RESUMEN
IntroductionIndividuals with COVID-19 frequently experience symptoms and impaired quality of life beyond 4-12 weeks, commonly referred to as Long COVID. Whether Long COVID is one or several distinct syndromes is unknown. Establishing the evidence base for appropriate therapies is needed. We aim to evaluate the symptom burden and underlying pathophysiology of Long COVID syndromes in non-hospitalised individuals and evaluate potential therapies. Methods and analysisA cohort of 4000 non-hospitalised individuals with a past COVID-19 diagnosis and 1000 matched controls will be selected from anonymised primary care records from the Clinical Practice Research Datalink (CPRD) and invited by their general practitioners to participate on a digital platform (Atom5). Individuals will report symptoms, quality of life, work capability, and patient reported outcome measures. Data will be collected monthly for one year. Statistical clustering methods will be used to identify distinct Long COVID symptom clusters. Individuals from the four most prevalent clusters and two control groups will be invited to participate in the BioWear sub-study which will further phenotype Long COVID symptom clusters by measurement of immunological parameters and actigraphy. We will review existing evidence on interventions for post-viral syndromes and Long COVID to map and prioritise interventions for each newly characterised Long COVID syndrome. Recommendations will be made using the cumulated evidence in an expert consensus workshop. A virtual supportive intervention will be coproduced with patients and health service providers for future evaluation. Individuals with lived experience of Long COVID will be involved throughout this programme through a patient and public involvement group. Ethics and disseminationEthical approval was obtained from the Solihull Research Ethics Committee, West Midlands (21/WM/0203). The study is registered on the ISRCTN Registry (1567490). Research findings will be presented at international conferences, in peer-reviewed journals, to Long COVID patient support groups and to policymakers. Article SummaryO_ST_ABSStrengths and limitations of the studyC_ST_ABSO_LIThe study will generate a nationally representative cohort of individuals with Long COVID recruited from primary care. C_LIO_LIWe will recruit controls matched on a wide range of demographic and clinical factors to assess differences in symptoms between people with Long COVID and similar individuals without a history of COVID-19. C_LIO_LIWe will use a newly developed electronic patient reported outcome measure (Symptom Burden Questionnaire) for Long COVID to comprehensively assess a wide range of symptoms highlighted by existing literature, patients, and clinicians. C_LIO_LIImmunological, proteomic, genetic, and wearable data captured in the study will allow deep phenotyping of Long COVID syndromes to help better target therapies. C_LIO_LIA limitation is that a significant proportion of non-hospitalised individuals affected by COVID-19 in the first wave of the pandemic will lack confirmatory testing and will be excluded from recruitment to the study. C_LI
RESUMEN
BackgroundCOVID-19 has placed a catastrophic burden on acute hospitals. In an attempt to reduce admissions and enable safe early discharge, a COVID virtual ward (CVW) care pathway has been supported by NHS England. This includes discharging people who meet objective criteria based on acuity scores and oxygen saturations, with pulse oximeters and daily phone calls for up to 14 days. Observational studies have reported the safety of this system, but without describing the outcomes from usual care. MethodsA retrospective study using routinely collected health data from all adults with a confirmed positive severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) swab result between 1st June 2020 and 31st Jan 2021 who attended the Emergency Department or Acute Medical Unit at QEHB, which does not have a CVW service. Criteria for CVW were applied using data from the first 24 hours of presentation to hospital and subsequent health outcomes were included for 28 days, including re-presentation, re-admission, ITU escalation and death. Results were compared to reported studies based in secondary care. ResultsDuring the study period, 26,127 patients presented to QEHB hospital. 2301 had a positive SARS-CoV-2 swab. Of these, 1730 (75.2%) did not meet the criteria for the CVW and 571 (24.8%) did. Of the 571, 325 (56.9%) were discharged home within 24 hours and 246 (43.1%) were admitted for 24 hours or longer. Those admitted were older, with increased co-morbidities, 80.9% required hospital-supported acute therapies after the first 24 hours and 10.6% died. Of the 325 discharged, 44 were readmitted (13.5%), 30 (9.2%) with COVID-related symptoms, 5 (1.5%) required ITU and 1 patient (0.3%) died. These results were comparable to published studies with a CVW service. DiscussionIn the current study, discharging patients without a CVW did not confer a greater risk of re-presentation, re-admission, ITU escalation or death. The majority of patients who remained in hospital despite meeting the CVW criteria did so for the provision of treatments or acute assessments. It remains uncertain whether a CVW delivers improvements in hard outcomes, and further research is needed.
RESUMEN
RationalInfection with the SARS-CoV2 virus is associated with elevated neutrophil counts. Evidence of neutrophil dysfunction in COVID-19 is based predominantly on transcriptomics or single functional assays. Cell functions are interwoven pathways, and so understanding the effect of COVID-19 across the spectrum of neutrophil function may identify tractable therapeutic targets. ObjectivesExamine neutrophil phenotype and functional capacity in COVID-19 patients versus age-matched controls (AMC) MethodsIsolated neutrophils from 41 hospitalised, non-ICU COVID-19 patients and 23 AMC underwent ex vivo analyses for migration, bacterial phagocytosis, ROS generation, NET formation (NETosis) and cell surface receptor expression. DNAse 1 activity was measured, alongside circulating levels of cfDNA, MPO, VEGF, IL-6 and sTNFRI. All measurements were correlated to clinical outcome. Serial sampling on day 3-5 post hospitalisation were also measured. ResultsCompared to AMC, COVID-19 neutrophils demonstrated elevated transmigration (p=0.0397) and NETosis (p=0.0366), but impaired phagocytosis (p=0.0236) associated with impaired ROS generation (p<0.0001). Surface expression of CD54 (p<0.0001) and CD11c (p=0.0008) was significantly increased and CD11b significantly decreased (p=0.0229) on COVID-19 patient neutrophils. COVID-19 patients showed increased systemic markers of NETosis including increased cfDNA (p=0.0153) and impaired DNAse activity (p<0.0.001). MPO (p<0.0001), VEGF (p<0.0001), TNFRI (p<0.0001) and IL-6 (p=0.009) were elevated in COVID-19, which positively correlated with disease severity by 4C score. ConclusionCOVID-19 is associated with neutrophil dysfunction across all main effector functions, with altered phenotype, elevated migration, impaired antimicrobial responses and elevated NETosis. These changes represent a clear mechanism for tissue damage and highlight that targeting neutrophil function may help modulate COVID-19 severity.
RESUMEN
BackgroundThis study assesses COVID-19 hospitalised patient demography and outcomes during wave 1 and wave 2, prior to new variants of the virus. MethodsAll patients with a positive SARS-CoV-2 swab between 10th March 2020 and 5th July 2020 (wave 1) and 1st September 2020 and 16th November 2020 (wave 2) admitted to University Hospitals Birmingham NHS Foundation Trust were included (n=4856), followed for 28 days. ResultsWave 2 patients were younger, more ethnically diverse, had less co-morbidities and disease presentation was milder on presentation. After matching for these factors, mortality was reduced, but without differences in intensive care admissions. ConclusionPrior to new SARS-CoV-2 variants, outcomes for hospitalised patients with COVID-19 were improving but with similar intensive care needs.
RESUMEN
ObjectivesExisting UK prognostic models for patients admitted to hospital with COVID-19 are limited by reliance on comorbidities, which are under-recorded in secondary care, and lack of imaging data among the candidate predictors. Our aims were to develop and externally validate novel prognostic models for adverse outcomes (death, intensive therapy unit (ITU) admission) in UK secondary care; and externally validate the existing 4C score. DesignCandidate predictors included demographic variables, symptoms, physiological measures, imaging, laboratory tests. Final models used logistic regression with stepwise selection. SettingModel development was performed in data from University Hospitals Birmingham (UHB). External validation was performed in the CovidCollab dataset. ParticipantsPatients with COVID-19 admitted to UHB January-August 2020 were included. Main outcome measuresDeath and ITU admission within 28 days of admission. Results1040 patients with COVID-19 were included in the derivation cohort; 288 (28%) died and 183 (18%) were admitted to ITU within 28 days of admission. Area under the receiver operating curve (AUROC) for mortality was 0.791 (95%CI 0.761-0.822) in UHB and 0.767 (95%CI 0.754-0.780) in CovidCollab; AUROC for ITU admission was 0.906 (95%CI 0.883-0.929) in UHB and 0.811 (95%CI 0.795-0.828) in CovidCollab. Models showed good calibration. Addition of comorbidities to candidate predictors did not improve model performance. AUROC for the 4C score in the UHB dataset was 0.754 (95%CI 0.721-0.786). ConclusionsThe novel prognostic models showed good discrimination and calibration in derivation and external validation datasets, and outperformed the existing 4C score. The models can be integrated into electronic medical records systems to calculate each individual patients probability of death or ITU admission at the time of hospital admission. Implementation of the models and clinical utility should be evaluated. Article SummaryO_ST_ABSStrengths and limitations of this studyC_ST_ABSO_LIWe developed novel prognostic models predicting mortality and ITU admission within 28 days of admission for patients hospitalised with COVID-19, using a large routinely collected dataset gathered at admission with a wide range of possible predictors (demographic variables, symptoms, physiological measures, imaging, laboratory test results). C_LIO_LIThese novel models showed good discrimination and calibration in both derivation and external validation cohorts, and outperformed the existing ISARIC model and 4C score in the derivation dataset. We found that addition of comorbidities to the set of candidate predictors included in model derivation did not improve model performance. C_LIO_LIIf integrated into hospital electronic medical records systems, the model algorithms will provide a predicted probability of mortality or ITU admission for each patient based on their individual data at, or close to, the time of admission, which will support clinicians decision making with regard to appropriate patient care pathways and triage. This information might also assist clinicians in explaining complex prognostic assessments and decisions to patients and their relatives. C_LIO_LIA limitation of the study was that in the external validation cohort we were unable to examine all of the predictors included in the original full UHB model due to only a reduced set of candidate predictors being available in CovidCollab. Nevertheless, the reduced model performed well and the results suggest it may be applicable in a wide range of datasets where only a reduced set of predictor variables is available. C_LIO_LIFurthermore, it was not possible to carry out stratified analysis by ethnicity as the UHB dataset contained too few patients in most of the strata, and no ethnicity data was available in the CovidCollab dataset. C_LI
RESUMEN
BackgroundThe COVID-19 pandemic was associated with social restrictions in the UK from 16th March 2020. It was unclear if the lockdown period was associated with differences in the case-mix of non-COVID acute medical admissions compared with the previous year. MethodsRetrospective data were collected for 1st-30th April 2019 and 1st-30th April 2020 from University Hospitals Birmingham NHS Foundation Trust, one of the largest hospitals in the UK with over 2 million patient contacts per year. The latter time period was chosen to coincide with the peak of COVID-19 cases in the West Midlands. All patients admitted under acute medicine during these time periods were included. COVID-19 was confirmed by SARS-Cov-2 swab or a probable case of COVID-19 based on World Health Organization diagnostic parameters. Non-COVID patients were those with a negative SARS-Cov-2 swab and no suspicion of COVID-19. Data was sourced from UHBs in-house electronic health system (EHS). ResultsThe total number of acute medical admissions fell comparing April 2019 (n = 2409) to April 2020 (n = 1682). As a proportion of total admissions, those aged under 45 years decreased, while those aged 46 and over did not change. The number of admissions due to psychiatric conditions and overdoses was higher in April 2020 (p < 0.001). When viewed as a proportion of admissions, alcohol-related admissions (p = 0.004), psychiatric conditions and overdoses (p< 0.001) increased in April 2020 than in April 2019. The proportion of patients who were in hospital due to falls also increased in April 2020 (p< 0.001). In the same period, the absolute number and the proportion of admissions that were due to non-specific chest pain, to musculoskeletal complaints and patients who self-discharged prior to assessment decreased (p = 0.02, p = 0.01 and p = 0.002 respectively). There were no significant differences in non-COVID-related intensive care admissions or mortality between the same months in the two years. ConclusionIn this large, single-centre study, there was a change in hospitalised case-mix when comparing April 2019 with April 2020: an increase in conditions which potentially reflect social isolation (falls, drug and alcohol misuse and psychiatric illness) and a decrease in conditions which rarely require in-patient hospital treatment (musculoskeletal pain and non-cardiac chest pain) especially among younger adults. These results highlight two areas for further research; the impact of social isolation on health and whether younger adults could be offered alternative health services to avoid potentially unnecessary hospital assessment.
RESUMEN
Introduction A significant proportion of patients with Coronavirus Disease-19 (COVID-19) have hypertension and are treated with renin-angiotensin system (RAS) inhibitors, namely angiotensin-converting enzyme I inhibitors (ACE inhibitors) or angiotensin II type-1 receptor blockers (ARBs). These medications have been postulated to influence susceptibility to Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2). The objective of this study was to assess a possible association between prescription of RAS inhibitors and the incidence of COVID-19 and all-cause mortality. Methods We conducted a propensity-score matched cohort study to assess the incidence of COVID-19 among patients with hypertension who were prescribed ACE inhibitors or ARBs compared to patients treated with calcium channel blockers (CCBs) in a large UK-based primary care database (The Health Improvement Network). We estimated crude incidence rates for confirmed/suspected COVID-19 among those prescribed ACE inhibitors, ARBs and CCBs. We used a Cox proportional hazards model to produce adjusted hazard ratios for COVID-19 comparing patients prescribed ACE inhibitors or ARBs to those prescribed CCBs. We further assessed all-cause mortality as a secondary outcome and a composite of accidents, trauma or fractures as a negative control outcome to assess for residual confounding. Results In the propensity score matched analysis, 83 of 18,895 users (0.44%) of ACE inhibitors developed COVID-19 over 8,923 person-years, an incidence rate of 9.3 per 1000 person-years. 85 of 18,895 (0.45%) users of CCBs developed COVID-19 over 8,932 person-years, an incidence rate of 9.5 per 1000 person-years. The adjusted hazard ratio for suspected/confirmed COVID-19 for users of ACE inhibitors compared to CCBs was 0.92 (95% CI 0.68 to 1.26). 79 out of 10,623 users (0.74%) of ARBs developed COVID-19 over 5010 person-years, an incidence rate of 15.8 per 1000 person-years, compared to 11.6 per 1000 person-years among users of CCBs. The adjusted hazard ratio for suspected/confirmed COVID-19 for users of ARBs compared to CCBs was 1.38 (95% CI 0.98 to 1.95). There were no significant associations between use of ACE inhibitors or ARBs and all-cause mortality, compared to use of CCBs. We found no evidence of significant residual confounding with the negative control analysis. Conclusion Current use of ACE inhibitors was not associated with the risk of suspected or confirmed COVID-19 whereas use of ARBs was associated with a statistically non-significant 38% relative increase in risk compared to use of CCBs. However, no significant associations were observed between prescription of either ACE inhibitors or ARBs and all-cause mortality during the peak of the pandemic.
RESUMEN
BackgroundIn December 2019, SARS-CoV-2 caused a global pandemic with a viral infection called COVID-19. The disease usually causes respiratory symptoms but in a small proportion of patients can lead to a pneumonitis, Adult Respiratory Distress Syndrome and death. Invasive Mechanical Ventilation (IMV) is considered a life-saving treatment for COVID-19 patients and a huge demand for IMV devices was reported globally. This review aims to provide insight on the initial IMV practises for COVID-19 patients in the initial phase of the pandemic. MethodsElectronic databases (Embase and MEDLINE) were searched for applicable articles using relevant keywords. The references of included articles were hand searched. Articles that reported the use of IMV in adult COVID-19 patients were included in the review. The NIH quality assessment tool for cohort and cross-sectional studies was used to appraise studies. Results106 abstracts were identified from the databases search, of which 16 were included. 5 studies were included in the meta-analysis. In total, 9988 patients were included across all studies. The overall cases of COVID-19 requiring IMV ranged from 2-77%. Increased age and pre-existing comorbidities increased the likelihood of IMV requirement. The reported mortality rate in patients receiving IMV ranged between 50-100%. On average, IMV was required and initiated between 10-10.5 days from symptoms onset. When invasively ventilated, COVID-19 patients required IMV for a median of 10-17 days across studies. Little information was provided on ventilatory protocols or management strategies and were inconclusive. ConclusionIn these initial reporting studies for the first month of the pandemic, patients receiving IMV were older and had more pre-existing co-morbidities than those who did not require IMV. The mortality rate was high in COVID-19 patients who received IMV. Studies are needed to evaluate protocols and modalities of IMV to improve outcomes and identify the populations most likely to benefit from IMV.
RESUMEN
BackgroundStudies suggest that certain Black and Asian Minority Ethnic groups experience poorer outcomes from COVID-19 but these studies have not provided insight into potential reasons for this. We hypothesised that outcomes would be poorer for those of South Asian ethnicity hospitalised from a confirmed SARS-CoV-2 infection, once confounding factors, health seeking behaviours and community demographics were considered and that this might reflect a more aggressive disease course in these patients. MethodsPatients with confirmed SARS-CoV-2 infection requiring admission to University Hospitals Birmingham NHS Foundation Trust(UHB) in Birmingham UK between 10th March 2020-17th April 2020 were included. Standardised Admission Ratio(SAR) and Standardised Mortality Ratio(SMR) were calculated using observed COVID-19 admissions/deaths and 2011 census data. Hazard Ratio (aHR) for mortality was estimated using Cox proportional hazard model adjusting and propensity score matching. ResultsAll patients admitted to UHB with COVID-19 during the study period were included (2217 in total). Fifty-eight percent were male, 69.5% White and the majority (80.2%) had co-morbidities. Eighteen and a half percent were of South Asian ethnicity, and these patients were more likely to be younger, have no co-morbidities but twice the prevalence of diabetes than White patients. SAR and SMR suggested more admissions and deaths in South Asian patients than would be predicted and they were more likely to present with severe disease despite no delay in presentation since symptom onset. South Asian ethnicity was associated with an increased risk of death; both by Cox regression (Hazard Ratio 1.4 (95%CI 1.2-1.8) after adjusting for age, sex, deprivation and comorbidities and by propensity score matching, matching for the same factors but categorising ethnicity into South Asian or not (Hazard ratio 1.3 (1.0-1.6)). ConclusionsThose of South Asian ethnicity appear at risk of worse COVID-19 outcomes, further studies need to establish the underlying mechanistic pathways.