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6-month neurological and psychiatric outcomes in 236 379 survivors of COVID-19: a retrospective cohort study using electronic health records.
Taquet, M, Geddes, JR, Husain, M, Luciano, S, Harrison, PJ
The lancet. Psychiatry. 2021;8(5):416-427
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Recent literature shows that COVID-19 survivors might be at an increased risk of neurological and psychiatric disorders. The aim of this study was to investigate the incidence of neurological and psychiatric diagnoses in survivors in the 6 months after documented clinical COVID-19 infection. This study is a retrospective cohort study with the primary cohort comprised of 236,379 patients diagnosed with COVID-19 and two propensity-score-matched control cohorts. The primary cohort was divided into one of the four subgroups. Results indicate that the severity of COVID-19 had a clear effect on subsequent neurological diagnoses. In fact, COVID-19 was associated with an increased risk of neurological and psychiatric outcomes. However, the incidences and hazard ratio of these were greater in patients who had required hospitalisation, and particularly those who required ITU admission or developed encephalopathy, even after extensive propensity score matching for other factors. Authors conclude that COVID-19 is followed by significant rates of neurological and psychiatric diagnoses over the subsequent 6 months.
Abstract
BACKGROUND Neurological and psychiatric sequelae of COVID-19 have been reported, but more data are needed to adequately assess the effects of COVID-19 on brain health. We aimed to provide robust estimates of incidence rates and relative risks of neurological and psychiatric diagnoses in patients in the 6 months following a COVID-19 diagnosis. METHODS For this retrospective cohort study and time-to-event analysis, we used data obtained from the TriNetX electronic health records network (with over 81 million patients). Our primary cohort comprised patients who had a COVID-19 diagnosis; one matched control cohort included patients diagnosed with influenza, and the other matched control cohort included patients diagnosed with any respiratory tract infection including influenza in the same period. Patients with a diagnosis of COVID-19 or a positive test for SARS-CoV-2 were excluded from the control cohorts. All cohorts included patients older than 10 years who had an index event on or after Jan 20, 2020, and who were still alive on Dec 13, 2020. We estimated the incidence of 14 neurological and psychiatric outcomes in the 6 months after a confirmed diagnosis of COVID-19: intracranial haemorrhage; ischaemic stroke; parkinsonism; Guillain-Barré syndrome; nerve, nerve root, and plexus disorders; myoneural junction and muscle disease; encephalitis; dementia; psychotic, mood, and anxiety disorders (grouped and separately); substance use disorder; and insomnia. Using a Cox model, we compared incidences with those in propensity score-matched cohorts of patients with influenza or other respiratory tract infections. We investigated how these estimates were affected by COVID-19 severity, as proxied by hospitalisation, intensive therapy unit (ITU) admission, and encephalopathy (delirium and related disorders). We assessed the robustness of the differences in outcomes between cohorts by repeating the analysis in different scenarios. To provide benchmarking for the incidence and risk of neurological and psychiatric sequelae, we compared our primary cohort with four cohorts of patients diagnosed in the same period with additional index events: skin infection, urolithiasis, fracture of a large bone, and pulmonary embolism. FINDINGS Among 236 379 patients diagnosed with COVID-19, the estimated incidence of a neurological or psychiatric diagnosis in the following 6 months was 33·62% (95% CI 33·17-34·07), with 12·84% (12·36-13·33) receiving their first such diagnosis. For patients who had been admitted to an ITU, the estimated incidence of a diagnosis was 46·42% (44·78-48·09) and for a first diagnosis was 25·79% (23·50-28·25). Regarding individual diagnoses of the study outcomes, the whole COVID-19 cohort had estimated incidences of 0·56% (0·50-0·63) for intracranial haemorrhage, 2·10% (1·97-2·23) for ischaemic stroke, 0·11% (0·08-0·14) for parkinsonism, 0·67% (0·59-0·75) for dementia, 17·39% (17·04-17·74) for anxiety disorder, and 1·40% (1·30-1·51) for psychotic disorder, among others. In the group with ITU admission, estimated incidences were 2·66% (2·24-3·16) for intracranial haemorrhage, 6·92% (6·17-7·76) for ischaemic stroke, 0·26% (0·15-0·45) for parkinsonism, 1·74% (1·31-2·30) for dementia, 19·15% (17·90-20·48) for anxiety disorder, and 2·77% (2·31-3·33) for psychotic disorder. Most diagnostic categories were more common in patients who had COVID-19 than in those who had influenza (hazard ratio [HR] 1·44, 95% CI 1·40-1·47, for any diagnosis; 1·78, 1·68-1·89, for any first diagnosis) and those who had other respiratory tract infections (1·16, 1·14-1·17, for any diagnosis; 1·32, 1·27-1·36, for any first diagnosis). As with incidences, HRs were higher in patients who had more severe COVID-19 (eg, those admitted to ITU compared with those who were not: 1·58, 1·50-1·67, for any diagnosis; 2·87, 2·45-3·35, for any first diagnosis). Results were robust to various sensitivity analyses and benchmarking against the four additional index health events. INTERPRETATION Our study provides evidence for substantial neurological and psychiatric morbidity in the 6 months after COVID-19 infection. Risks were greatest in, but not limited to, patients who had severe COVID-19. This information could help in service planning and identification of research priorities. Complementary study designs, including prospective cohorts, are needed to corroborate and explain these findings. FUNDING National Institute for Health Research (NIHR) Oxford Health Biomedical Research Centre.
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Greater risk of severe COVID-19 in Black, Asian and Minority Ethnic populations is not explained by cardiometabolic, socioeconomic or behavioural factors, or by 25(OH)-vitamin D status: study of 1326 cases from the UK Biobank.
Raisi-Estabragh, Z, McCracken, C, Bethell, MS, Cooper, J, Cooper, C, Caulfield, MJ, Munroe, PB, Harvey, NC, Petersen, SE
Journal of public health (Oxford, England). 2020;42(3):451-460
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The coronavirus disease 2019 (COVID-19) pandemic has to date resulted in over 6 million cases. Growing reports highlight men and Black, Asian and Minority Ethnic (BAME) cohorts as at higher risk of adverse COVID-19 outcomes. The aim of this study was to investigate whether differential patterns of COVID-19 incidence and severity, by sex and ethnicity, might be explained by cardiometabolic, socio-economic, lifestyle and behavioural exposures. This study is a prospective cohort study of over half a million men and women from across the UK. Results showed that male sex, BAME ethnicity, higher body mass index and greater household size were associated with significantly greater odds of a positive result. However, the sex and ethnicity differential pattern of COVID-19 is not adequately explained by variations in cardiometabolic factors, 25(OH)-vitamin D levels, socio-economic or behavioural factors. Authors conclude that investigation of alternative biological and genetic susceptibilities as well as more comprehensive assessment of the complex economic, social and behavioural differences should be prioritised.
Abstract
BACKGROUND We examined whether the greater severity of coronavirus disease 2019 (COVID-19) amongst men and Black, Asian and Minority Ethnic (BAME) individuals is explained by cardiometabolic, socio-economic or behavioural factors. METHODS We studied 4510 UK Biobank participants tested for COVID-19 (positive, n = 1326). Multivariate logistic regression models including age, sex and ethnicity were used to test whether addition of (1) cardiometabolic factors [diabetes, hypertension, high cholesterol, prior myocardial infarction, smoking and body mass index (BMI)]; (2) 25(OH)-vitamin D; (3) poor diet; (4) Townsend deprivation score; (5) housing (home type, overcrowding) or (6) behavioural factors (sociability, risk taking) attenuated sex/ethnicity associations with COVID-19 status. RESULTS There was over-representation of men and BAME ethnicities in the COVID-19 positive group. BAME individuals had, on average, poorer cardiometabolic profile, lower 25(OH)-vitamin D, greater material deprivation, and were more likely to live in larger households and in flats/apartments. Male sex, BAME ethnicity, higher BMI, higher Townsend deprivation score and household overcrowding were independently associated with significantly greater odds of COVID-19. The pattern of association was consistent for men and women; cardiometabolic, socio-demographic and behavioural factors did not attenuate sex/ethnicity associations. CONCLUSIONS In this study, sex and ethnicity differential pattern of COVID-19 was not adequately explained by variations in cardiometabolic factors, 25(OH)-vitamin D levels or socio-economic factors. Factors which underlie ethnic differences in COVID-19 may not be easily captured, and so investigation of alternative biological and genetic susceptibilities as well as more comprehensive assessment of the complex economic, social and behavioural differences should be prioritised.
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Brain-Behavior-Immune Interaction: Serum Cytokines and Growth Factors in Patients with Eating Disorders at Extremes of the Body Mass Index (BMI) Spectrum.
Caroleo, M, Carbone, EA, Greco, M, Corigliano, DM, Arcidiacono, B, Fazia, G, Rania, M, Aloi, M, Gallelli, L, Segura-Garcia, C, et al
Nutrients. 2019;11(9)
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Eating disorders such as anorexia, binge eating and night-time eating cause great fluctuations in body mass and have also been shown to alter the immune system, and more specifically markers of inflammation called cytokines. In this observational study of 90 patients with known eating disorders, the researchers tried to identify how much BMI, ‘underweightness’ and malnutrition influenced the body’s pro-inflammatory response and upset the normal immune response. They found that many inflammatory cytokines were elevated in the blood samples taken, a likely response to the conditions of stress in the body. These cytokines are known to interact with the nervous system and were also influenced by other common symptoms such as depression. They were able to group the differences in cytokines for anorexia nervosa, binge-eating disorder, post-dinner eating, night-eating, sweet-eating and fasting. These markers of dysfunctional eating behaviours may help form part of a therapeutic approach to treating eating disorders based on supporting the immune response and reducing inflammation to stabilise metabolic processes. Future studies in a larger population of patients is necessary to determine the relevance of these findings.
Abstract
Alterations of the immune system are known in eating disorders (EDs), however the importance of cytokine balance in this context has not been clarified. We compared cytokines and growth factors at opposite ends of BMI ranges, in 90 patients classified in relation to BMI, depressive and EDs comorbidities. Serum concentrations of interleukin (IL)-1α, IL-1β, IL-2, IL-4, IL-6, IL-8, IL-10, interferon-gamma (IFN-γ), tumor necrosis factor-alpha (TNF-α), monocyte chemoattractant protein-1 (MCP-1), vascular endothelial growth factor (VEGF), and epidermal growth factor (EGF) were determined by a biochip analyzer (Randox Labs). Differences were calculated through ANOVA. Possible predictors of higher cytokine levels were evaluated through regression analysis. IL-1α, IL-10, EGF, and IFN-γ were altered individuals with anorexia nervosa (AN) and binge eating disorder (BED). Night-eating was associated with IL-8 and EGF levels, IL-10 concentrations with post-dinner eating and negatively with sweet-eating, long fasting with higher IFN-γ levels. IL-2 increase was not linked to EDs, but to the interaction of depression and BMI. Altogether, for the first time, IL-1α, IL-10, EGF, and IFN-γ were shown to differ between AN and HCs, and between AN and individuals with obesity with or without BED. Only IL-2 was influenced by depression. Dysfunctional eating behaviors predicted abnormal concentrations of IL-10, EGF, IL-8 and IFN-γ.