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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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Comparison of the Effects of Fasting Glucose, Hemoglobin A1c, and Triglyceride-Glucose Index on Cardiovascular Events in Type 2 Diabetes Mellitus.
Su, WY, Chen, SC, Huang, YT, Huang, JC, Wu, PY, Hsu, WH, Lee, MY
Nutrients. 2019;11(11)
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Cardiovascular disease generally refers to the narrowing or blockage of the arteries of the heart, which can lead to a heart attack or stroke and is the major cause of death in individuals with type 2 diabetes. Identifying individuals with type 2 diabetes who are at high risk of developing cardiovascular disease could ensure better management of these patients. This retrospective observational study of 3524 individuals with type 2 diabetes aimed to investigate if the amount of sugar found in the blood over the last few months, known as haemaglobin A1c (HbA1c) can predict cardiovascular disease in individuals with type 2 diabetes. In addition, the study looked at the triglyceride-glucose (TyG) index and its relationship to cardiovascular disease outcomes. The results showed that several factors were associated with cardiovascular disease, however of main note was that the TyG index and the amount of sugar in the blood following a fast were associated with increased cardiovascular events in individuals with type 2 diabetes, but HbA1c was not. It was concluded that TyG and the blood sugar level could be used to allow early identification and management of type 2 diabetics to prevent cardiovascular events. Clinicians could use this study to justify the use of measuring the TyG index and blood sugar levels as a predictor for cardiovascular events to ensure that patients are managed not only for type 2 diabetes but also to reduce their risk of cardiovascular events in the future.
Abstract
The triglyceride-glucose (TyG) index has been correlated with insulin resistance. We aim to investigate the role of the TyG index on cardiovascular (CV) events in type 2 diabetes mellitus and compare the roles of fasting glucose, hemoglobin A1c, and the TyG index in predicting CV events. This retrospective study enrolled 3524 patients with type 2 diabetes from the Kaohsiung Medical University Research Database in 2009 in this longitudinal study and followed them until 2015. The TyG index was calculated as log (fasting triglyceride level (mg/dL) × fasting glucose level (mg/dL)/2). CV events included myocardial infarction, unstable angina, stroke, hospitalization for coronary artery disease, peripheral artery disease, and CV-related death. The association between variables and CV events was assessed using a multivariable stepwise Cox proportional hazard analysis. Two hundred and fifteen CV events (6.1%) were recorded during a follow-up period of 5.93 years. The multivariable stepwise analysis showed that high fasting glucose (HR, 1.007; p < 0.001) and a high TyG index (HR, 1.521; p = 0.004) but not hemoglobin A1c or triglycerides were associated with a higher rate of CV events. Adding fasting glucose and the TyG index to the basic model improved the predictive ability of progression to a CV event (p < 0.001 and p = 0.018, respectively), over that of hemoglobin A1c (p = 0.084) and triglyceride (p = 0.221). Fasting glucose and the TyG index are useful parameters and stronger predictive factors than hemoglobin A1c and triglyceride for CV events and may offer an additional prognostic benefit in patients with type 2 diabetes.