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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, Martin Wiegand was funded by the NIHR Cambridge Biomedical Research Centre (BRC-1215-20014). Victoria L. Keevil was funded by the MRC/NIHR Clinical Academic Research Partnership Grant (CARP) [grant code MR/T023902/1]. Vince Taylor was funded by the Cancer Research UK Cambridge Centre. Effrossyni Gkrania-Klotsas was supported by the NIHR Clinical Research Network (CRN) Greenshoots Award. Brian D. M. Tom and Robert J. B. Goudie were funded by the UKRI Medical Research Council (MRC) [programme code MC_UU_00002/2] and supported by the NIHR Cambridge Biomedical Research Centre (BRC-1215-20014).

The 4C Deterioration model was developed and validated on data collected in UK hospitals until August 26, 2020, but has not yet been validated in the presence of SARS-CoV-2 variants and novel treatment regimens that have emerged subsequently. In this first validation study of the 4C Deterioration model on patients admitted between August 27, 2020 and April 16, 2021 we found, despite a slightly overestimation of risk, that the discrimination (area under the curve 0.75, 95% CI 0.71-0.78) and calibration of the model remained consistent with the development study, strengthening the evidence for adopting this model into clinical practice.

Background A substantial portion of people with COVID-19 subsequently experience lasting symptoms including fatigue, shortness of breath, and neurological complaints such as cognitive dysfunction many months after acute infection. Emerging evidence suggests that this condition, commonly referred to as long COVID but also known as post-acute sequelae of SARS-CoV-2 infection (PASC) or post-COVID-19 condition, could become a significant global health burden. Main text While the number of studies investigating the post-COVID-19 condition is increasing, there is no agreement on how this new disease should be defined and diagnosed in clinical practice and what relevant outcomes to measure. There is an urgent need to optimise and standardise outcome measures for this important patient group both for clinical services and for research and to allow comparing and pooling of data. Conclusions A Core Outcome Set for post-COVID-19 condition should be developed in the shortest time frame possible, for improvement in data quality, harmonisation, and comparability between different geographical locations. We call for a global initiative, involving all relevant partners, including, but not limited to, healthcare professionals, researchers, methodologists, patients, and caregivers. We urge coordinated actions aiming to develop a Core Outcome Set (COS) for post-COVID-19 condition in both the adult and paediatric populations.

This is the twelfth version (eleventh update) of the living guideline, replacing earlier versions (available as data supplements). New recommendations will be published as updates to this guideline.What is the role of drugs in the treatment of patients with covid-19?The evidence base for therapeutics for covid-19 is evolving with numerous randomised controlled trials (RCTs) recently completed and under way. The emerging SARS-CoV-2 variants (such as omicron) and subvariants are also changing the role of therapeutics. This update provides updated recommendations for remdesivir, addresses the use of combination therapy with corticosteroids, interleukin-6 (IL-6) receptor blockers, and janus kinase (JAK) inhibitors in patients with severe or critical covid-19, and modifies previous recommendations for the neutralising monoclonal antibodies sotrovimab and casirivimab-imdevimab in patients with non-severe covid-19.• Remdesivir: a conditional recommendation for its use in patients with severe covid-19; and a conditional recommendation against its use in patients with critical covid-19. • Concomitant use of IL-6 receptor blockers (tocilizumab or sarilumab) and the JAK inhibitor baricitinib: these drugs may now be combined, in addition to corticosteroids, in patients with severe or critical covid-19. • Sotrovimab and casirivimab-imdevimab: strong recommendations against their use in patients with covid-19, replacing the previous conditional recommendations for their use.When moving from new evidence to updated recommendations, the Guideline Development Group (GDG) considered a combination of evidence assessing relative benefits and harms, values and preferences, and feasibility issues. For remdesivir, new trial data were added to a previous subgroup analysis and provided sufficiently trustworthy evidence to demonstrate benefits in patients with severe covid-19, but not critical covid-19. The GDG considered benefits of remdesivir to be modest and of moderate certainty for key outcomes such as mortality and mechanical ventilation, resulting in a conditional recommendation. For baricitinib, the GDG considered clinical trial evidence (RECOVERY) demonstrating reduced risk of death in patients already receiving corticosteroids and IL-6 receptor blockers. The GDG acknowledged that the clinical trials were not representative of the world population and that the risk-benefit balance may be less advantageous, particularly in patients who are immunosuppressed at higher risk of opportunistic infections (such as serious fungal, viral, or bacteria), those already deteriorating where less aggressive or stepwise addition of immunosuppressive medications may be preferred, and in areas where certain pathogens such as HIV or tuberculosis, are of concern. The panel anticipated that there would be situations where clinicians may opt for less aggressive immunosuppressive therapy or to combine medications in a stepwise fashion in patients who are deteriorating. The decision to combine the medications will depend on their availability, and the treating clinician's perception of the risk-benefit balance associated with combination immunosuppressive therapy, particularly in patient populations at risk of opportunistic infections who may have been under-represented in clinical trials. When making a strong recommendation against the use of monoclonal antibodies for patients with covid-19, the GDG considered in vitro neutralisation data demonstrating that sotrovimab and casirivimab-imdevimab evaluated in clinical trials have meaningfully reduced neutralisation activity of the currently circulating variants of SARS-CoV-2 and their subvariants. There was consensus among the panel that the absence of in vitro neutralisation activity strongly suggests absence of clinical effectiveness of these monoclonal antibodies. However, there was also consensus regarding the need for clinical trial evidence in order to confirm clinical efficacy of new monoclonal antibodies that reliably neutralise the circulating strains in vitro. Whether emerging new variants and subvariants might be susceptible to sotrovimab, casirivimab-imdevimab, or other anti-SARS-CoV-2 monoclonal antibodies cannot be predicted.• Recommended for patients with severe or critical covid-19—strong recommendations for systemic corticosteroids; IL-6 receptor blockers (tocilizumab or sarilumab) in combination with corticosteroids; and baricitinib as an alternative to IL-6 receptor blockers, in combination with corticosteroids. • Recommended for patients with non-severe covid-19 at highest risk of hospitalisation—a strong recommendation for nirmatrelvir/ritonavir; conditional recommendations for molnupiravir and remdesivir. • Not recommended for patients with non-severe covid-19—a conditional recommendation against systemic corticosteroids; a strong recommendation against convalescent plasma; a recommendation against fluvoxamine, except in the context of a clinical trial; and a strong recommendation against colchicine. • Not recommended for patients with non-severe covid-19 at low risk of hospitalisation—a conditional recommendation against nirmatrelvir/ritonavir. • Not recommended for patients with severe or critical covid-19—a recommendation against convalescent plasma except in the context of a clinical trial; and a conditional recommendation against the JAK inhibitors ruxolitinib and tofacitinib. • Not recommended, regardless of covid-19 disease severity—a strong recommendations against hydroxychloroquine and against lopinavir/ritonavir; and a recommendation against ivermectin except in the context of a clinical trial.This living guideline from the World Health Organization (WHO) incorporates new evidence to dynamically update recommendations for covid-19 therapeutics. The GDG typically evaluates a therapy when the WHO judges sufficient evidence is available to make a recommendation. While the GDG takes an individual patient perspective in making recommendations, it also considers resource implications, acceptability, feasibility, equity, and human rights. This guideline was developed according to standards and methods for trustworthy guidelines, making use of an innovative process to achieve efficiency in dynamic updating of recommendations. The methods are aligned with the WHO Handbook for Guideline Development and according to a pre-approved protocol (planning proposal) by the Guideline Review Committee (GRC). A box at the end of the article outlines key methodological aspects of the guideline process. MAGIC Evidence Ecosystem Foundation provides methodological support, including the coordination of living systematic reviews with network meta-analyses to inform the recommendations. The full version of the guideline is available online in MAGICapp and in PDF, with a summary version here in The BMJ. These formats should facilitate adaptation, which is strongly encouraged by WHO to contextualise recommendations in a healthcare system to maximise impact.Recommendations on anticoagulation are planned for the next update to this guideline.

Introduction: We describe the clinical features and inpatient trajectories of older adults hospitalized with COVID-19 and explore relationships with frailty. Methods: This retrospective observational study included older adults admitted as an emergency to a University Hospital who were diagnosed with COVID-19. Patient characteristics and hospital outcomes, primarily inpatient death or death within 14 days of discharge, were described for the whole cohort and by frailty status. Associations with mortality were further evaluated using Cox Proportional Hazards Regression (Hazard Ratio (HR), 95% Confidence Interval). Results: 214 patients (94 women) were included of whom 142 (66.4%) were frail with a median Clinical Frailty Scale (CFS) score of 6. Frail compared to nonfrail patients were more likely to present with atypical symptoms including new or worsening confusion (45.1% vs. 20.8%, p &lt, 0.001) and were more likely to die (66% vs. 16%, p = 0.001). Older age, being male, presenting with high illness acuity and high frailty were independent predictors of death and a dose–response association between frailty and mortality was observed (CFS 1–4: reference, CFS 5–6: HR 1.78, 95% CI 0.90, 3.53, CFS 7–8: HR 2.57, 95% CI 1.26, 5.24). Conclusions: Clinicians should have a low threshold for testing for COVID-19 in older and frail patients during periods of community viral transmission, and diagnosis should prompt early advanced care planning.

Background: While numerous point-of-admission disease severity models for COVID-19 have been proposed, disease stratification that accounts for changes in a patient’s condition while in hospital is urgently needed to facilitate patient management and resource allocation. Methods: We developed a prognostic model for 48-hour in-hospital mortality using 473 consecutive patients with COVID-19 presenting to a UK hospital between March 1 and September 12, 2020; and temporally validated using data on 405 patients presenting between September 13, 2020 and January 3, 2021.The primary outcome was all-cause in-hospital mortality. We additionally considered the competing risks of discharge from hospital and transfer to a tertiary Intensive Care Unit for extracorporeal membrane oxygenation. We adopted a landmarking approach to dynamic prediction that accounts for competing risks and informative missingness, and selected predictors using penalised regression. The model estimates, at any point during a hospital visit, the probability of in-hospital mortality during the next 48 hours. Results: Our final model includes age, Clinical Frailty Scale score, heart rate, respiratory rate, SpO2/FiO2 ratio, white cell count, presence of acidosis (pH < 7.35) and Interleukin-6. Internal validation achieved an AUROC of 0.90 (95% CI 0.87–0.93) and temporal validation gave an AUROC of 0.91 (95% CI 0.88-0.95). Interpretation: Our model uniquely incorporates both static risk factors (e.g. 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. External validation outside the study hospital will be required before adoption. Funding: NIHR Cambridge Biomedical Research Centre, UKRI Medical Research Council Declaration of Interest: None to declare. Ethical Approval: The study was approved by a UK Health Research Authority ethics committee (20/WM/0125). Patient consent was waived because the de-identified data presented here were collected during routine clinical practice; there was no requirement for informed consent.

Clinical question What is the role of drugs in preventing covid-19? Why does this matter? There is widespread interest in whether drug interventions can be used for the prevention of covid-19, but there is uncertainty about which drugs, if any, are effective. Recommendations The second version of this living guideline reiterates the previous strong recommendation against the use of hydroxychloroquine and includes a new conditional recommendation against the use of tixagevimab-cilgavimab in individuals who do not have covid-19. How this guideline was created This living guideline is from the World Health Organization (WHO) and provides up to date covid-19 guidance to inform policy and practice worldwide. Magic Evidence Ecosystem Foundation (MAGIC) provides methodological support. A living systematic review with network analysis informs the recommendations. An international guideline development group (GDG) of content experts, clinicians, patients, an ethicist and methodologists produces recommendations following standards for trustworthy guideline development using the Grading of Recommendations Assessment, Development and Evaluation (GRADE) approach. Understanding the recommendations The living network meta-analysis informing this guideline included 12 trials (8379 participants) comparing hydroxychloroquine to standard care/placebo, and one trial (5197 participants) comparing tixagevimab-cilgavimab to standard care/placebo. When moving from evidence to the continued strong recommendation against the use of hydroxychloroquine, the GDG emphasised additional evidence suggesting no or little effect on mortality and hospital admission, and an increased risk of adverse effects. For the new conditional recommendation against the use of tixagevimab-cilgavimab, the GDG emphasised in vitro evidence reducing the applicability of available trial data. While trial results demonstrated modest reduction in the occurrence of laboratory confirmed symptomatic covid-19, lack of in vitro neutralisation of new SARS-CoV-2 sub-lineages was considered to have rendered these results obsolete. Updates This is a living guideline. New recommendations will be published in this article and signposted by update notices to this guideline. Readers note This is the second version of the living guideline for drugs to prevent covid-19. It complements the WHO living guideline on drugs to treat covid-19 and living guidance regarding covid-19 related clinical management. When citing this article, please consider adding the update number and date of access for clarity.

Background: A comprehensive description of the clinical characteristics, inpatient trajectory and relationship with frailty of older inpatients admitted with COVID-19 is essential in the management of older adults during the COVID-19 pandemic. The aim of this study was to describe the clinical features and inpatient trajectory of older inpatients with confirmed COVID -19.Methods: This was a retrospective observational study of hospitalised older adults. Subjects include unscheduled medical admissions of older inpatients to a University Hospital with laboratory and clinically confirmed COVID-19. The primary outcome was death during the inpatient stay or within 14 days of discharge after a maximum follow up time of 45 days. The characteristics of the cohort were described in detail as a whole and by frailty status.Results: 214 patients were included in this study with a mean length of stay of 11 days (Range 6 to 18 days), of whom 140 (65.4%) patients were discharged and 74 (34.6%) patients died in hospital. 142 (66.4%) patients were frail with median Clinical Frailty Scale (CFS) score of 6. Frail patients were more likely to present with atypical symptoms including new or worsening confusion compared to non-frail patients (20.8% vs 45.1%, pConclusions: Older adult inpatients with COVID-19 infection are likely to present with atypical symptoms, experience delirium and have a high mortality, especially if they are also living with frailty. Clinicians should have a low threshold for testing for COVID-19 in older and frail patients presenting to hospital as an emergency during periods when there is community transmission of COVID-19 and, when diagnosed, this should prompt early advanced care planning with the patient and family.

Delirium incidence in intensive care unit (ICU) patients is high and associated with poor outcome. Identification of high-risk patients may facilitate its prevention.To develop and validate a model based on data available at ICU admission to predict delirium development during a patient's complete ICU stay and to determine the predictive value of this model in relation to the time of delirium development.Prospective cohort study in 13 ICUs from seven countries. Multiple logistic regression analysis was used to develop the early prediction (E-PRE-DELIRIC) model on data of the first two-thirds and validated on data of the last one-third of the patients from every participating ICU.In total, 2914 patients were included. Delirium incidence was 23.6%. The E-PRE-DELIRIC model consists of nine predictors assessed at ICU admission: age, history of cognitive impairment, history of alcohol abuse, blood urea nitrogen, admission category, urgent admission, mean arterial blood pressure, use of corticosteroids, and respiratory failure. The area under the receiver operating characteristic curve (AUROC) was 0.76 [95% confidence interval (CI) 0.73-0.77] in the development dataset and 0.75 (95% CI 0.71-0.79) in the validation dataset. The model was well calibrated. AUROC increased from 0.70 (95% CI 0.67-0.74), for delirium that developed2 days, to 0.81 (95% CI 0.78-0.84), for delirium that developed6 days.Patients' delirium risk for the complete ICU length of stay can be predicted at admission using the E-PRE-DELIRIC model, allowing early preventive interventions aimed to reduce incidence and severity of ICU delirium.

Sepsis is a major reason for intensive care unit (ICU) admission, also in resource–poor settings. ICUs in low– and middle–income countries (LMICs) face many challenges that could affect patient outcome. The aim of this review is to describe differences between resource–poor and resource–rich settings regarding the epidemiology, pathophysiology, economics and research aspects of sepsis. We restricted this manuscript to the ICU setting even knowing that many sepsis patients in LMICs are treated outside an ICU. Although many bacterial pathogens causing sepsis in LMICs are similar to those in high–income countries, resistance patterns to antimicrobial drugs can be very different; in addition, causes of sepsis in LMICs often include tropical diseases in which direct damaging effects of pathogens and their products can sometimes be more important than the response of the host. There are substantial and persisting differences in ICU capacities around the world; not surprisingly the lowest capacities are found in LMICs, but with important heterogeneity within individual LMICs. Although many aspects of sepsis management developed in rich countries are applicable in LMICs, implementation requires strong consideration of cost implications and the important differences in resources. Addressing both disease–specific and setting–specific factors is important to improve performance of ICUs in LMICs. Although critical care for severe sepsis is likely cost–effective in LMIC setting, more detailed evaluation at both at a macro– and micro–economy level is necessary. Sepsis management in resource–limited settings is a largely unexplored frontier with important opportunities for research, training, and other initiatives for improvement.

Contains fulltext : 177987.pdf (Publisher’s version ) (Open Access) BACKGROUND: Antimicrobial Stewardship Programs (ASPs) have been promoted to optimize antimicrobial usage and patient outcomes, and to reduce the emergence of antimicrobial-resistant organisms. However, the best strategies for an ASP are not definitively established and are likely to vary based on local culture, policy, and routine clinical practice, and probably limited resources in middle-income countries. The aim of this study is to evaluate structures and resources of antimicrobial stewardship teams (ASTs) in surgical departments from different regions of the world. METHODS: A cross-sectional web-based survey was conducted in 2016 on 173 physicians who participated in the AGORA (Antimicrobials: A Global Alliance for Optimizing their Rational Use in Intra-Abdominal Infections) project and on 658 international experts in the fields of ASPs, infection control, and infections in surgery. RESULTS: The response rate was 19.4%. One hundred fifty-six (98.7%) participants stated their hospital had a multidisciplinary AST. The median number of physicians working inside the team was five [interquartile range 4-6]. An infectious disease specialist, a microbiologist and an infection control specialist were, respectively, present in 80.1, 76.3, and 67.9% of the ASTs. A surgeon was a component in 59.0% of cases and was significantly more likely to be present in university hospitals (89.5%, p < 0.05) compared to community teaching (83.3%) and community hospitals (66.7%). Protocols for pre-operative prophylaxis and for antimicrobial treatment of surgical infections were respectively implemented in 96.2 and 82.3% of the hospitals. The majority of the surgical departments implemented both persuasive and restrictive interventions (72.8%). The most common types of interventions in surgical departments were dissemination of educational materials (62.5%), expert approval (61.0%), audit and feedback (55.1%), educational outreach (53.7%), and compulsory order forms (51.5%). CONCLUSION: The survey showed a heterogeneous organization of ASPs worldwide, demonstrating the necessity of a multidisciplinary and collaborative approach in the battle against antimicrobial resistance in surgical infections, and the importance of educational efforts towards this goal.

Background The increasing incidence of carbapenemase-producing Enterobacteriaceae (CPE) is a global health concern, as treatment options are extremely limited. The prevalence of CPE in UK hospitals is unknown, as national screening guidelines only recommend screening in patients considered to be at high-risk of CPE. Patients in intensive care units (ICU) are at high-risk of healthcare-associated infections caused by multidrug-resistant organisms (MDRO). Methods We conducted a six-month prospective surveillance study to determine the prevalence of MDRO in a UK teaching hospital ICU. Between June and December 2016, all adult patients admitted to ICU were screened for MDRO on admission, on discharge, and weekly during their ICU stay. Surveillance samples included stool or rectal swabs, urine, sputum or tracheal aspirates, and wound swabs (if wounds were present). Isolates were characterized phenotypically before undergoing whole-genome sequencing (WGS), epidemiological, and phylogenetic analyses. Results During the first week of the study we identified stool carriage of a multidrug-resistant Klebsiella pneumoniae strain in two patients neither of whom had recognized risk factors for CPE. Both isolates were resistant to all antibiotics tested, apart from colistin, and were PCR-positive for the blaNDM-1 gene. Enhanced surveillance by the infection control team identified four additional patients in several wards who had stool carriage (n = 3) or bloodstream infection (n = 1) with a blaNDM-1K. pneumoniae isolate. Epidemiological links were identified between these six patients. Five months later, a second outbreak of multidrug-resistant K. pneumoniae was detected, involving stool carriage by four patients on two different wards. Environmental screening identified environmental contamination with multidrug-resistant K. pneumoniae on one ward. DNA sequence analysis confirmed that a novel blaNDM-1K. pneumoniaelineage (ST78) was responsible for both outbreaks in the hospital. Conclusion We identified two unsuspected blaNDM-1K. pneumoniae outbreaks in patients with no recognized risk factors for CPE. This highlights the importance of prospective surveillance for MDRO in high-risk settings, such as ICUs, and supports the use of rapid WGS to support outbreak investigations in real-time. Disclosures All authors: No reported disclosures.