ABSTRACT
By September, 2022, more than 600 million cases of SARS-CoV-2 infection have been reported globally, resulting in over 6.5 million deaths. COVID-19 mortality risk estimators are often, however, developed with small unrepresentative samples and with methodological limitations. It is highly important to develop predictive tools for pulmonary embolism (PE) in COVID-19 patients as one of the most severe preventable complications of COVID-19. Using a dataset of more than 800,000 COVID-19 patients from an international cohort, we propose a cost-sensitive gradient-boosted machine learning model that predicts occurrence of PE and death at admission. Logistic regression, Cox proportional hazards models, and Shapley values were used to identify key predictors for PE and death. Our prediction model had a test AUROC of 75.9% and 74.2%, and sensitivities of 67.5% and 72.7% for PE and all-cause mortality respectively on a highly diverse and held-out test set. The PE prediction model was also evaluated on patients in UK and Spain separately with test results of 74.5% AUROC, 63.5% sensitivity and 78.9% AUROC, 95.7% sensitivity. Age, sex, region of admission, comorbidities (chronic cardiac and pulmonary disease, dementia, diabetes, hypertension, cancer, obesity, smoking), and symptoms (any, confusion, chest pain, fatigue, headache, fever, muscle or joint pain, shortness of breath) were the most important clinical predictors at admission. Our machine learning model developed from an international cohort can serve to better regulate hospital risk prioritisation of at-risk patients.
Subject(s)
Pulmonary Embolism , Dementia , Lung Diseases , Headache , Myalgia , Dyspnea , Chest Pain , Diabetes Mellitus , Fever , Neoplasms , Obesity , Death , Hypertension , COVID-19 , Fatigue , ConfusionABSTRACT
Background: Using a large dataset, we evaluated prevalence and severity of alterations in liver enzymes in COVID-19 and association with patient-centred outcomes. Methods: We included hospitalized patients with confirmed or suspected SARS-CoV-2 infection from the International Severe Acute Respiratory and emerging Infection Consortium (ISARIC) database. Key exposure was baseline liver enzymes (AST, ALT, bilirubin). Patients were assigned Liver Injury Classification score based on 3 components of enzymes at admission: Normal; Stage I) Liver injury: any component between 1-3x upper limit of normal (ULN); Stage II) Severe liver injury: any component >= 3x ULN. Outcomes were hospital mortality, utilization of selected resources, complications, and durations of hospital and ICU stay. Analyses used logistic regression with associations expressed as adjusted odds ratios (OR) with 95% confidence intervals (CI). Results: Of 17,531 included patients, 46.2% (8099) and 8.2% (1430) of patients had stage 1 and 2 liver injury respectively. Compared to normal, stages 1 and 2 were associated with higher odds of mortality (OR 1.53 [1.37-1.71]; OR 2.50 [2.10-2.96]), ICU admission (OR 1.63 [1.48-1.79]; OR 1.90 [1.62-2.23]) and invasive mechanical ventilation (OR 1.43 [1.27-1.70]; OR 1.95 (1.55-2.45).Stages 1 and 2 were also associated with higher odds of developing sepsis (OR 1.38 [1.27-1.50]; OR 1.46 [1.25-1.70]), acute kidney injury (OR 1.13 [1.00-1.27]; OR 1.59 [1.32-1.91]), and acute respiratory distress syndrome (OR 1.38 [1.22-1.55]; OR 1.80 [1.49-2.17]). Conclusions: Liver enzyme abnormalities are common among COVID-19 patients and associated with worse outcomes.
Subject(s)
COVID-19 , Respiratory Tract Infections , Chemical and Drug Induced Liver InjuryABSTRACT
Introduction: Case definitions are used to guide clinical practice, surveillance, and research protocols. However, how they identify COVID-19-hospitalised patients is not fully understood. We analysed the proportion of hospitalised patients with laboratory-confirmed COVID-19, in the ISARIC prospective cohort study database, meeting widely used case definitions. Methods: Patients were assessed using the CDC, ECDC, WHO, and UKHSA case definitions by age, region, and time. Case fatality ratios (CFR) and symptoms of those who did and who did not meet the case definitions were evaluated. Patients with incomplete data and non-laboratory-confirmed test-result were excluded. Results: 263,218 of the patients (42%) in the ISARIC database were included. Most patients (90.4%) were from Europe and Central Asia. The proportions of patients meeting the case definitions were 56.8% (WHO), 74.4% (UKHSA), 81.6% (ECDC), and 82.3% (CDC). For each case definition, patients at the extremes of age distribution met the criteria less frequently than those aged 30 to 70 years; geographical and time variations were also observed. Estimated CFRs were similar for the patients that met the case definitions. However, when more patients did not meet the case definition, the CFR increased. Conclusions: The performance of case definitions might be different in different regions and may change over time. Similarly concerning is the fact that older patients often did not meet case definitions. While epidemiologists must balance their analytics with field applicability, ongoing revision of case definitions is necessary to improve patient care through early diagnosis and limit potential nosocomial spread.
Subject(s)
COVID-19ABSTRACT
BackgroundThe long-term sequelae of coronavirus disease 2019 (Covid-19) in children remain poorly characterised. This study aimed to assess long-term outcomes in children previously hospitalised with Covid-19 and associated risk factors. MethodsThis is a prospective cohort study of children ([≤]18 years old) admitted with confirmed Covid-19 to Z.A. Bashlyaeva Childrens Municipal Clinical Hospital in Moscow, Russia. Children admitted to the hospital during the first wave of the pandemic, between April 2, 2020 and August 26, 2020, were included. Telephone interview using the International Severe Acute Respiratory and emerging Infection Consortium (ISARIC) Covid-19 Health and Wellbeing paediatric follow up survey. Persistent symptoms (>5 months) were further categorised by system(s) involved. FindingsOverall, 518 of 853 (61%) of eligible children were available for the follow-up assessment and included in the study. Median age was 10.4 years (IQR, 3-15.2) and 270 (52.1%) were girls; median follow-up since hospital discharge was 256 (223-271) days. At the time of the follow-up interview 126 (24.3%) participants reported persistent symptoms among which fatigue (53, 10.7%), sleep disturbance (36, 6.9%,) and sensory problems (29, 5.6%) were the most common. Multiple symptoms were experienced by 44 (8.4%) participants. Risk factors for persistent symptoms were: age "6-11 years" (odds ratio 2.74 (95% confidence interval 1.37 to 5.75) and "12-18 years" (2.68, 1.41 to 5.4), and a history of allergic diseases (1.67, 1.04 to 2.67). InterpretationA quarter of children experienced persistent symptoms months after hospitalization with acute covid-19 infection, with almost one in ten experiencing multi-system involvement. Older age and allergic diseases were associated with higher risk of persistent symptoms at follow-up. Our findings highlight the need for replication and further investigation of potential mechanisms as well as clinical support to improve long term outcomes in children. FundingNone. O_TEXTBOXResearch in contextO_ST_ABSEvidence before this studyC_ST_ABSEvidence suggests that Covid-19 may result in short- and long-term consequences to health. Studies in children and adolescents are limited and available evidence is scarce. We searched Embase for publications from inception to April, 25, 2021, using the following phrases or combinations of phrases "post-covid condition" or "post-covid syndrome" or "covid sequalae" or "post-acute covid" or "long covid" or "long hauler" with "pediatric*" or "paediatric*" or "child*" or "infant*" or "newborn*" or "toddler*" or "neonate*" or "neonatal" or "adolescent*" or "teen*". We found small case series and small cohort studies looking at Covid-19 consequences in children. No large cohort studies of previously hospitalised children, assessing symptom duration, categorisation or attempting multivariable analyses to identify independent risk factors for long Covid development were identified. Added value of this studyTo our knowledge, this is the largest cohort study with the longest follow-up since hospital discharge of previously hospitalised children. We found that even months after discharge from the hospital, approximately a quarter of children experience persistent symptoms with one in ten having multi-system involvement. Older age and allergic diseases are associated with Covid-19 consequences. Parents of some children report emotional and behavioural changes in their children after Covid-19. Implications of all the available evidenceOur findings highlight the need for continued global research of Covid-19 consequences in the paediatric population. Older children admitted to the hospital should be carefully monitored upon discharge. Large, controlled studies aiming to identify risk groups and potential intervention strategies are required to fill knowledge gaps. C_TEXTBOX
Subject(s)
COVID-19ABSTRACT
Structured Abstract Objectives: The long-term consequences of severe Covid-19 requiring hospital admission are not well characterised. The objective of this study was to establish the long-term effects of Covid-19 following hospitalisation and the impact these may have on patient reported outcome measures. Design: A multicentre, prospective cohort study with at least 3 months follow-up of participants admitted to hospital between 5th February 2020 and 5th October 2020. Setting: 31 hospitals in the United Kingdom. Participants: 327 hospitalised participants discharged alive from hospital with confirmed/high likelihood SARS-CoV-2 infection. Main outcome measures and comparisons: The primary outcome was self-reported recovery at least ninety days after initial Covid-19 symptom onset. Secondary outcomes included new symptoms, new or increased disability (Washington group short scale), breathlessness (MRC Dyspnoea scale) and quality of life (EQ5D-5L). We compared these outcome measures across age, comorbidity status and in-hospital Covid-19 severity to identify groups at highest risk of developing long-term difficulties. Multilevel logistic and linear regression models were built to adjust for the effects of patient and centre level risk factors on these outcomes. Results: In total 53.7% (443/824) contacted participants responded, yielding 73.8% (327/443) responses with follow-up of 90 days or more from symptom onset. The median time between symptom onset of initial illness and completing the participant questionnaire was 222 days (Interquartile range (IQR) 189 to 269 days). In total, 54.7% (179/327) of participants reported they did not feel fully recovered. Persistent symptoms were reported by 93.3% (305/325) of participants, with fatigue the most common (82.8%, 255/308), followed by breathlessness (53.5%, 175/327). 46.8% (153/327) reported an increase in MRC dyspnoea scale of at least one grade. New or worse disability was reported by 24.2% (79/327) of participants. Overall (EQ5D-5L) summary index was significantly worse at the time of follow-up (median difference 0.1 points on a scale of 0 to 1, IQR: -0.2 to 0.0). Females under the age of 50 years were five times less likely to report feeling recovered (adjusted OR 5.09, 95% CI 1.64 to 15.74), were more likely to have greater disability (adjusted OR 4.22, 95% CI 1.12 to 15.94), twice as likely to report worse fatigue (adjusted OR 2.06, 95% CI 0.81 to 3.31) and seven times more likely to become more breathless (adjusted OR 7.15, 95% CI 2.24 to 22.83) than men of the same age. Conclusions: Survivors of Covid-19 experienced long-term symptoms, new disability, increased breathlessness, and reduced quality of life. These findings were present even in young, previously healthy working age adults, and were most common in younger females. Policymakers should fund further research to identify effective treatments for long-Covid and ensure healthcare, social care and welfare support is available for individuals with long-Covid.
Subject(s)
COVID-19 , Dyspnea , FatigueABSTRACT
BackgroundThe long-term sequalae of COVID-19 remain poorly characterised. In this study, we aimed to assess long-standing symptoms (LS) (symptoms lasting from the time of discharge) in previously hospitalised patients with COVID-19 and assess associated risk factors. MethodsThis is a longitudinal cohort study of adults ([≥]18 years of age) with clinically diagnosed or laboratory-confirmed COVID-19 admitted to Sechenov University Hospital Network in Moscow, Russia. Data were collected from patients discharged between April 8 and July 10, 2020. Participants were interviewed via telephone using Tier 1 ISARIC Long-term Follow-up Study CRF and the WHO CRF for Post COVID conditions. Reported symptoms were further categorised based on the system(s) involved. Additional information on dyspnoea, quality of life and fatigue was collected using validated instruments. Multivariable logistic regressions were performed to investigate risk factors for development of LS categories. FindingsOverall, 2,649 of 4,755 patients discharged from the hospitals were available for the follow-up and included in the study. The median age of the patients was 56 years (IQR, 46-66) and 1,353 (51.1%) were women. The median follow-up time since hospital discharge was 217.5 (200.4-235.5) days. At the time of the follow-up interview 1247 (47.1%) participants reported LS. Fatigue (21.2%, 551/2599), shortness of breath (14.5%, 378/2614) and forgetfulness (9.1%, 237/2597) were the most common LS reported. Chronic fatigue (25%, 658/2593) and respiratory (17.2% 451/2616) were the most common LS categories. with reporting of multi-system involvement (MSI) less common (11.3%; 299). Female sex was associated with LS categories of chronic fatigue with an odds ratio of 1.67 (95% confidence interval 1.39 to 2.02), neurological (2.03, 1.60 to 2.58), mood and behaviour (1.83, 1.41 to 2.40), dermatological (3.26, 2.36 to 4.57), gastrointestinal (2.50, 1.64 to 3.89), sensory (1.73, 2.06 to 2.89) and respiratory (1.31, 1.06 to 1.62). Pre-existing asthma was associated with neurological (1.95, 1.25 to 2.98) and mood and behavioural changes (2.02, 1.24 to 3.18) and chronic pulmonary disease was associated with chronic fatigue (1.68, 1.21 to 2.32). Interpretation6 to 8 months after acute infection episode almost a half of patients experience symptoms lasting since hospital discharge. One in ten individuals experiences MSI. Female sex is the main risk factor for majority of the LS categories. chronic pulmonary disease is associated with a higher risk of chronic fatigue development, and asthma with neurological and mood and behaviour changes. Individuals with LS and MSI should be the main target for future research and intervention strategies. FundingThis study is supported by Russian Fund for Basic Research and UK Embassy in Moscow. The ISARIC work is supported by grants from: the NIHR Health Protection Research Unit (HPRU) in Emerging and Zoonotic Infections at University of Liverpool in partnership with Public Health England (PHE), in collaboration with Liverpool School of Tropical Medicine and the University of Oxford [award 200907], Wellcome Trust and Department for International Development [215091/Z/18/Z], and the Bill and Melinda Gates Foundation [OPP1209135], EU Platform for European Preparedness Against (Re-) emerging Epidemics (PREPARE) [FP7 project 602525] This research was funded in part, by the Wellcome Trust. The views expressed are those of the authors and not necessarily those of the DID, NIHR, Wellcome Trust or PHE. Research in contextO_ST_ABSEvidence before this studyC_ST_ABSEvidence suggests that COVID-19 may result in short- and long-term consequences to health. Most studies do not provide definitive answers due to a combination of short follow-up (2-3 months), small sample size, and use of non-standardised tools. There is a need to study the longer-term health consequences of previously hospitalised patients with COVID-19 infection and to identify risk factors for sequalae. Added value of this studyTo our knowledge, this is the largest cohort study (n=2,649) with the longest follow-up since hospital discharge (6-8 months) of previously hospitalised adult patients. We found that 6-8 months after discharge from the hospital, around a half (47.1%) of patients reported at least one long-standing symptom since discharge. Once categories of symptoms were assessed, chronic fatigue and respiratory problems were the most frequent clusters of long-standing symptoms in our patients. Of those patients having long-term symptoms, a smaller proportion (11.3%) had multisystem involvement, with three or more categories of long-standing symptoms present. Although most patients developed symptoms since discharge, a smaller number of individuals experienced symptom beginning symptom appearing weeks or months after the acute phase. Female sex was a predictor for most of the symptom categories at the time of the follow-up interview, with chronic pulmonary disease associated with chronic fatigue-related symptoms, and asthma with a higher risk of neurological symptoms, mood and behaviour problems. Implications of all the available evidenceThe majority of patients experienced long-lasting symptoms 6 to 8 months after hospital discharge and almost half reported at least one long-standing symptom, with chronic fatigue and respiratory problems being the most frequent. A smaller number reported multisystem impacts with three or more long-standing categories present at follow-up. A higher risk was found for women, for chronic pulmonary disease with chronic fatigue, and neurological symptoms and mood and behaviour problems with asthma. Patterns of the symptom development following COVID-19 should be further investigated in future research.
Subject(s)
COVID-19ABSTRACT
Background: Reports of ethnic inequalities in COVID-19 outcomes are conflicting and the reasons for any differences in outcomes are unclear. We investigated ethnic inequalities in critical care admission patterns, the need for invasive mechanical ventilation (IMV), and in-hospital mortality, among hospitalised patients with COVID-19. Methods: We undertook a prospective cohort study in which dedicated research staff recruited hospitalised patients with suspected/confirmed COVID-19 from 260 hospitals across England, Scotland and Wales, collecting data directly and from records between 6th February and 8th May 2020 with follow-up until 22nd May 2020. Analysis used hierarchical regression models accounting for confounding, competing risks, and clustering of patients in hospitals. Potential mediators for death were explored with a three-way decomposition mediation analysis. Findings: Of 34,986 patients enrolled, 30,693 (88%) had ethnicity recorded: South Asian (1,388, 5%), East Asian (266, 1%), Black (1,094, 4%), Other Ethnic Minority (2,398, 8%) (collectively Ethnic Minorities), and White groups (25,547, 83%). Ethnic Minorities were younger and more likely to have diabetes (type 1/type 2) but had fewer other comorbidities such as chronic heart disease or dementia than the White group. No difference was seen between ethnic groups in the time from symptom onset to hospital admission, nor in illness severity at admission. Critical care admission was more common in South Asian (odds ratio 1.28, 95% confidence interval 1.09 to 1.52), Black (1.36, 1.14 to 1.62), and Other Ethnic Minority (1.29, 1.13 to 1.47) groups compared to the White group, after adjusting for age, sex and location. This was broadly unchanged after adjustment for deprivation and comorbidities. Patterns were similar for IMV. Higher adjusted mortality was seen in the South Asian (hazard ratio 1.19, 1.05 to 1.36), but not East Asian (1.00, 0.74 to 1.35), Black (1.05, 0.91 to 1.26) or Other Ethnic Minority (0.99, 0.89 to 1.10) groups, compared to the White group. 18% (95% CI, 9% to 56%) of the excess mortality in South Asians was mediated by pre-existing diabetes. Interpretation: Ethnic Minorities in hospital with COVID-19 were more likely to be admitted to critical care and receive IMV than Whites, despite similar disease severity on admission, similar duration of symptoms, and being younger with fewer comorbidities. South Asians are at greater risk of dying, due at least in part to a higher prevalence of pre-existing diabetes. Trial Registration: The study was registered at https://www.isrctn.com/ISRCTN66726260. Funding Statement: This work is supported by grants from: the National Institute for Health Research [award CO-CIN-01], the Medical Research Council [grant MC_PC_19059] and by the National Institute for Health Research Health Protection Research Unit (NIHR HPRU) in Emerging and Zoonotic Infections at University of Liverpool in partnership with Public Health England (PHE), in collaboration with Liverpool School of Tropical Medicine and the University of Oxford [NIHR award 200907], Wellcome Trust and Department for International Development [215091/Z/18/Z], and the Bill and Melinda Gates Foundation [OPP1209135], and Liverpool Experimental Cancer Medicine Centre for providing infrastructure support for this research (Grant Reference: C18616/A25153). JSN-V-T is seconded to the Department of Health and Social Care, England (DHSC).Declaration of Interests: All authors have completed the ICMJE uniform disclosure form at www.icmje.org/coi_disclosure.pdf and declare: AB Docherty reports grants from Department of Health and Social Care, during the conduct of the study; grants from Wellcome Trust, outside the submitted work; CA Green reports grants from DHSC National Institute of Health Research UK, during the conduct of the study; PW Horby reports grants from Wellcome Trust / Department for International Development / Bill and Melinda Gates Foundation, grants from NIHR , during the conduct of the study; JS Nguyen-Van-Tam reports grants from Department of Health and Social Care, England, during the conduct of the study; and is seconded to the Department of Health and Social Care, England (DHSC); PJM Openshaw reports personal fees from consultancies and from European Respiratory Society; grants from MRC, MRC Global Challenge Research Fund, EU, NIHR Biomedical Research Centre, MRC/GSK, Wellcome Trust, NIHR (HPRU in Respiratory Infection), and NIHR Senior Investigator outside the submitted work. His role as President of the British Society for Immunology was unpaid but travel and accommodation at some meetings was provided by the Society. JK Baillie reports grants from Medical Research Council UK; MG Semple reports grants from DHSC National Institute of Health Research UK, grants from Medical Research Council UK, grants from Health Protection Research Unit in Emerging & Zoonotic Infections, University of Liverpool, during the conduct of the study; other from Integrum Scientific LLC, Greensboro, NC, USA, outside the submitted work. EM Harrison, H Ardwick, J Dunning, R Pius, L Norman, KA Holden, JM Read, G Carson, L Merson, J Lee, D Plotkin, L Sigfrid, S Halpin, C Jackson, and C Gamble, all declare: no support from any organisation for the submitted work; no financial relationships with any organisations that might have an interest in the submitted work in the previous three years; and no other relationships or activities that could appear to have influenced the submitted work.Ethics Approval Statement: Ethical approval was given by the South Central – Oxford C Research Ethics Committee in England (Ref: 13/SC/0149), and by the Scotland A Research Ethics Committee (Ref: 20/SS/0028).