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      Impact of sex and gender on post-COVID-19 syndrome, Switzerland, 2020

      research-article
      1 , * , 2 , 3 , * , 4 , 1 , 2 , 3 , 2 , 3 , 5 , 6 , 2 , 3 , 6 , 7 , 7 , 7 , 8 , 9 , 3 , 9 , 9 , 10 , 11 , 10 , 12 , 1 , 13 , 14 , 14 , 2 , 3 , 2 , 3 , 2 , 3 , 1 , 1 , 1 , 15 , 6 , 6 , 7 , 6 , 16 , 2 , 3 , 17 , 2 , 3 , 2 , 3 , 2 , 3 , 1 , 1 , 2 , 3 , 18 , 2 , 2 , 2 , 2 , 2 , 1 , 5 , 19 , 2 , 3
      Eurosurveillance
      European Centre for Disease Prevention and Control (ECDC)
      SARS-CoV-2, Gender, Sex, Women, Post-COVID-19, Long-COVID, Long-Haulers

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          Abstract

          Background

          Women are overrepresented among individuals with post-acute sequelae of SARS-CoV-2 infection (PASC). Biological (sex) as well as sociocultural (gender) differences between women and men might account for this imbalance, yet their impact on PASC is unknown.

          Aim

          We assessed the impact of sex and gender on PASC in a Swiss population.

          Method

          Our multicentre prospective cohort study included 2,856 (46% women, mean age 44.2 ± 16.8 years) outpatients and hospitalised patients with PCR-confirmed SARS-CoV-2 infection.

          Results

          Among those who remained outpatients during their first infection, women reported persisting symptoms more often than men (40.5% vs 25.5% of men; p < 0.001). This sex difference was absent in hospitalised patients. In a crude analysis, both female biological sex (RR = 1.59; 95% CI: 1.41–1.79; p < 0.001) and a score summarising gendered sociocultural variables (RR = 1.05; 95% CI: 1.03–1.07; p < 0.001) were significantly associated with PASC. Following multivariable adjustment, biological female sex (RR = 0.96; 95% CI: 0.74–1.25; p = 0.763) was outperformed by feminine gender-related factors such as a higher stress level (RR = 1.04; 95% CI: 1.01–1.06; p = 0.003), lower education (RR = 1.16; 95% CI: 1.03–1.30; p = 0.011), being female and living alone (RR = 1.91; 95% CI: 1.29–2.83; p = 0.001) or being male and earning the highest income in the household (RR = 0.76; 95% CI: 0.60–0.97; p = 0.030).

          Conclusion

          Specific sociocultural parameters that differ in prevalence between women and men, or imply a unique risk for women, are predictors of PASC and may explain, at least in part, the higher incidence of PASC in women. Once patients are hospitalised during acute infection, sex differences in PASC are no longer evident.

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          Most cited references24

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          6-month consequences of COVID-19 in patients discharged from hospital: a cohort study

          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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            Attributes and predictors of long COVID

            Reports of long-lasting coronavirus disease 2019 (COVID-19) symptoms, the so-called 'long COVID', are rising but little is known about prevalence, risk factors or whether it is possible to predict a protracted course early in the disease. We analyzed data from 4,182 incident cases of COVID-19 in which individuals self-reported their symptoms prospectively in the COVID Symptom Study app1. A total of 558 (13.3%) participants reported symptoms lasting ≥28 days, 189 (4.5%) for ≥8 weeks and 95 (2.3%) for ≥12 weeks. Long COVID was characterized by symptoms of fatigue, headache, dyspnea and anosmia and was more likely with increasing age and body mass index and female sex. Experiencing more than five symptoms during the first week of illness was associated with long COVID (odds ratio = 3.53 (2.76-4.50)). A simple model to distinguish between short COVID and long COVID at 7 days (total sample size, n = 2,149) showed an area under the curve of the receiver operating characteristic curve of 76%, with replication in an independent sample of 2,472 individuals who were positive for severe acute respiratory syndrome coronavirus 2. This model could be used to identify individuals at risk of long COVID for trials of prevention or treatment and to plan education and rehabilitation services.
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              Long COVID: major findings, mechanisms and recommendations

              Long COVID is an often debilitating illness that occurs in at least 10% of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections. More than 200 symptoms have been identified with impacts on multiple organ systems. At least 65 million individuals worldwide are estimated to have long COVID, with cases increasing daily. Biomedical research has made substantial progress in identifying various pathophysiological changes and risk factors and in characterizing the illness; further, similarities with other viral-onset illnesses such as myalgic encephalomyelitis/chronic fatigue syndrome and postural orthostatic tachycardia syndrome have laid the groundwork for research in the field. In this Review, we explore the current literature and highlight key findings, the overlap with other conditions, the variable onset of symptoms, long COVID in children and the impact of vaccinations. Although these key findings are critical to understanding long COVID, current diagnostic and treatment options are insufficient, and clinical trials must be prioritized that address leading hypotheses. Additionally, to strengthen long COVID research, future studies must account for biases and SARS-CoV-2 testing issues, build on viral-onset research, be inclusive of marginalized populations and meaningfully engage patients throughout the research process. Long COVID is an often debilitating illness of severe symptoms that can develop during or following COVID-19. In this Review, Davis, McCorkell, Vogel and Topol explore our knowledge of long COVID and highlight key findings, including potential mechanisms, the overlap with other conditions and potential treatments. They also discuss challenges and recommendations for long COVID research and care.
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                Author and article information

                Journal
                Euro Surveill
                Euro Surveill
                eurosurveillance
                Eurosurveillance
                European Centre for Disease Prevention and Control (ECDC)
                1025-496X
                1560-7917
                11 January 2024
                : 29
                : 2
                : 2300200
                Affiliations
                [1 ]Intensive Care Unit, University Hospital Basel, University of Basel, Basel, Switzerland
                [2 ]Department of Nuclear Medicine, University Hospital Zurich, University of Zurich, Zurich, Switzerland
                [3 ]Center for Molecular Cardiology, University of Zurich, Schlieren, Switzerland
                [4 ]Institute of Biometry and Clinical Epidemiology, Charité - Universitätsmedizin Berlin, Berlin, Germany
                [5 ]Department of Biostatistics at Epidemiology, Biostatistics and Prevention Institute, University of Zurich, Zurich, Switzerland
                [6 ]Institute of Intensive Care, University Hospital Zurich, University of Zurich, Zurich, Switzerland
                [7 ]Department of Infectious Diseases and Hospital Epidemiology, University Hospital Zurich, University of Zurich, Zurich, Switzerland
                [8 ]Department of Cardiology, University Hospital Zurich, Zurich, Switzerland
                [9 ]Department of Internal Medicine, Cantonal Hospital of Baden, Baden, Switzerland
                [10 ]Department of Cardiology, University Hospital Basel, Basel, Switzerland
                [11 ]Department of Cardiology and University Center of Cardiovascular Science, University Heart and Vascular Center Hamburg, Hamburg, Germany
                [12 ]Department of Biomedicine, University of Basel, Basel, Switzerland
                [13 ]Division of Infectious Diseases and Hospital Epidemiology, University of Basel, Basel, Switzerland
                [14 ]Department of Intensive Care Medicine, Inselspital Bern University Hospital, University of Bern, Bern, Switzerland
                [15 ]Department of Informatics, University Hospital Basel, Basel, Switzerland
                [16 ]Department of Quantitative Biomedicine, University of Zurich, Zurich, Switzerland
                [17 ]Division of Nuclear Medicine and Molecular Imaging, Massachusetts General Hospital, and Department of Radiology, Harvard Medical School, Boston, Massachusetts, United States
                [18 ]Department of Consultation-Liaison Psychiatry and Psychosomatic Medicine, University Hospital Zurich, University of Zurich, Zurich, Switzerland
                [19 ]Institute of Gender in Medicine (GiM), Charité - Universitätsmedizin Berlin, Berlin, Germany
                [* ]These authors contributed equally
                Author notes

                Correspondence: Catherine Gebhard ( Catherine.gebhard@ 123456usz.ch )

                Author information
                https://orcid.org/0000-0001-7240-5822
                Article
                2300200 2300200
                10.2807/1560-7917.ES.2024.29.2.2300200
                10785203
                38214079
                80afa135-8500-446c-869d-e7901767755d
                This article is copyright of the authors or their affiliated institutions, 2024.

                This is an open-access article distributed under the terms of the Creative Commons Attribution (CC BY 4.0) Licence. You may share and adapt the material, but must give appropriate credit to the source, provide a link to the licence, and indicate if changes were made.

                History
                : 03 April 2023
                : 04 October 2023
                Categories
                Research
                Custom metadata
                6

                sars-cov-2,gender,sex,women,post-covid-19, long-covid, long-haulers

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