in current clinical algorithms will inform implementation in key populations. Funding StopTB (New Diagnostics Working Group) and FIND. Translations For the Chinese and Russian translations of the abstract see Supplementary Materials section.

Purpose To prospectively validate two risk scores to predict mortality (4C Mortality) and in-hospital deterioration (4C Deterioration) among adults hospitalised with COVID-19. Methods Prospective observational cohort study of adults (age ≥18 years) with confirmed or highly suspected COVID-19 recruited into the International Severe Acute Respiratory and emerging Infections Consortium (ISARIC) WHO Clinical Characterisation Protocol UK (CCP-UK) study in 306 hospitals across England, Scotland and Wales. Patients were recruited between 27 August 2020 and 17 February 2021, with at least 4 weeks follow-up before final data extraction. The main outcome measures were discrimination and calibration of models for in-hospital deterioration (defined as any requirement of ventilatory support or critical care, or death) and mortality, incorporating predefined subgroups. Results 76 588 participants were included, of whom 27 352 (37.4%) deteriorated and 12 581 (17.4%) died. Both the 4C Mortality (0.78 (0.77 to 0.78)) and 4C Deterioration scores (pooled C-statistic 0.76 (95% CI 0.75 to 0.77)) demonstrated consistent discrimination across all nine National Health Service regions, with similar performance metrics to the original validation cohorts. Calibration remained stable (4C Mortality: pooled slope 1.09, pooled calibration-in-the-large 0.12; 4C Deterioration: 1.00, –0.04), with no need for temporal recalibration during the second UK pandemic wave of hospital admissions. Conclusion Both 4C risk stratification models demonstrate consistent performance to predict clinical deterioration and mortality in a large prospective second wave validation cohort of UK patients. Despite recent advances in the treatment and management of adults hospitalised with COVID-19, both scores can continue to inform clinical decision making. Trial registration number NCT66726260.

Summary Background Emergency admissions for infection often lack initial diagnostic certainty. COVID-19 has highlighted a need for novel diagnostic approaches to indicate likelihood of viral infection in a pandemic setting. We aimed to derive and validate a blood transcriptional signature to detect viral infections, including COVID-19, among adults with suspected infection who presented to the emergency department. Methods Individuals (aged ≥18 years) presenting with suspected infection to an emergency department at a major teaching hospital in the UK were prospectively recruited as part of the Bioresource in Adult Infectious Diseases (BioAID) discovery cohort. Whole-blood RNA sequencing was done on samples from participants with subsequently confirmed viral, bacterial, or no infection diagnoses. Differentially expressed host genes that met additional filtering criteria were subjected to feature selection to derive the most parsimonious discriminating signature. We validated the signature via RT-qPCR in a prospective validation cohort of participants who presented to an emergency department with undifferentiated fever, and a second case-control validation cohort of emergency department participants with PCR-positive COVID-19 or bacterial infection. We assessed signature performance by calculating the area under receiver operating characteristic curves (AUROCs), sensitivities, and specificities. Findings A three-gene transcript signature, comprising HERC6, IGF1R, and NAGK, was derived from the discovery cohort of 56 participants with bacterial infections and 27 with viral infections. In the validation cohort of 200 participants, the signature differentiated bacterial from viral infections with an AUROC of 0·976 (95% CI 0·919−1·000), sensitivity of 97·3% (85·8−99·9), and specificity of 100% (63·1−100). The AUROC for C-reactive protein (CRP) was 0·833 (0·694−0·944) and for leukocyte count was 0·938 (0·840−0·986). The signature achieved higher net benefit in decision curve analysis than either CRP or leukocyte count for discriminating viral infections from all other infections. In the second validation analysis, which included SARS-CoV-2-positive participants, the signature discriminated 35 bacterial infections from 34 SARS-CoV-2-positive COVID-19 infections with AUROC of 0·953 (0·893−0·992), sensitivity 88·6%, and specificity of 94·1%. Interpretation This novel three-gene signature discriminates viral infections, including COVID-19, from other emergency infection presentations in adults, outperforming both leukocyte count and CRP, thus potentially providing substantial clinical utility in managing acute presentations with infection. Funding National Institute for Health Research, Medical Research Council, Wellcome Trust, and EU-FP7.

Background Plantar fasciitis, which is a common cause of heel pain, often results in significant morbidity. In cases who are not responsive to initial conservative treatment, invasive procedures, often in the form of local infiltration of steroid are required. These procedures are associated with significant complications. Local Platelet Rich Plasma (PRP) infiltration is an emerging addition to these treatments. However, whether it is more effective in reducing pain and improving function than other treatments (such as steroid injections or whole blood) remains controversial. Methods Skeletally mature patients with plantar fasciitis who had failed conservative therapy were randomized using envelope method into 2 groups: PRP and Steroid group. The participants were assessed for pain using Visual Analog Scale on the day of presentation, and then after therapy at 2 weeks, 4 weeks, 3 months, and 6 months. They were additionally assessed on final follow-up using AOFAS hind-foot Score. Results 118 patients were randomized into 2 groups: 58 patients to the PRP group and 60 to the Steroid group. PRP was associated with greater improvement in VAS score and resulted in superior AOFAS score at 6 months as compared to steroid injection. The authors did not find any local or systemic complications in any of the groups. The result and difference were more pronounced as the time from injection increased and maximal benefit was observed at 6 months follow-up. None of the patients needed a repeat injection at 6 months. Conclusion Our study expands on the previous studies to provide a better evidence for superiority of PRP over local injection of steroid in plantar fasciitis, and the authors conclude that PRP provides better pain relief and function as compared to steroid injection. Level of evidence Level 1 Prospective Randomized Control Trial (RCT)

COVID-19 has been shown to spread rapidly among Healthcare Workers (HCWs) and there is an urgent need to find and implement various mitigation strategies for these individuals. In this study, we summarize the epidemiological characteristics of the COVID-19 outbreak among HCWs in a tertiary care hospital and compare various parameters and preventive measures taken by infected and uninfected subjects. A retrospective questionnaire and record-based analysis was carried out to evaluate the epidemiological and clinical parameters of the participants. Preventive strategies such as masking, hand hygiene and use of prophylactic agents were compared for infected and uninfected subjects. Appropriate statistical tests were applied wherever required. The average age of participants in the COVID-19 positive group was 35.9 years and 52.1% of the positive HCWs were symptomatic. Three of these subjects needed hospitalization and one required admission to an intensive care unit. The study found a protective role of full course of prophylactic hydroxychloroquine in treated subjects versus untreated controls (p = 0.021) and benefit of N95 masks over others (p

Background The National Early Warning Score (NEWS2) is currently recommended in the UK for the risk stratification of COVID-19 patients, but little is known about its ability to detect severe cases. We aimed to evaluate NEWS2 for the prediction of severe COVID-19 outcome and identify and validate a set of blood and physiological parameters routinely collected at hospital admission to improve upon the use of NEWS2 alone for medium-term risk stratification. Methods Training cohorts comprised 1276 patients admitted to King’s College Hospital National Health Service (NHS) Foundation Trust with COVID-19 disease from 1 March to 30 April 2020. External validation cohorts included 6237 patients from five UK NHS Trusts (Guy’s and St Thomas’ Hospitals, University Hospitals Southampton, University Hospitals Bristol and Weston NHS Foundation Trust, University College London Hospitals, University Hospitals Birmingham), one hospital in Norway (Oslo University Hospital), and two hospitals in Wuhan, China (Wuhan Sixth Hospital and Taikang Tongji Hospital). The outcome was severe COVID-19 disease (transfer to intensive care unit (ICU) or death) at 14 days after hospital admission. Age, physiological measures, blood biomarkers, sex, ethnicity, and comorbidities (hypertension, diabetes, cardiovascular, respiratory and kidney diseases) measured at hospital admission were considered in the models. Results A baseline model of ‘NEWS2 + age’ had poor-to-moderate discrimination for severe COVID-19 infection at 14 days (area under receiver operating characteristic curve (AUC) in training cohort = 0.700, 95% confidence interval (CI) 0.680, 0.722; Brier score = 0.192, 95% CI 0.186, 0.197). A supplemented model adding eight routinely collected blood and physiological parameters (supplemental oxygen flow rate, urea, age, oxygen saturation, C-reactive protein, estimated glomerular filtration rate, neutrophil count, neutrophil/lymphocyte ratio) improved discrimination (AUC = 0.735; 95% CI 0.715, 0.757), and these improvements were replicated across seven UK and non-UK sites. However, there was evidence of miscalibration with the model tending to underestimate risks in most sites. Conclusions NEWS2 score had poor-to-moderate discrimination for medium-term COVID-19 outcome which raises questions about its use as a screening tool at hospital admission. Risk stratification was improved by including readily available blood and physiological parameters measured at hospital admission, but there was evidence of miscalibration in external sites. This highlights the need for a better understanding of the use of early warning scores for COVID.

The risk of tuberculosis (TB) is variable among individuals with latentMycobacterium tuberculosisinfection (LTBI), but validated estimates of personalized risk are lacking. In pooled data from 18 systematically identified cohort studies from 20 countries, including 80,468 individuals tested for LTBI, 5-year cumulative incident TB risk among people with untreated LTBI was 15.6% (95% confidence interval (CI), 8.0-29.2%) among child contacts, 4.8% (95% CI, 3.0-7.7%) among adult contacts, 5.0% (95% CI, 1.6-14.5%) among migrants and 4.8% (95% CI, 1.5-14.3%) among immunocompromised groups. We confirmed highly variable estimates within risk groups, necessitating an individualized approach to risk stratification. Therefore, we developed a personalized risk predictor for incident TB (PERISKOPE-TB) that combines a quantitative measure of T cell sensitization and clinical covariates. Internal-external cross-validation of the model demonstrated a random effects meta-analysis C-statistic of 0.88 (95% CI, 0.82-0.93) for incident TB. In decision curve analysis, the model demonstrated clinical utility for targeting preventative treatment, compared to treating all, or no, people with LTBI. We challenge the current crude approach to TB risk estimation among people with LTBI in favor of our evidence-based and patient-centered method, in settings aiming for pre-elimination worldwide. The risk of developing active tuberculosis (TB) in individuals with latent TB infection is highly variable within and among different risk groups. A personalized risk predictor was developed to better target preventative treatment to individuals at greatest risk, supporting evidence-based clinical decision-making for latent TB.

BACKGROUND: Intra-articular injection therapy constituting corticosteroids, viscosupplements and blood-derived products are considered to have a key role in non-operative management of osteoarthritis knee. While corticosteroids and viscosupplements have proven short-term efficacy in early osteoarthritis; orthobiologics are gaining increased attention in osteoarthritis management. The aim of present study was thus to compare two commonly used biologics (platelet-rich plasma/PRP and autologous conditioned serum/ACS) to each other and to established therapies. METHODS: After required institutional clearances, all patients presenting with early primary osteoarthritis knee who had failed initial conservative management and received only unilateral knee injection were included. Patients in the PRP group were compared to the other groups (comprising the HA/hyaluronic acid group, steroid group, and a matched cohort who had been administered ACS for the same indication earlier). Clinical outcome was evaluated using the Western Ontario and McMaster Universities Arthritis Index (WOMAC) questionnaire and Visual Analogue scale (VAS) pre-injection and at 6 months. RESULTS: ACS and PRP did not have any significant difference in terms of either WOMAC score (p = 0.154) or VAS score at 6 months (p = 0.850). The scores for both these orthobiologics were better than the control groups (HA group and Steroid group). Between the two control groups, HA group had better VAS scores as compared to the Steroid group (p = 0.008). CONCLUSION: The clinical outcomes following intra-articular injection of ACS and PRP are better than controls (HA and steroid), but a difference between the two orthobiologics could not be demonstrated. LEVEL OF EVIDENCE: 3b.

BackgroundIdentification of an accurate, low-cost triage test for pulmonary TB among people presenting to healthcare facilities is an urgent global research priority. We assessed the diagnostic accuracy and clinical utility of C-reactive protein (CRP) for TB triage among symptomatic adult outpatients, irrespective of HIV status.MethodsWe prospectively enrolled adults reporting at least one (for people with HIV) or two (for people without HIV) symptoms of cough, fever, night sweats, or weight loss at two TB clinics in Cape Town, South Africa. Participants provided sputum for culture and Xpert MTB/RIF Ultra. We evaluated the diagnostic accuracy of CRP (measured using a laboratory-based assay) against a TB-culture reference standard as the area under the receiver operating characteristic curve (AUROC) and sensitivity and specificity at pre-specified thresholds. We assessed clinical utility using decision curve analysis, benchmarked against WHO recommendations.ResultsOf 932 included individuals, 255 (27%) had culture-confirmed TB and 389 (42%) were living with HIV. CRP demonstrated an AUROC of 0.80 (95% confidence interval 0.77–0.83), with sensitivity 93% (89–95%) and specificity 54% (50–58%) using a primary cut-off of ≥10mg/L. Performance was similar among people with HIV to those without. In decision curve analysis, CRP-based triage offered greater clinical utility than confirmatory testing for all up to a number willing to test threshold of 20 confirmatory tests per true positive TB case diagnosed.ConclusionsCRP approached the WHO-defined minimum performance for a TB triage test and showed evidence of clinical utility among symptomatic outpatients, irrespective of HIV status.

BackgroundCOVID-19 is a multi-system disease and patients who survive may experience in-hospital complications. These complications are likely to have important short and long-term consequences for patients, healthcare utilisation, healthcare system preparedness, and society amidst the ongoing COVID-19 pandemic. Our aim was to characterise the extent and impact of COVID-19 complications, particularly in those who survive using the International Severe Acute Respiratory and emerging Infections Consortium (ISARIC) WHO Clinical Characterisation Protocol UK (CCP-UK).MethodsA multicentre, prospective cohort study in 302 UK healthcare facilities of adults hospitalised with COVID-19 between 17th January and 4th August 2020. Complications were defined as organ specific diagnoses occurring alone or in addition to any hallmarks of COVID-19 illness. Outcomes included death, critical care use, and ability to self-care at hospital discharge. We used multilevel logistic regression and survival models to explore associations between these outcomes and in-hospital complications, age, and pre-existing comorbidities.ResultsOf patients admitted to hospital for management of COVID-19, 49.7% (36 367/73 197) experienced at least one complication. The mean age of our cohort was 71.1 years old (SD 18.7), included more males (56.0%, 41 025/73 ) with 81.0% (59 289/73 197) of patients having at least one comorbidity. Males over 60 were most likely to experience a complication (60 y and over, 54.5% [16 579/30 416] in males and 48.2% [11 707/24 288] in females; Under 60 y, 48.8% [5179/10 609] in males, 36.6% [2814/7689] in females). Renal (24.3%, 17 752/73 197), complex respiratory 18.4% (13 486/73 197), and systemic (16.3%, 11 895/73 197) complications were most frequent. Cardiovascular (12.3%, 8973/73 197), neurological (4.3%, 3115/73 197), and gastrointestinal/liver (0.8%, 7901/73 197) complications were also reported. The presence of any complication was associated with significantly worse survival (adjusted HR 1.74, 95% CI 1.64 to 1.84) and increased admission to critical care (adjusted OR 7.25, 95% CI 6.83 to 7.69). Reduced ability to self-care at discharge was significantly greater in patients who experienced a complication (adjusted OR 2.42, 95% CI 2.31 to 2.54) and was greatest in those who experienced neurological complications (adjusted OR 4.39, 95% CI 3.95 to 4.89). ConclusionsComplications and worse functional outcomes in patients admitted to hospital with COVID-19 are high, even in young, previously healthy individuals. Acute complications are associated with reduced ability to self-care at discharge, with neurological complications being associated with the worst functional outcomes. COVID-19 complications are likely to cause significant strain on health and social care in the coming years. These data will help in the design and provision of services aimed at the post-hospitalisation care of patients with COVID-19.

Background: Microbiological characterisation of co-infections and secondary infections in patients with COVID-19 is lacking, and antimicrobial use is high. We aimed to describe microbiologically confirmed co-infections and secondary infections, and antimicrobial use, in patients admitted to hospital with COVID-19. Methods: The International Severe Acute Respiratory and Emerging Infections Consortium (ISARIC) WHO Clinical Characterisation Protocol UK (CCP-UK) study is an ongoing, prospective cohort study recruiting inpatients from 260 hospitals in England, Scotland, and Wales, conducted by the ISARIC Coronavirus Clinical Characterisation Consortium. Patients with a confirmed or clinician-defined high likelihood of SARS-CoV-2 infection were eligible for inclusion in the ISARIC WHO CCP-UK study. For this specific study, we excluded patients with a recorded negative SARS-CoV-2 test result and those without a recorded outcome at 28 days after admission. Demographic, clinical, laboratory, therapeutic, and outcome data were collected using a prespecified case report form. Organisms considered clinically insignificant were excluded. Findings: We analysed data from 48 902 patients admitted to hospital between Feb 6 and June 8, 2020. The median patient age was 74 years (IQR 59–84) and 20 786 (42·6%) of 48 765 patients were female. Microbiological investigations were recorded for 8649 (17·7%) of 48 902 patients, with clinically significant COVID-19-related respiratory or bloodstream culture results recorded for 1107 patients. 762 (70·6%) of 1080 infections were secondary, occurring more than 2 days after hospital admission. Staphylococcus aureus and Haemophilus influenzae were the most common pathogens causing respiratory co-infections (diagnosed ≤2 days after admission), with Enterobacteriaceae and S aureus most common in secondary respiratory infections. Bloodstream infections were most frequently caused by Escherichia coli and S aureus. Among patients with available data, 13 390 (37·0%) of 36 145 had received antimicrobials in the community for this illness episode before hospital admission and 39 258 (85·2%) of 46 061 patients with inpatient antimicrobial data received one or more antimicrobials at some point during their admission (highest for patients in critical care). We identified frequent use of broad-spectrum agents and use of carbapenems rather than carbapenem-sparing alternatives. Interpretation: In patients admitted to hospital with COVID-19, microbiologically confirmed bacterial infections are rare, and more likely to be secondary infections. Gram-negative organisms and S aureus are the predominant pathogens. The frequency and nature of antimicrobial use are concerning, but tractable targets for stewardship interventions exist. Funding: National Institute for Health Research (NIHR), UK Medical Research Council, Wellcome Trust, UK Department for International Development, Bill & Melinda Gates Foundation, EU Platform for European Preparedness Against (Re-)emerging Epidemics, NIHR Health Protection Research Unit (HPRU) in Emerging and Zoonotic Infections at University of Liverpool, and NIHR HPRU in Respiratory Infections at Imperial College London.

Summary Background We hypothesised that host-response biomarkers of viral infections might contribute to early identification of individuals infected with SARS-CoV-2, which is critical to breaking the chains of transmission. We aimed to evaluate the diagnostic accuracy of existing candidate whole-blood transcriptomic signatures for viral infection to predict positivity of nasopharyngeal SARS-CoV-2 PCR testing. Methods We did a nested case-control diagnostic accuracy study among a prospective cohort of health-care workers (aged ≥18 years) at St Bartholomew's Hospital (London, UK) undergoing weekly blood and nasopharyngeal swab sampling for whole-blood RNA sequencing and SARS-CoV-2 PCR testing, when fit to attend work. We identified candidate blood transcriptomic signatures for viral infection through a systematic literature search. We searched MEDLINE for articles published between database inception and Oct 12, 2020, using comprehensive MeSH and keyword terms for "viral infection", "transcriptome", "biomarker", and "blood". We reconstructed signature scores in blood RNA sequencing data and evaluated their diagnostic accuracy for contemporaneous SARS-CoV-2 infection, compared with the gold standard of SARS-CoV-2 PCR testing, by quantifying the area under the receiver operating characteristic curve (AUROC), sensitivities, and specificities at a standardised Z score of at least 2 based on the distribution of signature scores in test-negative controls. We used pairwise DeLong tests compared with the most discriminating signature to identify the subset of best performing biomarkers. We evaluated associations between signature expression, viral load (using PCR cycle thresholds), and symptom status visually and using Spearman rank correlation. The primary outcome was the AUROC for discriminating between samples from participants who tested negative throughout the study (test-negative controls) and samples from participants with PCR-confirmed SARS-CoV-2 infection (test-positive participants) during their first week of PCR positivity. Findings We identified 20 candidate blood transcriptomic signatures of viral infection from 18 studies and evaluated their accuracy among 169 blood RNA samples from 96 participants over 24 weeks. Participants were recruited between March 23 and March 31, 2020. 114 samples were from 41 participants with SARS-CoV-2 infection, and 55 samples were from 55 test-negative controls. The median age of participants was 36 years (IQR 27–47) and 69 (72%) of 96 were women. Signatures had little overlap of component genes, but were mostly correlated as components of type I interferon responses. A single blood transcript for IFI27 provided the highest accuracy for discriminating between test-negative controls and test-positive individuals at the time of their first positive SARS-CoV-2 PCR result, with AUROC of 0·95 (95% CI 0·91–0·99), sensitivity 0·84 (0·70–0·93), and specificity 0·95 (0·85–0·98) at a predefined threshold (Z score >2). The transcript performed equally well in individuals with and without symptoms. Three other candidate signatures (including two to 48 transcripts) had statistically equivalent discrimination to IFI27 (AUROCs 0·91–0·95). Interpretation Our findings support further urgent evaluation and development of blood IFI27 transcripts as a biomarker for early phase SARS-CoV-2 infection for screening individuals at high risk of infection, such as contacts of index cases, to facilitate early case isolation and early use of antiviral treatments as they emerge. Funding Barts Charity, Wellcome Trust, and National Institute of Health Research.

Background\ud \ud Mortality rates in hospitalised patients with COVID-19 in the UK appeared to decline during the first wave of the pandemic. We aimed to quantify potential drivers of this change and identify groups of patients who remain at high risk of dying in hospital.\ud \ud \ud Methods\ud \ud In this multicentre prospective observational cohort study, the International Severe Acute Respiratory and Emerging Infections Consortium WHO Clinical Characterisation Protocol UK recruited a prospective cohort of patients with COVID-19 admitted to 247 acute hospitals in England, Scotland, and Wales during the first wave of the pandemic (between March 9 and Aug 2, 2020). We included all patients aged 18 years and older with clinical signs and symptoms of COVID-19 or confirmed COVID-19 (by RT-PCR test) from assumed community-acquired infection. We did a three-way decomposition mediation analysis using natural effects models to explore associations between week of admission and in-hospital mortality, adjusting for confounders (demographics, comorbidities, and severity of illness) and quantifying potential mediators (level of respiratory support and steroid treatment). The primary outcome was weekly in-hospital mortality at 28 days, defined as the proportion of patients who had died within 28 days of admission of all patients admitted in the observed week, and it was assessed in all patients with an outcome. This study is registered with the ISRCTN Registry, ISRCTN66726260.\ud \ud \ud Findings\ud \ud Between March 9, and Aug 2, 2020, we recruited 80 713 patients, of whom 63 972 were eligible and included in the study. Unadjusted weekly in-hospital mortality declined from 32·3% (95% CI 31·8–32·7) in March 9 to April 26, 2020, to 16·4% (15·0–17·8) in June 15 to Aug 2, 2020. Reductions in mortality were observed in all age groups, in all ethnic groups, for both sexes, and in patients with and without comorbidities. After adjustment, there was a 32% reduction in the risk of mortality per 7-week period (odds ratio [OR] 0·68 [95% CI 0·65–0·71]). The higher proportions of patients with severe disease and comorbidities earlier in the first wave (March and April) than in June and July accounted for 10·2% of this reduction. The use of respiratory support changed during the first wave, with gradually increased use of non-invasive ventilation over the first wave. Changes in respiratory support and use of steroids accounted for 22·2%, OR 0·95 (0·94–0·95) of the reduction in in-hospital mortality.\ud \ud \ud Interpretation\ud \ud The reduction in in-hospital mortality in patients with COVID-19 during the first wave in the UK was partly accounted for by changes in the case-mix and illness severity. A significant reduction in in-hospital mortality was associated with differences in respiratory support and critical care use, which could partly reflect accrual of clinical knowledge. The remaining improvement in in-hospital mortality is not explained by these factors, and could be associated with changes in community behaviour, inoculum dose, and hospital capacity strain.\ud \ud \ud Funding\ud \ud National Institute for Health Research and the Medical Research Council.

Background\ud \ud Prognostic models to predict the risk of clinical deterioration in acute COVID-19 cases are urgently required to inform clinical management decisions.\ud \ud \ud Methods\ud \ud We developed and validated a multivariable logistic regression model for in-hospital clinical deterioration (defined as any requirement of ventilatory support or critical care, or death) among consecutively hospitalised adults with highly suspected or confirmed COVID-19 who were prospectively recruited to the International Severe Acute Respiratory and Emerging Infections Consortium Coronavirus Clinical Characterisation Consortium (ISARIC4C) study across 260 hospitals in England, Scotland, and Wales. Candidate predictors that were specified a priori were considered for inclusion in the model on the basis of previous prognostic scores and emerging literature describing routinely measured biomarkers associated with COVID-19 prognosis. We used internal–external cross-validation to evaluate discrimination, calibration, and clinical utility across eight National Health Service (NHS) regions in the development cohort. We further validated the final model in held-out data from an additional NHS region (London).\ud \ud \ud Findings\ud \ud 74 944 participants (recruited between Feb 6 and Aug 26, 2020) were included, of whom 31 924 (43·2%) of 73 948 with available outcomes met the composite clinical deterioration outcome. In internal–external cross-validation in the development cohort of 66 705 participants, the selected model (comprising 11 predictors routinely measured at the point of hospital admission) showed consistent discrimination, calibration, and clinical utility across all eight NHS regions. In held-out data from London (n=8239), the model showed a similarly consistent performance (C-statistic 0·77 [95% CI 0·76 to 0·78]; calibration-in-the-large 0·00 [–0·05 to 0·05]); calibration slope 0·96 [0·91 to 1·01]), and greater net benefit than any other reproducible prognostic model.\ud \ud \ud Interpretation\ud \ud The 4C Deterioration model has strong potential for clinical utility and generalisability to predict clinical deterioration and inform decision making among adults hospitalised with COVID-19.\ud \ud \ud Funding\ud \ud National Institute for Health Research (NIHR), UK Medical Research Council, Wellcome Trust, Department for International Development, Bill & Melinda Gates Foundation, EU Platform for European Preparedness Against (Re-)emerging Epidemics, NIHR Health Protection Research Unit (HPRU) in Emerging and Zoonotic Infections at University of Liverpool, NIHR HPRU in Respiratory Infections at Imperial College London.

The correlates of natural protective immunity to SARS-CoV-2 in the majority who experience asymptomatic infection or non-severe disease are not fully characterised, and remain important as new variants emerge. We addressed this question using blood transcriptomics, multiparameter flow cytometry and T cell receptor (TCR) sequencing spanning the time of incident infection. We identified a type 1 interferon (IFN) response common to other acute respiratory viruses, and a cell proliferation response that discriminated SARS-CoV-2 from other viruses. These responses peaked by the time the virus was first detected, and in some preceded virus detection. Cell proliferation was most evident in CD8 T cells and associated with rapid expansion of SARS-CoV-2 reactive TCRs. We found an equally rapid increase in immunoglobulin transcripts, but circulating virus-specific antibodies lagged by 1-2 weeks. Our data support a protective role for rapid induction of type 1 IFN and CD8 T cell responses to SARS-CoV-2.

The field of prediction modelling has exploded during the COVID-19 pandemic, with countless studies seeking to derive and/or validate models to assist diagnosis of SARS-CoV-2 or to predict clinical outcomes of infection. While the vast majority of reports have been of a poor standard,1 there have been some examples of higher quality work, including the QCOVID prognostic model.2 Whereas most prediction models are intended to predict a single outcome, QCOVID seeks to predict the risk of acquiring and then either dying from or being hospitalised with SARS-CoV-2 in the general population. The model was originally derived using data from 6.1 million people in England during the first pandemic wave (January–April 2020) and showed promising performance in a recent analysis by the Office for National Statistics over a similar time period.3 QCOVID is implemented online,4 although stipulated for research rather than clinical use, and provides distinct probabilities of COVID-19 hospitalisation and COVID-19 mortality. Simpson et al report an external validation of QCOVID using data from Scotland over two periods (1 March 2020 to 30 April 2020 and 1 May 2020 to 30 June 2020), designed to test the performance of the algorithms during time intervals that aligned with the original QCOVID derivation and temporal validation cohorts.5 The authors use a population-based approach, including data from primary care facilities covering an impressive 99% of the Scottish population. The data provided …

We hypothesised that host-response biomarkers of viral infections may contribute to early identification of SARS-CoV-2 infected individuals, critical to breaking chains of transmission. We identified 20 candidate blood transcriptomic signatures of viral infection by systematic review and evaluated their ability to detect SARS-CoV-2 infection, compared to the gold-standard of virus PCR tests, among a prospective cohort of 400 hospital staff subjected to weekly testing when fit to attend work. The transcriptional signatures had limited overlap, but were mostly co-correlated as components of type 1 interferon responses. We reconstructed each signature score in blood RNA sequencing data from 41 individuals over sequential weeks spanning a first positive SARS-CoV-2 PCR, and after 6-month convalescence. A single blood transcript for IFI27 provided the highest accuracy for discriminating individuals at the time of their first positive viral PCR result from uninfected controls, with area under the receiver operating characteristic curve (AUROC) of 0.95 (95% confidence interval 0.91–0.99), sensitivity 0.84 (0.7–0.93) and specificity 0.95 (0.85–0.98) at a predefined test threshold. The test performed equally well in individuals with and without symptoms, correlated with viral load, and identified incident infections one week before the first positive viral PCR with sensitivity 0.4 (0.17–0.69) and specificity 0.95 (0.85–0.98). Our findings strongly support further urgent evaluation and development of blood IFI27 transcripts as a biomarker for early phase SARS-CoV-2 infection, for screening individuals such as contacts of index cases, in order to facilitate early case isolation and early antiviral treatments as they emerge.

BACKGROUND: SARS-CoV-2 serology is used to identify prior infection at individual and at population level. Extended longitudinal studies with multi-timepoint sampling to evaluate dynamic changes in antibody levels are required to identify the time horizon in which these applications of serology are valid, and to explore the longevity of protective humoral immunity. METHODS: Healthcare workers were recruited to a prospective cohort study from the first SARS-CoV-2 epidemic peak in London, undergoing weekly symptom screen, viral PCR and blood sampling over 16-21 weeks. Serological analysis (n =12,990) was performed using semi-quantitative Euroimmun IgG to viral spike S1 domain and Roche total antibody to viral nucleocapsid protein (NP) assays. Comparisons were made to pseudovirus neutralizing antibody measurements. FINDINGS: A total of 157/729 (21.5%) participants developed positive SARS-CoV-2 serology by one or other assay, of whom 31.0% were asymptomatic and there were no deaths. Peak Euroimmun anti-S1 and Roche anti-NP measurements correlated (r = 0.57, p

ObjectiveTo develop and validate a pragmatic risk score to predict mortality in patients admitted to hospital with coronavirus disease 2019 (covid-19).DesignProspective observational cohort study.SettingInternational Severe Acute Respiratory and emerging Infections Consortium (ISARIC) World Health Organization (WHO) Clinical Characterisation Protocol UK (CCP-UK) study (performed by the ISARIC Coronavirus Clinical Characterisation Consortium—ISARIC-4C) in 260 hospitals across England, Scotland, and Wales. Model training was performed on a cohort of patients recruited between 6 February and 20 May 2020, with validation conducted on a second cohort of patients recruited after model development between 21 May and 29 June 2020.ParticipantsAdults (age ≥18 years) admitted to hospital with covid-19 at least four weeks before final data extraction.Main outcome measureIn-hospital mortality.Results35 463 patients were included in the derivation dataset (mortality rate 32.2%) and 22 361 in the validation dataset (mortality rate 30.1%). The final 4C Mortality Score included eight variables readily available at initial hospital assessment: age, sex, number of comorbidities, respiratory rate, peripheral oxygen saturation, level of consciousness, urea level, and C reactive protein (score range 0-21 points). The 4C Score showed high discrimination for mortality (derivation cohort: area under the receiver operating characteristic curve 0.79, 95% confidence interval 0.78 to 0.79; validation cohort: 0.77, 0.76 to 0.77) with excellent calibration (validation: calibration-in-the-large=0, slope=1.0). Patients with a score of at least 15 (n=4158, 19%) had a 62% mortality (positive predictive value 62%) compared with 1% mortality for those with a score of 3 or less (n=1650, 7%; negative predictive value 99%). Discriminatory performance was higher than 15 pre-existing risk stratification scores (area under the receiver operating characteristic curve range 0.61-0.76), with scores developed in other covid-19 cohorts often performing poorly (range 0.63-0.73).ConclusionsAn easy-to-use risk stratification score has been developed and validated based on commonly available parameters at hospital presentation. The 4C Mortality Score outperformed existing scores, showed utility to directly inform clinical decision making, and can be used to stratify patients admitted to hospital with covid-19 into different management groups. The score should be further validated to determine its applicability in other populations.Study registrationISRCTN66726260

BackgroundSARS-CoV-2 serology is used to identify prior infection at individual and at population level. Extended longitudinal studies with multi-timepoint sampling to evaluate dynamic changes in antibody levels are required to identify the time horizon in which these applications of serology are valid, and to explore the longevity of protective humoral immunity.MethodsHealth-care workers were recruited to a prospective cohort study from the first SARS-CoV-2 epidemic peak in London, undergoing weekly symptom screen, viral PCR and blood sampling over 16-21 weeks. Serological analysis (n=12,990) was performed using semi-quantitative Euroimmun IgG to viral spike S1 domain and Roche total antibody to viral nucleocapsid protein (NP) assays. Comparisons were made to previously reported pseudovirus neutralising antibody measurements.FindingsA total of 157/729 (21.5%) participants developed positive SARS-CoV-2 serology by one or other assay, of whom 31.0% were asymptomatic and there were no deaths. Peak Euroimmun anti-S1 and Roche anti-NP measurements correlated (r=0.57, pInterpretationMild SARS-CoV-2 infection is associated with heterogenous serological responses in Euroimmun anti-S1 and Roche anti-NP assays. Anti-S1 responses showed faster rates of clearance, more rapid transition from high to low level production rate and greater reduction in production rate after this transition. The application of individual assays for diagnostic and epidemiological serology requires validation in time series analysis.FundingCharitable donations via Barts CharityResearch in contextEvidence before this studyWe searched PubMed, medRxiv, and bioRxiv for [“antibody” OR “serology”] AND [“SARS-CoV-2” OR “COVID-19”]. The available literature highlights widespread use of serology to detect recent SARS-CoV-2 infection in individual patients and in population epidemiological surveys. Antibody to virus spike protein S1 domain is widely reported to correlate with neutralising antibody titres. The existing assays have good sensitivity to detect seroconversion within 14 days of incident infection, but the available longitudinal studies have reported variable rates of decline in antibody levels and reversion to undetectable levels in some people over 3 months. High frequency multi-time point serology data for different antibody targets or assays in longitudinal cohorts from the time of incident infection to greater than 3 months follow up are lacking.Added value of this studyWe combine detailed longitudinal serology using the Euroimmun anti-S1 and Roche anti-nucleocapsid protein (NP) assays in 731 health care workers from the time of the first SARS-CoV-2 epidemic peak in London, UK. In 157 seroconverters (using either assay) we show substantial heterogeneity in semiquantitative antibody measurements over time between individuals and between assays. Mathematical modelling of individual participant antibody production and clearance rates in individuals with at least 8 data points over 21 weeks showed anti-S1 antibodies to have a faster clearance rate, earlier transition from the initial antibody production rate to lower rates, and greater reduction in antibody production rate after this transition, compared to anti-NP antibodies as measured by these assays. As a result, Euroimmun anti-S1 measurements peaked earlier and then reduced more rapidly than Roche anti-NP measurements. In this study, these differences led to 21% anti-S1 sero-reversion, compared to 4% anti-NP sero-reversion over 4-5 months.Implications of all of the available evidenceThe rapid decline in anti-S1 antibodies measured by the Euroimmun assay following infection limits its application for diagnostic and epidemiological screening. If generalisable, these data are consistent with the hypothesis that anti-S1 mediated humoral immunity may not be sustained in some people beyond the initial post-infective period. Further work is required to understand the mechanisms behind the heterogeneity in antibody kinetics between individuals to SARS-CoV-2. Our data point to differential mechanisms regulating humoral immunity against these two viral targets.

Prognostic models to predict the risk of clinical deterioration in acute COVID-19 are required to inform clinical management decisions. Among 75,016 consecutive adults across England, Scotland and Wales prospectively recruited to the ISARIC Coronavirus Clinical Characterisation Consortium (ISARIC4C) study, we developed and validated a multivariable logistic regression model for in-hospital clinical deterioration (defined as any requirement of ventilatory support or critical care, or death) using 11 routinely measured variables. We used internal-external cross-validation to show consistent measures of discrimination, calibration and clinical utility across eight geographical regions. We further validated the final model in held-out data from 8,252 individuals in London, with similarly consistent performance (C-statistic 0.77 (95% CI 0.75 to 0.78); calibration-in-the-large 0.01 (−0.04 to 0.06); calibration slope 0.96 (0.90 to 1.02)). Importantly, this model demonstrated higher net benefit than using other candidate scores to inform decision-making. Our 4C Deterioration model thus demonstrates unprecedented clinical utility and generalisability to predict clinical deterioration among adults hospitalised with COVID-19.

ObjectiveTo investigate the relationship between social risk factors and latent tuberculosis infection (LTBI) among individuals who are eligible for LTBI screening in the United Kingdom (UK).MethodsThis cross-sectional study used data collected in the UK Prognostic Evaluation of Diagnostic Interferon-Gamma Release Assays (IGRAs) Consortium Study which enrolled 9176 recent tuberculosis (TB) contacts and migrants at National Health Service (NHS) facilities and community settings in the UK. The study outcome was LTBI (positive IGRA test (QuantiFERON-TB Gold In-Tube or T-SPOT.TB)). The main exposures were history of smoking, history of substance misuse, homelessness, prison stay and socioeconomic deprivation.Results4914 (56.2%) individuals resided in the most deprived areas and 2536 (27.6%) had LTBI. In the multivariable analysis (adjusting for age, gender, place of birth, ethnicity, HIV status, BCG vaccination and recent TB contact) living in the least deprived areas compared with living in the most deprived areas was associated with reduced odds of LTBI (odds ratio (OR)=0.68, 95% CI: 0.51 to 0.90) while ever been homeless (OR=1.50, 95% CI: 1.02 to 2.21) was associated with increased odds of LTBI. Smoking, homelessness and substance misuse were not associated with LTBI.ConclusionSocial deprivation could be an important risk factor for LTBI, highlighting the social inequality in the burden of TB infection in the UK. Migrants and TB contacts who were socially deprived or homeless were at a significantly higher risk for LTBI, thus tailored intense public health interventions to these groups may help to reduce the risk of future TB disease.Trial registration numberClinicalTrials.gov Registry (NCT01162265).

Background The number of proposed prognostic models for COVID-19 is growing rapidly, but it is unknown whether any are suitable for widespread clinical implementation. Methods We independently externally validated the performance candidate prognostic models, identified through a living systematic review, among consecutive adults admitted to hospital with a final diagnosis of COVID-19. We reconstructed candidate models as per original descriptions and evaluated performance for their original intended outcomes using predictors measured at admission. We assessed discrimination, calibration and net benefit, compared to the default strategies of treating all and no patients, and against the most discriminating predictor in univariable analyses. Results We tested 22 candidate prognostic models among 411 participants with COVID-19, of whom 180 (43.8%) and 115 (28.0%) met the endpoints of clinical deterioration and mortality, respectively. Highest areas under receiver operating characteristic (AUROC) curves were achieved by the NEWS2 score for prediction of deterioration over 24 h (0.78; 95% CI 0.73–0.83), and a novel model for prediction of deterioration, Oxygen saturation on room air and patient age are strong predictors of deterioration and mortality among hospitalised adults with COVID-19, respectively. None of the 22 prognostic models evaluated in this study add incremental value to these univariable predictors.

Glasziou and colleagues discuss the waste in covid-19 research that amplifies pre-existing failures.1 We think the situation goes beyond waste. Delaying publication of trial results after data have been collected and analysed is unethical. It leads to ongoing use of ineffective and potentially toxic compounds, plus avoidable and potentially harmful initiation of new studies using the same compounds. Moreover, the sheer number of small trials runs the risk of falsely finding apparent benefit, which is complicated by the potential misuse …

BackgroundMedical schools differ, particularly in their teaching, but it is unclear whether such differences matter, although influential claims are often made. The Medical School Differences (MedDifs) study brings together a wide range of measures of UK medical schools, including postgraduate performance, fitness to practise issues, specialty choice, preparedness, satisfaction, teaching styles, entry criteria and institutional factors.MethodAggregated data were collected for 50 measures across 29 UK medical schools. Data includeinstitutional history(e.g. rate of production of hospital and GP specialists in the past),curricular influences(e.g. PBL schools, spend per student, staff-student ratio), selection measures(e.g. entry grades),teaching and assessment(e.g. traditional vs PBL, specialty teaching, self-regulated learning), student satisfaction, Foundation selection scores,Foundation satisfaction,postgraduate examination performance andfitness to practise(postgraduate progression, GMC sanctions). Six specialties (General Practice, Psychiatry, Anaesthetics, Obstetrics and Gynaecology, Internal Medicine, Surgery) were examined in more detail.ResultsMedical school differences are stable across time (median alpha = 0.835). The 50 measures were highly correlated, 395 (32.2%) of 1225 correlations being significant withp p Problem-based learning (PBL) schools differ on many measures, including lower performance on postgraduate assessments. While these are in part explained by lower entry grades, a surprising finding is that schools such as PBL schools which reportedgreaterstudent satisfaction with feedback also showedlowerperformance at postgraduate examinations.More medical school teaching of psychiatry, surgery and anaesthetics did not result in more specialist trainees. Schools that taught more general practice did have more graduates entering GP training, but those graduates performed less well in MRCGP examinations, the negative correlation resulting from numbers of GP trainees and exam outcomes being affected both by non-traditional teaching and by greater historical production of GPs.Postgraduate exam outcomes were also higher in schools with more self-regulated learning, but lower in larger medical schools.A path model for 29 measures found a complex causal nexus, most measures causing or being caused by other measures. Postgraduate exam performance was influenced by earlier attainment, at entry to Foundation and entry to medical school (the so-called academic backbone), and by self-regulated learning.Foundation measures of satisfaction, including preparedness, had no subsequent influence on outcomes. Fitness to practise issues were more frequent in schools producing more male graduates and more GPs.ConclusionsMedical schools differ in large numbers of ways that are causally interconnected. Differences between schools in postgraduate examination performance, training problems and GMC sanctions have important implications for the quality of patient care and patient safety.

BackgroundThe National Early Warning Score (NEWS2) is currently recommended in the United Kingdom for risk stratification of COVID outcomes, but little is known about its ability to detect severe cases. We aimed to evaluate NEWS2 for severe COVID outcome and identify and validate a set of routinely-collected blood and physiological parameters taken at hospital admission to improve the score.MethodsTraining cohorts comprised 1276 patients admitted to King’s College Hospital NHS Foundation Trust with COVID-19 disease from 1st March to 30th April 2020. External validation cohorts included 5037 patients from four UK NHS Trusts (Guys and St Thomas’ Hospitals, University Hospitals Southampton, University Hospitals Bristol and Weston NHS Foundation Trust, University College London Hospitals), and two hospitals in Wuhan, China (Wuhan Sixth Hospital and Taikang Tongji Hospital). The outcome was severe COVID disease (transfer to intensive care unit or death) at 14 days after hospital admission. Age, physiological measures, blood biomarkers, sex, ethnicity and comorbidities (hypertension, diabetes, cardiovascular, respiratory and kidney diseases) measured at hospital admission were considered in the models.ResultsA baseline model of ‘NEWS2 + age’ had poor-to-moderate discrimination for severe COVID infection at 14 days (AUC in training sample = 0.700; 95% CI: 0.680, 0.722; Brier score = 0.192; 95% CI: 0.186, 0.197). A supplemented model adding eight routinely-collected blood and physiological parameters (supplemental oxygen flow rate, urea, age, oxygen saturation, CRP, estimated GFR, neutrophil count, neutrophil/lymphocyte ratio) improved discrimination (AUC = 0.735; 95% CI: 0.715, 0.757) and these improvements were replicated across five UK and non-UK sites. However, there was evidence of miscalibration with the model tending to underestimate risks in most sites.ConclusionsNEWS2 score had poor-to-moderate discrimination for medium-term COVID outcome which raises questions about its use as a screening tool at hospital admission. Risk stratification was improved by including readily available blood and physiological parameters measured at hospital admission, but there was evidence of miscalibration in external sites. This highlights the need for a better understanding of the use of early warning scores for COVID.Key messagesThe National Early Warning Score (NEWS2), currently recommended for stratification of severe COVID-19 disease in the UK, showed poor-to-moderate discrimination for medium-term outcomes (14-day transfer to ICU or death) among COVID-19 patients.Risk stratification was improved by the addition of routinely-measured blood and physiological parameters routinely at hospital admission (supplemental oxygen, urea, oxygen saturation, CRP, estimated GFR, neutrophil count, neutrophil/lymphocyte ratio) which provided moderate improvements in a risk stratification model for 14-day ICU/death.This improvement over NEWS2 alone was maintained across multiple hospital trusts but the model tended to be miscalibrated with risks of severe outcomes underestimated in most sites.We benefited from existing pipelines for informatics at KCH such as CogStack that allowed rapid extraction and processing of electronic health records. This methodological approach provided rapid insights and allowed us to overcome the complications associated with slow data centralisation approaches.

RATIONALE: Development of diagnostic tools with improved predictive value for tuberculosis (TB) is a global research priority. OBJECTIVES: We evaluated whether implementing higher diagnostic thresholds than currently recommended for QuantiFERON Gold-in-Tube (QFT-GIT), T-SPOT.TB and the tuberculin skin test (TST) might improve prediction of incident TB. METHODS: Follow-up of a UK cohort of 9,610 adult TB contacts and recent migrants was extended by re-linkage to national TB surveillance records (median follow-up 4.7 years). Incidence rates and rate ratios, sensitivities, specificities and predictive values for incident TB were calculated according to ordinal strata for quantitative results of QFT-GIT, T-SPOT.TB and TST (with adjustment for prior BCG). MEASUREMENTS AND MAIN RESULTS: For all tests, incidence rates and rate ratios increased with the magnitude of the test result (p

Background Blood transcriptional signatures may predict risk of tuberculosis (TB). While multiple candidate signatures for active and incipient TB have been identified, it is not known which signature performs best, or whether any meets World Health Organization target product profile (WHO TPP) benchmarks, for incipient TB biomarkers. Methods We performed a systematic review to identify candidate mRNA signatures for incipient TB, along with genome-wide transcriptomic datasets with sampling prior to TB diagnosis. We reconstructed each signature model and directly compared signature performance for diagnosis of incipient TB in the pooled RNAseq dataset, stratified by interval to disease, in a one-stage individual participant data meta-analysis (IPD-MA). Results We tested 17 candidate mRNA signatures in a pooled dataset from four studies conducted in South Africa, Ethiopia, The Gambia and the UK. We included 1,126 samples, with 183 samples from 127 incipient TB cases, Eight signatures (comprising 1–25 transcripts), predominantly reflecting interferon-inducible gene expression, had equivalent diagnostic accuracy for incipient TB over a two-year period with areas under the receiver operating characteristic curves ranging from 0.70 (95% confidence interval 0.64–0.76) to 0.77 (0.71–0.82). The sensitivity of all eight signatures declined with increasing disease-free time interval. Using a threshold derived from two standard deviations above the mean of uninfected controls, giving specificities of >90%, the eight signatures achieved sensitivities of 24.7–39.9% over 24 months, rising to 47.1–81.0% over 3 months. Based on pre-test probability of 2%, the eight signatures achieved positive predictive values from 6.8–9.4% over 24 months, rising to 11.1–14.3% over 3 months. When using biomarker thresholds maximising sensitivity and specificity with equal weighting to both, no signature met the minimum WHO TPP parameters for incipient TB biomarkers over a two-year period. Sensitivity analyses using two-stage IPD-MA with random effects produced similar AUC, sensitivity and specificity estimates. Conclusions Multiple transcriptional signatures perform with equivalent diagnostic accuracy for incipient TB. These biomarkers reflect short-term risk of TB and only exceed WHO benchmarks if applied to 3–6 month intervals. A screening strategy that incorporates serial testing on a 3–6 monthly basis among carefully selected target groups may be required for optimal implementation of these biomarkers.

Summary Background Blood transcriptional signatures are candidates for non-sputum triage or confirmatory tests of tuberculosis. Prospective head-to-head comparisons of their diagnostic accuracy in real-world settings are necessary to assess their clinical use. We aimed to compare the diagnostic accuracy of candidate transcriptional signatures identified by systematic review, in a setting with a high burden of tuberculosis and HIV. Methods We did a prospective observational study nested within a diagnostic accuracy study of sputum Xpert MTB/RIF (Xpert) and Xpert MTB/RIF Ultra (Ultra) tests for pulmonary tuberculosis. We recruited consecutive symptomatic adults aged 18 years or older self-presenting to a tuberculosis clinic in Cape Town, South Africa. Participants provided blood for RNA sequencing, and sputum samples for liquid culture and molecular testing using Xpert and Ultra. We assessed the diagnostic accuracy of candidate blood transcriptional signatures for active tuberculosis (including those intended to distinguish active tuberculosis from other diseases) identified by systematic review, compared with culture or Xpert MTB/RIF positivity as the standard reference. In our primary analysis, patients with tuberculosis were defined as those with either a positive liquid culture or Xpert result. Patients with missing blood RNA or sputum results were excluded. Our primary objective was to benchmark the diagnostic accuracy of candidate transcriptional signatures against the WHO target product profile (TPP) for a tuberculosis triage test. Findings Between Feb 12, 2016, and July 18, 2017, we obtained paired sputum and RNA sequencing data from 181 participants, 54 (30%) of whom had confirmed pulmonary tuberculosis. Of 27 eligible signatures identified by systematic review, four achieved the highest diagnostic accuracy with similar area under the receiver operating characteristic curves (Sweeney3: 90·6% [95% CI 85·6–95·6]; Kaforou25: 86·9% [80·9–92·9]; Roe3: 86·9% [80·3–93·5]; and BATF2: 86·8% [80·6–93·1]), independent of age, sex, HIV status, previous tuberculosis, or sputum smear result. At test thresholds that gave 70% specificity (the minimum WHO TPP specificity for a triage test), these four signatures achieved sensitivities between 83·3% (95% CI 71·3–91·0) and 90·7% (80·1–96·0). No signature met the optimum criteria, of 95% sensitivity and 80% specificity proposed by WHO for a triage test, or the minimum criteria (of 65% sensitivity and 98% specificity) for a confirmatory test, but all four correctly identified Ultra-positive, culture-negative patients. Interpretation Selected blood transcriptional signatures met the minimum WHO benchmarks for a tuberculosis triage test but not for a confirmatory test. Further development of the signatures is warranted to investigate their possible effects on clinical and health economic outcomes as part of a triage strategy, or when used as add-on confirmatory test in conjunction with the highly sensitive Ultra test for Mycobacterium tuberculosis DNA. Funding Royal Society Newton Advanced Fellowship, Wellcome Trust, National Institute of Health Research, and UK Medical Research Council.

Background The roll-out of anti-retroviral therapy (ART) has changed contexts of human immunodeficiency virus (HIV) risk. Here, we summarise direct estimates of HIV incidence among adolescent girls and young women (AGYW) since ART and before large investments in targeted prevention for AGYW in sub-Saharan Africa. Methods Database searches identified studies reporting HIV incident data from serological samples collected among 15-24 year-old females in 10 countries selected for PEPFAR investment in 2015. Estimates collected between 2005-2015, published or received from authors, were summarised by age and sex, and pooled by region. Findings Fifty-one analyses were identified from nine of the eligible countries (save Lesotho). Directly-observed incidence rates were lowest among AGYW in Kumi, Uganda (0.38%) and highest in KwaZulu-Natal, South Africa (7.8% among 15-19y; 8.6% in 20-24y); fishing communities in Uganda (12.4% and 4.7% among 15-19y and 20-24y females); and among sex workers aged 18-24y in South Africa (13.2%) and Zimbabwe (10.8%). In pooled rates from general population studies, the greatest sex differentials were in the youngest age groups, i.e., 15-19y females compared to males in both Southern African (relative risk=5.94; 95% CI:3.39-10.44) and Eastern African countries (3.22; 95% CI:1.51-6.87), and not significantly different among the oldest (25-29y) in either region. Incidence often peaked earlier (during teenage years) among high-risk compared to general populations. Since 2005, AGYW incidence declined in Rakai (Uganda), Manicaland (Zimbabwe), and among sex workers in Kenya, but not in the highest-risk communities in South Africa. Interpretation Few sources of direct estimates of HIV incidence exist in high-burden countries and trend analyses with age/sex disaggregated data are rare but indicate recent declines among AGYW. In some of the highest-risk settings, however, little evidence exists to suggest ART availability and other efforts slowed transmission by 2016. Despite wide geographic diversity in absolute levels of AGYW incidence, risk relative to males persisted in all settings, with the greatest sex differentials in the youngest age groups. To end new infections among the growing population of adolescents in sub-Saharan Africa, prevention programs must address gender inequalities driving excessive risk among adolescent girls.

Summary Background Multiple blood transcriptional signatures have been proposed for identification of active and incipient tuberculosis. We aimed to compare the performance of systematically identified candidate signatures for incipient tuberculosis and to benchmark these against WHO targets. Methods We did a systematic review and individual participant data meta-analysis. We searched Medline and Embase for candidate whole blood mRNA signatures discovered with the primary objective of diagnosis of active or incipient tuberculosis, compared with controls who were healthy or had latent tuberculosis infection. We tested the performance of eligible signatures in whole blood transcriptomic datasets, in which sampling before tuberculosis diagnosis was done and time to disease was available. Culture-confirmed and clinically or radiologically diagnosed pulmonary or extrapulmonary tuberculosis cases were included. Non-progressor (individuals who remained tuberculosis-free during follow-up) samples with less than 6 months of follow-up from the date of sample collection were excluded, as were participants with prevalent tuberculosis and those who received preventive therapy. Scores were calculated for candidate signatures for each participant in the pooled dataset. Receiver operating characteristic curves, sensitivities, and specificities were examined using prespecified intervals to tuberculosis (

Background: \ud What subjects UK medical schools teach, what ways they teach subjects, and how much they teach those subjects is unclear. Whether teaching differences matter is a separate, important question. This study provides a detailed picture of timetabled undergraduate teaching activity at 25 UK medical schools, particularly in relation to problem-based learning (PBL).\ud \ud Method: \ud The Analysis of Teaching of Medical Schools (AToMS) survey used detailed timetables provided by 25 schools with standard 5-year courses. Timetabled teaching events were coded in terms of course year, duration, teaching format, and teaching content. Ten schools used PBL. Teaching times from timetables were validated against two other studies that had assessed GP teaching and lecture, seminar, and tutorial times.\ud \ud Results: \ud A total of 47,258 timetabled teaching events in the academic year 2014/2015 were analysed, including SSCs (student-selected components) and elective studies. A typical UK medical student receives 3960 timetabled hours of teaching during their 5-year course. There was a clear difference between the initial 2 years which mostly contained basic medical science content and the later 3 years which mostly consisted of clinical teaching, although some clinical teaching occurs in the first 2 years. Medical schools differed in duration, format, and content of teaching. Two main factors underlay most of the variation between schools, Traditional vs PBL teaching and Structured vs Unstructured teaching. A curriculum map comparing medical schools was constructed using those factors. PBL schools differed on a number of measures, having more PBL teaching time, fewer lectures, more GP teaching, less surgery, less formal teaching of basic science, and more sessions with unspecified content.\ud \ud Discussion: \ud UK medical schools differ in both format and content of teaching. PBL and non-PBL schools clearly differ, albeit with substantial variation within groups, and overlap in the middle. The important question of whether differences in teaching matter in terms of outcomes is analysed in a companion study (MedDifs) which examines how teaching differences relate to university infrastructure, entry requirements, student perceptions, and outcomes in Foundation Programme and postgraduate training.

Despite much progress globally, TB is still one of the top 10 causes of death worldwide. Several studies have shown the importance of implementing different preventive strategies alongside treatment of TB disease, including BCG vaccination and treatment of latent tuberculosis infection (LTBI). Large-scale population level LTBI treatment is not currently part of WHO guidelines which recommend LTBI treatment only to high risk populations. Moreover, BCG has been widely used in the past decades to both prevent infection with M. tuberculosis and reduce rates of reactivation. In this viewpoint we discuss the hypothesis of BCG vaccination following latent TB treatment and its potential impact across different settings. Keywords: Latent TB, BCG, Vaccination

Background Emergency Department (ED) presentations could present a valuable opportunity to identify high-risk individuals with latent tuberculosis infection (LTBI) and active tuberculosis (TB) disease. We aimed to investigate the prevalence and cost-effectiveness of screening for LTBI and pulmonary TB disease among migrants and under-served groups attending London EDs. Methods We recruited adults attending EDs (18/7/2013–25/5/2017) who were either recent entrants from high TB-incidence countries; or had a history of homelessness, imprisonment, or substance use disorder. We assessed the yield of screening for LTBI (using an interferon-gamma release assay; IGRA) and active pulmonary TB (with a symptom screen, followed by chest radiograph and sputum Xpert MTB/RIF if positive). A cost-effectiveness analysis was performed by calculating cost per true-positive LTBI test. Results A total of 1420 participants were screened for LTBI. Median age was 45 years (IQR 34–60), and the majority were born outside the UK (1,162/1,420; 81.8%). A total of 241/1,420 participants (17.0%) had a history of either substance use disorder, homelessness or imprisonment. Of those with available IGRA results, 214/1,246 (17.2%) were positive. Male sex, age >35 years, non-UK country of birth, and previous TB contact were independent risk factors for being IGRA-positive. Of the 214 with a positive IGRA, 120 (56%) were followed-up by health record review for evidence of progression to TB disease; 5/120 (4.2%) were diagnosed with TB disease (median interval to TB 162 days (IQR 55–108.5)). In the economic analysis, the average cost per patient recruited of correctly diagnosing an LTBI case was £834 (compared to an estimated £1007 per LTBI case diagnosed through primary care). Only 14/513 (2.7%) participants screened for active TB had a positive symptom screen so were eligible for further testing. No cases of active TB were diagnosed. Conclusions Targeted LTBI screening in EDs could be considered to complement the primary care LTBI screening programme. In contrast, active TB screening in EDs using our symptom screen-led algorithm should not be pursued as the yield is likely to be minimal. Other active TB screening models (e.g. routine, automated reviews of ED chest radiographs) could be considered as a focus of future research.

Most tuberculosis (TB) cases in low-incidence settings are thought to be due to reactivation of latent TB infection (LTBI) in high-risk populations [1–3]. Assessment of patients at emergency departments (EDs) is a potential opportunity to achieve early TB diagnosis, and interrupt transmission. An earlier study in London found that 39% of patients diagnosed with TB had attended an ED in the preceding 6 months [4]. Of these, 76% had a chest radiograph performed, of which 86% and 40% were abnormal in cases of pulmonary and extrapulmonary TB, respectively. Attendance at EDs provides an opportunity to identify individuals with LTBI, who may be at risk for progression to active disease and unlikely to engage with healthcare services via other routes., LTBI screening among high-risk groups at EDs could be implemented to identify those at risk of progression to TB disease. Large-scale studies are required to investigate effective TB disease screening strategies in EDs. https://bit.ly/3bTkoOn

Introduction: Physical activity is a core component of COPD management, however, individuals often find standard pulmonary rehabilitation (PR) challenging, resulting in poor initial attendance and high levels of attrition. Our respiratory service provides a Tai Chi programme, which is primarily, but not exclusively, for individuals unable/unwilling to participate in standard PR. Methods: We compared baseline characteristics of participants from this programme with national PR participant baseline data, to assess similarities and differences between these groups. Results: Tai Chi programme baseline data included 88 participants, 59% female, 68% white British. Median values for key variables included age 68, FEV1%predicted 64%, FEV1/FVC ratio 0.64, 6MWT 185m, CAT score 29. Excluding individuals who attended no sessions (n=16), 50% completed the entire programme (median sessions attended 9). National PR baseline data included 47% female, 94% white British. Median values for the same variables included: age 70, FEV1% predicted 55, FEV1/FVC ratio 0.60, 6MWT 240m, CAT score 22, sessions attended 10. Conclusions: The Tai Chi group had had higher CAT scores and lower 6MWT results, however, median lung function results were similar compared with standard PR participants. The lower percentage of white British participants is representative of our local population. These data suggest people with more severe functional impairment, unable/unwilling to do standard PR, may consider and participate in Tai Chi as an alternative form of physical activity.

In countries with low tuberculosis (TB) incidence, TB is concentrated in vulnerable populations, including people living with the human immunodeficiency virus (PLHIV), who have a substantially greater risk of TB than people without HIV. We searched PubMed, EMBASE and Web of Science for studies evaluating the risk factors for latent tuberculous infection (LTBI) or active TB in PLHIV in countries with TB incidence 10 per 100 000 population. Due to the number of risk factors evaluated and heterogeneity in study designs, we present summary data and a narrative synthesis. We included 45 studies: 17 reported data on the risk factors for LTBI and 32 on active TB. Black, Asian or Hispanic ethnicity, birth or long-term residence in a country with high TB incidence, and HIV acquisition via injecting drug use (IDU) or heterosexual sex were strong predictors of both LTBI and active TB. History of contact, a greater degree of immunosuppression at diagnosis or higher viral load increased the TB risk. Early HIV diagnosis to allow timely initiation of antiretroviral therapy is essential for the prevention of TB in PLHIV. Screening and treating PLHIV for LTBI to reduce the risk of progression to active TB disease should also be considered to further reduce the burden of active TB in low TB incidence settings. Research to support the expansion of TB and HIV prevention and treatment globally is essential to eliminate TB in low-incidence settings.

Vulnerable populations, including homeless persons, high-risk drug and alcohol users, prison inmates and other marginalised populations, contribute a disproportionate burden of tuberculosis (TB) cases in low-incidence settings. Drivers of this disease burden include an increased risk of both TB transmission in congregate settings, and progression from infection to active disease. Late diagnosis and poor treatment completion further propagate the epidemic and fuel the acquisition of drug resistance. These groups are therefore a major priority for TB control programmes in low-incidence settings. Targeted strategies include active case finding (ACF) initiatives and interventions to improve treatment completion, both of which should be tailored to local populations. ACF usually deploys mobile X-ray unit screening, which allows sensitive, high-throughput screening with immediate availability of results. Such initiatives have been found to be effective and cost-effective, and associated with reductions in proxy measures of transmission in hard-to-reach groups. The addition of point-of-care molecular diagnostics and automated X-ray readers may further streamline the screening pathway. There is little evidence to support interventions to improve adherence among these risk groups. Such approaches include enhanced case management and directly observed treatment, while video-observed therapy (currently under evaluation) appears to be a promising tool for the future. Integrating outreach services to include both case detection and case-management interventions that share a resource infrastructure may allow cost-effectiveness to be maximised. Integrating screening and treatment for other diseases that are prevalent among targeted risk groups into TB outreach interventions may further improve cost-effectiveness. This article reviews the existing literature, and highlights priorities for further research.

Objectives: Tuberculosis (TB) is estimated to be the leading cause of HIV-related deaths globally. However, since HIV-associated TB frequently remains unascertained, we systematically reviewed autopsy studies to determine the true burden of TB at death. Methods: We systematically searched Medline and Embase databases (to end 2013) for literature reporting on health facility-based autopsy studies of HIV-infected adults and/or children in resource-limited settings. Using forest plots and random-effects meta-analysis, we summarized the TB prevalence found at autopsy and used meta-regression to explore variables associated with autopsy TB prevalence. Results: We included 36 eligible studies, reporting on 3237 autopsies. Autopsy TB prevalence was extremely heterogeneous (range 0–64.4%), but was markedly higher in adults [pooled prevalence 39.7%, 95% confidence interval (CI) 32.4–47.0%] compared to children (pooled prevalence 4.5%, 95% CI 1.7–7.4%). Post-mortem TB prevalence varied by world region, with pooled estimates in adults of 63.2% (95% CI 57.7–68.7%) in South Asia (n = 2 studies); 43.2% (95% CI 38.0–48.3) in sub-Saharan Africa (n = 9 studies); and 27.1% (95% CI 16.0–38.1%) in the Americas (n = 5 studies). Autopsy prevalence positively correlated with contemporary estimates of national TB prevalence. TB in adults was disseminated in 87.9% (82.2–93.7%) of cases and was considered the cause of death in 91.4% (95% CI 85.8–97.0%) of TB cases. Overall, TB was the cause of death in 37.2% (95% CI 25.7–48.7%) of adult HIV/AIDS-related deaths. TB remained undiagnosed at death in 45.8% (95% CI 32.6–59.1%) of TB cases. Conclusions: In resource-limited settings, TB accounts for approximately 40% of facility-based HIV/AIDS-related adult deaths. Almost half of this disease remains undiagnosed at the time of death. These findings highlight the critical need to improve the prevention, diagnosis and treatment of HIV-associated TB globally.

The role of Xpert(®) MTB/RIF for tuberculosis (TB) diagnosis remains to be clearly delineated in high-resource settings. At a London hospital, we evaluated a policy of selective assay use, with testing restricted to defined sub-groups of patients. Management was directly influenced in 30% of patients studied, including 'ruling-in' a TB diagnosis (leading to initiation of treatment for TB or for potential multidrug-resistant TB); negative assay results also helped support decisions for cessation of empirical anti-tuberculosis treatment or the safe initiation of other treatments such as immunosuppressant drugs. The benefits and pitfalls of this assay's use within high-resource settings are discussed.

Among a nationwide cohort of renal transplant recipients (n=30 433), TB incidence was highest in the first year post-transplant. Asian ethnicity and CMV seropositivity were independent risk factors for post-transplant TBhttp://bit.ly/2YSVGt2