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      Informing antimicrobial management in the context of COVID-19: understanding the longitudinal dynamics of C-reactive protein and procalcitonin

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          Abstract 

          Background

          To characterise the longitudinal dynamics of C-reactive protein (CRP) and Procalcitonin (PCT) in a cohort of hospitalised patients with COVID-19 and support antimicrobial decision-making.

          Methods

          Longitudinal CRP and PCT concentrations and trajectories of 237 hospitalised patients with COVID-19 were modelled. The dataset comprised of 2,021 data points for CRP and 284 points for PCT. Pairwise comparisons were performed between: (i) those with or without significant bacterial growth from cultures, and (ii) those who survived or died in hospital.

          Results

          CRP concentrations were higher over time in COVID-19 patients with positive microbiology (day 9: 236 vs 123 mg/L, p < 0.0001) and in those who died (day 8: 226 vs 152 mg/L, p < 0.0001) but only after day 7 of COVID-related symptom onset. Failure for CRP to reduce in the first week of hospital admission was associated with significantly higher odds of death. PCT concentrations were higher in patients with COVID-19 and positive microbiology or in those who died, although these differences were not statistically significant.

          Conclusions

          Both the absolute CRP concentration and the trajectory during the first week of hospital admission are important factors predicting microbiology culture positivity and outcome in patients hospitalised with COVID-19. Further work is needed to describe the role of PCT for co-infection. Understanding relationships of these biomarkers can support development of risk models and inform optimal antimicrobial strategies.

          Supplementary Information

          The online version contains supplementary material available at 10.1186/s12879-021-06621-7.

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          Most cited references18

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          Clinical course and risk factors for mortality of adult inpatients with COVID-19 in Wuhan, China: a retrospective cohort study

          Summary Background Since December, 2019, Wuhan, China, has experienced an outbreak of coronavirus disease 2019 (COVID-19), caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Epidemiological and clinical characteristics of patients with COVID-19 have been reported but risk factors for mortality and a detailed clinical course of illness, including viral shedding, have not been well described. Methods In this retrospective, multicentre cohort study, we included all adult inpatients (≥18 years old) with laboratory-confirmed COVID-19 from Jinyintan Hospital and Wuhan Pulmonary Hospital (Wuhan, China) who had been discharged or had died by Jan 31, 2020. Demographic, clinical, treatment, and laboratory data, including serial samples for viral RNA detection, were extracted from electronic medical records and compared between survivors and non-survivors. We used univariable and multivariable logistic regression methods to explore the risk factors associated with in-hospital death. Findings 191 patients (135 from Jinyintan Hospital and 56 from Wuhan Pulmonary Hospital) were included in this study, of whom 137 were discharged and 54 died in hospital. 91 (48%) patients had a comorbidity, with hypertension being the most common (58 [30%] patients), followed by diabetes (36 [19%] patients) and coronary heart disease (15 [8%] patients). Multivariable regression showed increasing odds of in-hospital death associated with older age (odds ratio 1·10, 95% CI 1·03–1·17, per year increase; p=0·0043), higher Sequential Organ Failure Assessment (SOFA) score (5·65, 2·61–12·23; p<0·0001), and d-dimer greater than 1 μg/mL (18·42, 2·64–128·55; p=0·0033) on admission. Median duration of viral shedding was 20·0 days (IQR 17·0–24·0) in survivors, but SARS-CoV-2 was detectable until death in non-survivors. The longest observed duration of viral shedding in survivors was 37 days. Interpretation The potential risk factors of older age, high SOFA score, and d-dimer greater than 1 μg/mL could help clinicians to identify patients with poor prognosis at an early stage. Prolonged viral shedding provides the rationale for a strategy of isolation of infected patients and optimal antiviral interventions in the future. Funding Chinese Academy of Medical Sciences Innovation Fund for Medical Sciences; National Science Grant for Distinguished Young Scholars; National Key Research and Development Program of China; The Beijing Science and Technology Project; and Major Projects of National Science and Technology on New Drug Creation and Development.
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            Clinical Characteristics of 138 Hospitalized Patients With 2019 Novel Coronavirus–Infected Pneumonia in Wuhan, China

            In December 2019, novel coronavirus (2019-nCoV)-infected pneumonia (NCIP) occurred in Wuhan, China. The number of cases has increased rapidly but information on the clinical characteristics of affected patients is limited.
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              Co-infections in people with COVID-19: a systematic review and meta-analysis

              Highlights • SARS-CoV-2, the cause of COVID19 disease, has spread globally since late 2019 • Bacterial coinfections associated with mortality in previous influenza pandemics • Proportion of COVID19 patients with bacterial coinfection less than in flu pandemics • Higher proportion of critically-ill with bacterial coinfections than in mixed setting • Bacterial co-pathogen profiles different to those in influenza co-infections • Fungal coinfection diagnosis difficult so high level suspicion in critically-ill
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                Author and article information

                Contributors
                d.ming@imperial.ac.uk
                Journal
                BMC Infect Dis
                BMC Infect Dis
                BMC Infectious Diseases
                BioMed Central (London )
                1471-2334
                8 September 2021
                8 September 2021
                2021
                : 21
                : 932
                Affiliations
                [1 ]GRID grid.7445.2, ISNI 0000 0001 2113 8111, Centre for Antimicrobial Optimisation, Hammersmith Hospital, , Imperial College London, ; Du Cane Road, London, W12 0NN UK
                [2 ]GRID grid.7445.2, ISNI 0000 0001 2113 8111, National Institute for Health Research Health Protection Research Unit in Healthcare Associated Infections and Antimicrobial Resistance, , Imperial College London, ; Hammersmith Campus, Du Cane Road, London, W12 0NN UK
                [3 ]GRID grid.4305.2, ISNI 0000 0004 1936 7988, School of Informatics, , University of Edinburgh, ; Scotland, UK
                [4 ]GRID grid.4305.2, ISNI 0000 0004 1936 7988, School of Biological Science, , University of Edinburgh, ; Scotland, UK
                [5 ]GRID grid.411760.5, ISNI 0000 0001 1378 7891, Department of Neurology, , University Hospital of Würzburg, ; 97080 Würzburg, Germany
                [6 ]GRID grid.7445.2, ISNI 0000 0001 2113 8111, Department of Mathematics, , Imperial College London, ; London, UK
                Author information
                http://orcid.org/0000-0003-3125-6378
                Article
                6621
                10.1186/s12879-021-06621-7
                8424157
                34496795
                040843d3-cec7-4155-8f4d-2b9ab6ca181b
                © The Author(s) 2021

                Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

                History
                : 3 November 2020
                : 26 August 2021
                Funding
                Funded by: Department of Health and Social Care
                Funded by: Medical Research Foundation.
                Funded by: National Institute for Health Research Health Protection Research Unit
                Categories
                Research Article
                Custom metadata
                © The Author(s) 2021

                Infectious disease & Microbiology
                bacterial co-infection,covid-19,biomarkers,antimicrobial stewardship,risk stratification,clinical decision-support

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