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      Deep Phenotyping of Neurologic Postacute Sequelae of SARS-CoV-2 Infection

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          Abstract

          Background and Objectives

          SARS-CoV-2 infection has been associated with a syndrome of long-term neurologic sequelae that is poorly characterized. We aimed to describe and characterize in-depth features of neurologic postacute sequelae of SARS-CoV-2 infection (neuro-PASC).

          Methods

          Between October 2020 and April 2021, 12 participants were seen at the NIH Clinical Center under an observational study to characterize ongoing neurologic abnormalities after SARS-CoV-2 infection. Autonomic function and CSF immunophenotypic analysis were compared with healthy volunteers (HVs) without prior SARS-CoV-2 infection tested using the same methodology.

          Results

          Participants were mostly female (83%), with a mean age of 45 ± 11 years. The median time of evaluation was 9 months after COVID-19 (range 3–12 months), and most (11/12, 92%) had a history of only a mild infection. The most common neuro-PASC symptoms were cognitive difficulties and fatigue, and there was evidence for mild cognitive impairment in half of the patients (MoCA score <26). The majority (83%) had a very disabling disease, with Karnofsky Performance Status ≤80. Smell testing demonstrated different degrees of microsmia in 8 participants (66%). Brain MRI scans were normal, except 1 patient with bilateral olfactory bulb hypoplasia that was likely congenital. CSF analysis showed evidence of unique intrathecal oligoclonal bands in 3 cases (25%). Immunophenotyping of CSF compared with HVs showed that patients with neuro-PASC had lower frequencies of effector memory phenotype both for CD4 + T cells ( p < 0.0001) and for CD8 + T cells ( p = 0.002), an increased frequency of antibody-secreting B cells ( p = 0.009), and increased frequency of cells expressing immune checkpoint molecules. On autonomic testing, there was evidence for decreased baroreflex-cardiovagal gain ( p = 0.009) and an increased peripheral resistance during tilt-table testing ( p < 0.0001) compared with HVs, without excessive plasma catecholamine responses.

          Discussion

          CSF immune dysregulation and neurocirculatory abnormalities after SARS-CoV-2 infection in the setting of disabling neuro-PASC call for further evaluation to confirm these changes and explore immunomodulatory treatments in the context of clinical trials.

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          An interactive web-based dashboard to track COVID-19 in real time

          Ensheng Dong, Hongru Du, Lauren Gardner (2020)
          In December, 2019, a local outbreak of pneumonia of initially unknown cause was detected in Wuhan (Hubei, China), and was quickly determined to be caused by a novel coronavirus, 1 namely severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The outbreak has since spread to every province of mainland China as well as 27 other countries and regions, with more than 70 000 confirmed cases as of Feb 17, 2020. 2 In response to this ongoing public health emergency, we developed an online interactive dashboard, hosted by the Center for Systems Science and Engineering (CSSE) at Johns Hopkins University, Baltimore, MD, USA, to visualise and track reported cases of coronavirus disease 2019 (COVID-19) in real time. The dashboard, first shared publicly on Jan 22, illustrates the location and number of confirmed COVID-19 cases, deaths, and recoveries for all affected countries. It was developed to provide researchers, public health authorities, and the general public with a user-friendly tool to track the outbreak as it unfolds. All data collected and displayed are made freely available, initially through Google Sheets and now through a GitHub repository, along with the feature layers of the dashboard, which are now included in the Esri Living Atlas. The dashboard reports cases at the province level in China; at the city level in the USA, Australia, and Canada; and at the country level otherwise. During Jan 22–31, all data collection and processing were done manually, and updates were typically done twice a day, morning and night (US Eastern Time). As the outbreak evolved, the manual reporting process became unsustainable; therefore, on Feb 1, we adopted a semi-automated living data stream strategy. Our primary data source is DXY, an online platform run by members of the Chinese medical community, which aggregates local media and government reports to provide cumulative totals of COVID-19 cases in near real time at the province level in China and at the country level otherwise. Every 15 min, the cumulative case counts are updated from DXY for all provinces in China and for other affected countries and regions. For countries and regions outside mainland China (including Hong Kong, Macau, and Taiwan), we found DXY cumulative case counts to frequently lag behind other sources; we therefore manually update these case numbers throughout the day when new cases are identified. To identify new cases, we monitor various Twitter feeds, online news services, and direct communication sent through the dashboard. Before manually updating the dashboard, we confirm the case numbers with regional and local health departments, including the respective centres for disease control and prevention (CDC) of China, Taiwan, and Europe, the Hong Kong Department of Health, the Macau Government, and WHO, as well as city-level and state-level health authorities. For city-level case reports in the USA, Australia, and Canada, which we began reporting on Feb 1, we rely on the US CDC, the government of Canada, the Australian Government Department of Health, and various state or territory health authorities. All manual updates (for countries and regions outside mainland China) are coordinated by a team at Johns Hopkins University. The case data reported on the dashboard aligns with the daily Chinese CDC 3 and WHO situation reports 2 for within and outside of mainland China, respectively (figure ). Furthermore, the dashboard is particularly effective at capturing the timing of the first reported case of COVID-19 in new countries or regions (appendix). With the exception of Australia, Hong Kong, and Italy, the CSSE at Johns Hopkins University has reported newly infected countries ahead of WHO, with Hong Kong and Italy reported within hours of the corresponding WHO situation report. Figure Comparison of COVID-19 case reporting from different sources Daily cumulative case numbers (starting Jan 22, 2020) reported by the Johns Hopkins University Center for Systems Science and Engineering (CSSE), WHO situation reports, and the Chinese Center for Disease Control and Prevention (Chinese CDC) for within (A) and outside (B) mainland China. Given the popularity and impact of the dashboard to date, we plan to continue hosting and managing the tool throughout the entirety of the COVID-19 outbreak and to build out its capabilities to establish a standing tool to monitor and report on future outbreaks. We believe our efforts are crucial to help inform modelling efforts and control measures during the earliest stages of the outbreak.
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            6-month consequences of COVID-19 in patients discharged from hospital: a cohort study

            Chaolin Huang, Lixue Huang, Yeming Wang … (2021)
            Background The long-term health consequences of COVID-19 remain largely unclear. The aim of this study was to describe the long-term health consequences of patients with COVID-19 who have been discharged from hospital and investigate the associated risk factors, in particular disease severity. Methods We did an ambidirectional cohort study of patients with confirmed COVID-19 who had been discharged from Jin Yin-tan Hospital (Wuhan, China) between Jan 7, 2020, and May 29, 2020. Patients who died before follow-up, patients for whom follow-up would be difficult because of psychotic disorders, dementia, or re-admission to hospital, those who were unable to move freely due to concomitant osteoarthropathy or immobile before or after discharge due to diseases such as stroke or pulmonary embolism, those who declined to participate, those who could not be contacted, and those living outside of Wuhan or in nursing or welfare homes were all excluded. All patients were interviewed with a series of questionnaires for evaluation of symptoms and health-related quality of life, underwent physical examinations and a 6-min walking test, and received blood tests. A stratified sampling procedure was used to sample patients according to their highest seven-category scale during their hospital stay as 3, 4, and 5–6, to receive pulmonary function test, high resolution CT of the chest, and ultrasonography. Enrolled patients who had participated in the Lopinavir Trial for Suppression of SARS-CoV-2 in China received severe acute respiratory syndrome coronavirus 2 antibody tests. Multivariable adjusted linear or logistic regression models were used to evaluate the association between disease severity and long-term health consequences. Findings In total, 1733 of 2469 discharged patients with COVID-19 were enrolled after 736 were excluded. Patients had a median age of 57·0 (IQR 47·0–65·0) years and 897 (52%) were men. The follow-up study was done from June 16, to Sept 3, 2020, and the median follow-up time after symptom onset was 186·0 (175·0–199·0) days. Fatigue or muscle weakness (63%, 1038 of 1655) and sleep difficulties (26%, 437 of 1655) were the most common symptoms. Anxiety or depression was reported among 23% (367 of 1617) of patients. The proportions of median 6-min walking distance less than the lower limit of the normal range were 24% for those at severity scale 3, 22% for severity scale 4, and 29% for severity scale 5–6. The corresponding proportions of patients with diffusion impairment were 22% for severity scale 3, 29% for scale 4, and 56% for scale 5–6, and median CT scores were 3·0 (IQR 2·0–5·0) for severity scale 3, 4·0 (3·0–5·0) for scale 4, and 5·0 (4·0–6·0) for scale 5–6. After multivariable adjustment, patients showed an odds ratio (OR) 1·61 (95% CI 0·80–3·25) for scale 4 versus scale 3 and 4·60 (1·85–11·48) for scale 5–6 versus scale 3 for diffusion impairment; OR 0·88 (0·66–1·17) for scale 4 versus scale 3 and OR 1·77 (1·05–2·97) for scale 5–6 versus scale 3 for anxiety or depression, and OR 0·74 (0·58–0·96) for scale 4 versus scale 3 and 2·69 (1·46–4·96) for scale 5–6 versus scale 3 for fatigue or muscle weakness. Of 94 patients with blood antibodies tested at follow-up, the seropositivity (96·2% vs 58·5%) and median titres (19·0 vs 10·0) of the neutralising antibodies were significantly lower compared with at the acute phase. 107 of 822 participants without acute kidney injury and with estimated glomerular filtration rate (eGFR) 90 mL/min per 1·73 m2 or more at acute phase had eGFR less than 90 mL/min per 1·73 m2 at follow-up. Interpretation At 6 months after acute infection, COVID-19 survivors were mainly troubled with fatigue or muscle weakness, sleep difficulties, and anxiety or depression. Patients who were more severely ill during their hospital stay had more severe impaired pulmonary diffusion capacities and abnormal chest imaging manifestations, and are the main target population for intervention of long-term recovery. Funding National Natural Science Foundation of China, Chinese Academy of Medical Sciences Innovation Fund for Medical Sciences, National Key Research and Development Program of China, Major Projects of National Science and Technology on New Drug Creation and Development of Pulmonary Tuberculosis, and Peking Union Medical College Foundation.
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              Persistent Symptoms in Patients After Acute COVID-19

              Angelo Carfì, Roberto Bernabei, Francesco Landi (2020)
              This case series describes COVID-19 symptoms persisting a mean of 60 days after onset among Italian patients previously discharged from COVID-19 hospitalization.
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                Author and article information

                Journal
                Journal ID (nlm-ta): Neurol Neuroimmunol Neuroinflamm
                Journal ID (iso-abbrev): Neurol Neuroimmunol Neuroinflamm
                Journal ID (hwp): nnn
                Journal ID (publisher-id): NEURIMMINFL
                Title: Neurology® Neuroimmunology & Neuroinflammation
                Publisher: Lippincott Williams & Wilkins (Hagerstown, MD )
                ISSN (Electronic): 2332-7812
                Publication date Collection: July 2023
                Publication date (Electronic): 5 May 2023
                Publication date PMC-release: 5 May 2023
                Volume: 10
                Issue: 4
                Electronic Location Identifier: e200097
                Affiliations
                From the National Institute of Neurological Disorders and Stroke (Y.M., Y.E.-A., A.J.V., C.C.M., G.N., L.B.R., B.W., S.J., D.S.G., B.R.S., A.N.), National Institutes of Health, Bethesda, MD; Sackler Faculty of Medicine (Y.M.), Tel-Aviv University, Israel; Center for Infectious Disease Imaging (D.A.H.), Radiology and Imaging Sciences, Clinical Center, National Institutes of Health; and Vaccine Immunology Program (S.R.N., S.E.O.C., R.C., B.C.L., A.B.M.), Vaccine Research Center, National Institutes of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD.
                Author notes
                Correspondence Dr. Nath natha@ 123456ninds.nih.gov

                Go to Neurology.org/NN for full disclosures. Funding information is provided at the end of the article.

                The Article Processing Charge was funded by the NIH.

                Submitted and externally peer reviewed. The handling editor was Editor Josep O. Dalmau, MD, PhD, FAAN.

                Author information
                https://orcid.org/0000-0003-2311-6623
                https://orcid.org/0000-0002-7102-9703
                https://orcid.org/0000-0001-7406-7871
                https://orcid.org/0000-0003-3725-615X
                https://orcid.org/0000-0001-6305-7723
                https://orcid.org/0000-0001-9850-5944
                https://orcid.org/0000-0003-0927-5855
                Article
                Publisher ID: NXI-2023-000002
                DOI: 10.1212/NXI.0000000000200097
                PMC ID: 10162706
                PubMed ID: 37147136
                SO-VID: b270644b-3ceb-4f6d-b9b5-e71f645c708a
                Copyright © Written work prepared by employees of the Federal Government as part of their official duties is, under the U.S. Copyright Act, a “work of the United States Government” for which copyright protection under Title 17 of the United States Code is not available. As such, copyright does not extend to the contributions of employees of the Federal Government.
                License:

                 

                History
                Date received : 29 August 2022
                Date accepted : 04 January 2023
                Categories
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                Subject: 131
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                Subject: 145
                Subject: 23
                Subject: Research Article
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