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      Long Term Neuropsychiatric Consequences In COVID-19 Survivors: Cognitive Impairment and Inflammatory underpinnings Fifteen Months After Discharge

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          Abstract

          Background

          Emerging evidence shows that cognitive dysfunction may occur following coronavirus disease 19 (COVID-19) infection which is one of the most common symptoms reported in researches of “Long COVID”. Several inflammatory markers are known to be elevated in COVID-19 survivors and the relationship between long-term inflammation changes and cognitive function remains unknown.

          Methods

          We assessed cognitive function and neuropsychiatric symptoms of 66 COVID-19 survivors and 79 healthy controls (HCs) matched with sex, age, and education level using a digital, gamified cognitive function evaluation tool and questionnaires at 15 months after discharge. Venous blood samples were collected to measure cytokine levels. We performed correlation analyses and multiple linear regression analysis to identify the factors potentially related to cognitive function.

          Results

          The COVID-19 survivors performed less well on the Trails (p = 0.047) than the HCs, but most of them did not report subjective neuropsychiatric symptoms. Intensive care unit experience (β = -2.247, p < 0.0001) and self-perceived disease severity (β = -1.522, p = 0.007) were positively correlated, whereas years of education (β = 0.098, p = 0.013) was negatively associated with the performance on the Trails. Moreover, the abnormally elevated TNF-α levels (r = -0.19, p = 0.040) were negatively correlated with performance on the Trails in COVID-19 group.

          Conclusion

          Our findings suggest that COVID-19 survivors show long-term cognitive impairment in executive function, even at 15 months after discharge. Serum TNF-α levels may be an underlying mechanism of long-term cognitive impairment in patients recovering from COVID-19.

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          Most cited references54

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          Clinical features of patients infected with 2019 novel coronavirus in Wuhan, China

          Chaolin Huang, Yeming Wang, Xingwang Li … (2020)
          Summary Background A recent cluster of pneumonia cases in Wuhan, China, was caused by a novel betacoronavirus, the 2019 novel coronavirus (2019-nCoV). We report the epidemiological, clinical, laboratory, and radiological characteristics and treatment and clinical outcomes of these patients. Methods All patients with suspected 2019-nCoV were admitted to a designated hospital in Wuhan. We prospectively collected and analysed data on patients with laboratory-confirmed 2019-nCoV infection by real-time RT-PCR and next-generation sequencing. Data were obtained with standardised data collection forms shared by WHO and the International Severe Acute Respiratory and Emerging Infection Consortium from electronic medical records. Researchers also directly communicated with patients or their families to ascertain epidemiological and symptom data. Outcomes were also compared between patients who had been admitted to the intensive care unit (ICU) and those who had not. Findings By Jan 2, 2020, 41 admitted hospital patients had been identified as having laboratory-confirmed 2019-nCoV infection. Most of the infected patients were men (30 [73%] of 41); less than half had underlying diseases (13 [32%]), including diabetes (eight [20%]), hypertension (six [15%]), and cardiovascular disease (six [15%]). Median age was 49·0 years (IQR 41·0–58·0). 27 (66%) of 41 patients had been exposed to Huanan seafood market. One family cluster was found. Common symptoms at onset of illness were fever (40 [98%] of 41 patients), cough (31 [76%]), and myalgia or fatigue (18 [44%]); less common symptoms were sputum production (11 [28%] of 39), headache (three [8%] of 38), haemoptysis (two [5%] of 39), and diarrhoea (one [3%] of 38). Dyspnoea developed in 22 (55%) of 40 patients (median time from illness onset to dyspnoea 8·0 days [IQR 5·0–13·0]). 26 (63%) of 41 patients had lymphopenia. All 41 patients had pneumonia with abnormal findings on chest CT. Complications included acute respiratory distress syndrome (12 [29%]), RNAaemia (six [15%]), acute cardiac injury (five [12%]) and secondary infection (four [10%]). 13 (32%) patients were admitted to an ICU and six (15%) died. Compared with non-ICU patients, ICU patients had higher plasma levels of IL2, IL7, IL10, GSCF, IP10, MCP1, MIP1A, and TNFα. Interpretation The 2019-nCoV infection caused clusters of severe respiratory illness similar to severe acute respiratory syndrome coronavirus and was associated with ICU admission and high mortality. Major gaps in our knowledge of the origin, epidemiology, duration of human transmission, and clinical spectrum of disease need fulfilment by future studies. Funding Ministry of Science and Technology, Chinese Academy of Medical Sciences, National Natural Science Foundation of China, and Beijing Municipal Science and Technology Commission.
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            COVID-19: consider cytokine storm syndromes and immunosuppression

            Puja Mehta, Daniel McAuley, Michael Brown … (2020)
            As of March 12, 2020, coronavirus disease 2019 (COVID-19) has been confirmed in 125 048 people worldwide, carrying a mortality of approximately 3·7%, 1 compared with a mortality rate of less than 1% from influenza. There is an urgent need for effective treatment. Current focus has been on the development of novel therapeutics, including antivirals and vaccines. Accumulating evidence suggests that a subgroup of patients with severe COVID-19 might have a cytokine storm syndrome. We recommend identification and treatment of hyperinflammation using existing, approved therapies with proven safety profiles to address the immediate need to reduce the rising mortality. Current management of COVID-19 is supportive, and respiratory failure from acute respiratory distress syndrome (ARDS) is the leading cause of mortality. 2 Secondary haemophagocytic lymphohistiocytosis (sHLH) is an under-recognised, hyperinflammatory syndrome characterised by a fulminant and fatal hypercytokinaemia with multiorgan failure. In adults, sHLH is most commonly triggered by viral infections 3 and occurs in 3·7–4·3% of sepsis cases. 4 Cardinal features of sHLH include unremitting fever, cytopenias, and hyperferritinaemia; pulmonary involvement (including ARDS) occurs in approximately 50% of patients. 5 A cytokine profile resembling sHLH is associated with COVID-19 disease severity, characterised by increased interleukin (IL)-2, IL-7, granulocyte-colony stimulating factor, interferon-γ inducible protein 10, monocyte chemoattractant protein 1, macrophage inflammatory protein 1-α, and tumour necrosis factor-α. 6 Predictors of fatality from a recent retrospective, multicentre study of 150 confirmed COVID-19 cases in Wuhan, China, included elevated ferritin (mean 1297·6 ng/ml in non-survivors vs 614·0 ng/ml in survivors; p 39·4°C 49 Organomegaly None 0 Hepatomegaly or splenomegaly 23 Hepatomegaly and splenomegaly 38 Number of cytopenias * One lineage 0 Two lineages 24 Three lineages 34 Triglycerides (mmol/L) 4·0 mmol/L 64 Fibrinogen (g/L) >2·5 g/L 0 ≤2·5 g/L 30 Ferritin ng/ml 6000 ng/ml 50 Serum aspartate aminotransferase <30 IU/L 0 ≥30 IU/L 19 Haemophagocytosis on bone marrow aspirate No 0 Yes 35 Known immunosuppression † No 0 Yes 18 The Hscore 11 generates a probability for the presence of secondary HLH. HScores greater than 169 are 93% sensitive and 86% specific for HLH. Note that bone marrow haemophagocytosis is not mandatory for a diagnosis of HLH. HScores can be calculated using an online HScore calculator. 11 HLH=haemophagocytic lymphohistiocytosis. * Defined as either haemoglobin concentration of 9·2 g/dL or less (≤5·71 mmol/L), a white blood cell count of 5000 white blood cells per mm3 or less, or platelet count of 110 000 platelets per mm3 or less, or all of these criteria combined. † HIV positive or receiving longterm immunosuppressive therapy (ie, glucocorticoids, cyclosporine, azathioprine).
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              Effect size estimates: current use, calculations, and interpretation.

              Catherine O Fritz, Peter Morris, Jennifer J. Richler (2012)
              The Publication Manual of the American Psychological Association (American Psychological Association, 2001, American Psychological Association, 2010) calls for the reporting of effect sizes and their confidence intervals. Estimates of effect size are useful for determining the practical or theoretical importance of an effect, the relative contributions of factors, and the power of an analysis. We surveyed articles published in 2009 and 2010 in the Journal of Experimental Psychology: General, noting the statistical analyses reported and the associated reporting of effect size estimates. Effect sizes were reported for fewer than half of the analyses; no article reported a confidence interval for an effect size. The most often reported analysis was analysis of variance, and almost half of these reports were not accompanied by effect sizes. Partial η2 was the most commonly reported effect size estimate for analysis of variance. For t tests, 2/3 of the articles did not report an associated effect size estimate; Cohen's d was the most often reported. We provide a straightforward guide to understanding, selecting, calculating, and interpreting effect sizes for many types of data and to methods for calculating effect size confidence intervals and power analysis.
              Article 0 comments Cited 777 times – based on 0 reviews     Review now
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                Author and article information

                Journal
                Journal ID (nlm-ta): Asian J Psychiatr
                Journal ID (iso-abbrev): Asian J Psychiatr
                Title: Asian Journal of Psychiatry
                Publisher: Published by Elsevier B.V.
                ISSN (Print): 1876-2018
                ISSN (Electronic): 1876-2026
                Publication date PMC-release: 15 December 2022
                Publication date (Electronic): 15 December 2022
                Electronic Location Identifier: 103409
                Affiliations
                [a ]Mental Health Center and Psychiatric Laboratory, West China Hospital of Sichuan University, Chengdu, China
                [b ]West China Biomedical Big Data Center, West China Hospital, Sichuan University, Chengdu, China
                [c ]Med-X Center for Informatics, Sichuan University, Chengdu, China
                [d ]Huaxi Brain Research Center, West China Hospital of Sichuan University, Chengdu, China
                Author notes
                [* ]Correspondence to: Mental Health Center, West China Hospital of Sichuan University, Dianxin South Road No.28, Chengdu 610041, China
                [1]

                These authors contributed equally: Danmei He and Minlan Yuan.

                Article
                Publisher Item ID: S1876-2018(22)00407-5 Publisher ID: 103409
                DOI: 10.1016/j.ajp.2022.103409
                PMC ID: 9751007
                PubMed ID: 36549172
                SO-VID: 202e151f-1f55-4201-be31-de94749f73de
                Copyright © © 2022 Published by Elsevier B.V.
                License:

                Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active.

                History
                Date received : 8 October 2022
                Date revision received : 8 December 2022
                Date accepted : 12 December 2022
                Categories
                Subject: Article

                Keywords: covid-19,cognitive function,systematic inflammation,long-covid
                Data availability:
                Keywords: covid-19, cognitive function, systematic inflammation, long-covid

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