Adverse events following first and second dose COVID-19 vaccination in England, October 2020 to September 2021: a national vaccine surveillance platform self-controlled case series study.

BackgroundPost-authorisation vaccine safety surveillance is well established for reporting common adverse events of interest (AEIs) following influenza vaccines, but not for COVID-19 vaccines.AimTo estimate the incidence of AEIs presenting to primary care following COVID-19 vaccination in England, and report safety profile differences between vaccine brands.MethodsWe used a self-controlled case series design to estimate relative incidence (RI) of AEIs reported to the national sentinel network, the Oxford-Royal College of General Practitioners Clinical Informatics Digital Hub. We compared AEIs (overall and by clinical category) 7 days pre- and post-vaccination to background levels between 1 October 2020 and 12 September 2021.ResultsWithin 7,952,861 records, 781,200 individuals (9.82%) presented to general practice with 1,482,273 AEIs, 4.85% within 7 days post-vaccination. Overall, medically attended AEIs decreased post-vaccination against background levels. There was a 3-7% decrease in incidence within 7 days after both doses of Comirnaty (RI: 0.93; 95% CI: 0.91-0.94 and RI: 0.96; 95% CI: 0.94-0.98, respectively) and Vaxzevria (RI: 0.97; 95% CI: 0.95-0.98). A 20% increase was observed after one dose of Spikevax (RI: 1.20; 95% CI: 1.00-1.44). Fewer AEIs were reported as age increased. Types of AEIs, e.g. increased neurological and psychiatric conditions, varied between brands following two doses of Comirnaty (RI: 1.41; 95% CI: 1.28-1.56) and Vaxzevria (RI: 1.07; 95% CI: 0.97-1.78).ConclusionCOVID-19 vaccines are associated with a small decrease in medically attended AEI incidence. Sentinel networks could routinely report common AEI rates, contributing to reporting vaccine safety.

Intrapulmonary shunting is a key contributor to hypoxia in COVID-19: An update on the pathophysiology.

BACKGROUND: The pathophysiology of COVID-19 remains poorly understood. We aimed to estimate the contribution of intrapulmonary shunting and ventilation-to-perfusion (VA/Q) mismatch using a mathematical model to construct oxygen-haemoglobin dissociation curves (ODCs). METHODS: ODCs were constructed using transcutaneous pulse oximetry at two different fractions of inspired oxygen (FiO2). 199 patients were included from two large district general hospitals in the South East of England from 1st to 14th January 2021. The study was supported by the National Institute of Health Research (NIHR) Clinical Research Network. RESULTS: Overall mortality was 29%. Mean age was 68.2 years (SEM 1·2) with 46% female. Median shunt on admission was 17% (IQR 8-24.5); VA/Q was 0.61 (IQR 0.52-0.73). Shunt was 37.5% higher in deaths (median 22%, IQR 9-29) compared to survivors (16%, 8-21; p = 0.0088) and was a predictor of mortality (OR 1.04; 95% CI 1.01-1.07). Admission oxygen saturations were more strongly predictive of mortality (OR 0.91, 95% CI 0.87-0.96). There was no difference in VA/Q mismatch between deaths (0.60; IQR 0.50-0.73) and survivors (0.61; IQR 0.52-0.73; p = 0.63) and it was not predictive of mortality (OR 0.68; 95% CI 0.18-2.52; p = 0.55). Shunt negatively correlated with admission oxygen saturation (R -0.533; p<0.0001) whereas VA/Q was not (R 0.1137; p = 0.12). INTERPRETATION: Shunt, not VA/Q mismatch, was associated with worsening hypoxia, though calculating shunt was not of prognostic value. This study adds to our understanding of the pathophysiology of hypoxaemia in COVID-19. Our inexpensive and reliable technique may provide further insights into the pathophysiology of hypoxia in other respiratory diseases.

Differences in Clinical Presentation With Long COVID After Community and Hospital Infection and Associations With All-Cause Mortality: English Sentinel Network Database Study.

BACKGROUND: Most studies of long COVID (symptoms of COVID-19 infection beyond 4 weeks) have focused on people hospitalized in their initial illness. Long COVID is thought to be underrecorded in UK primary care electronic records. OBJECTIVE: We sought to determine which symptoms people present to primary care after COVID-19 infection and whether presentation differs in people who were not hospitalized, as well as post-long COVID mortality rates. METHODS: We used routine data from the nationally representative primary care sentinel cohort of the Oxford-Royal College of General Practitioners Research and Surveillance Centre (N=7,396,702), applying a predefined long COVID phenotype and grouped by whether the index infection occurred in hospital or in the community. We included COVID-19 infection cases from March 1, 2020, to April 1, 2021. We conducted a before-and-after analysis of long COVID symptoms prespecified by the Office of National Statistics, comparing symptoms presented between 1 and 6 months after the index infection matched with the same months 1 year previously. We conducted logistic regression analysis, quoting odds ratios (ORs) with 95% CIs. RESULTS: In total, 5.63% (416,505/7,396,702) and 1.83% (7623/416,505) of the patients had received a coded diagnosis of COVID-19 infection and diagnosis of, or referral for, long COVID, respectively. People with diagnosis or referral of long COVID had higher odds of presenting the prespecified symptoms after versus before COVID-19 infection (OR 2.66, 95% CI 2.46-2.88, for those with index community infection and OR 2.42, 95% CI 2.03-2.89, for those hospitalized). After an index community infection, patients were more likely to present with nonspecific symptoms (OR 3.44, 95% CI 3.00-3.95; P<.001) compared with after a hospital admission (OR 2.09, 95% CI 1.56-2.80; P<.001). Mental health sequelae were more strongly associated with index hospital infections (OR 2.21, 95% CI 1.64-2.96) than with index community infections (OR 1.36, 95% CI 1.21-1.53; P<.001). People presenting to primary care after hospital infection were more likely to be men (OR 1.43, 95% CI 1.25-1.64; P<.001), more socioeconomically deprived (OR 1.42, 95% CI 1.24-1.63; P<.001), and with higher multimorbidity scores (OR 1.41, 95% CI 1.26-1.57; P<.001) than those presenting after an index community infection. All-cause mortality in people with long COVID was associated with increasing age, male sex (OR 3.32, 95% CI 1.34-9.24; P=.01), and higher multimorbidity score (OR 2.11, 95% CI 1.34-3.29; P<.001). Vaccination was associated with reduced odds of mortality (OR 0.10, 95% CI 0.03-0.35; P<.001). CONCLUSIONS: The low percentage of people recorded as having long COVID after COVID-19 infection reflects either low prevalence or underrecording. The characteristics and comorbidities of those presenting with long COVID after a community infection are different from those hospitalized. This study provides insights into the presentation of long COVID in primary care and implications for workload.

Developing a Long COVID Phenotype for Postacute COVID-19 in a National Primary Care Sentinel Cohort: Observational Retrospective Database Analysis.

BACKGROUND: Following COVID-19, up to 40% of people have ongoing health problems, referred to as postacute COVID-19 or long COVID (LC). LC varies from a single persisting symptom to a complex multisystem disease. Research has flagged that this condition is underrecorded in primary care records, and seeks to better define its clinical characteristics and management. Phenotypes provide a standard method for case definition and identification from routine data and are usually machine-processable. An LC phenotype can underpin research into this condition. OBJECTIVE: This study aims to develop a phenotype for LC to inform the epidemiology and future research into this condition. We compared clinical symptoms in people with LC before and after their index infection, recorded from March 1, 2020, to April 1, 2021. We also compared people recorded as having acute infection with those with LC who were hospitalized and those who were not. METHODS: We used data from the Primary Care Sentinel Cohort (PCSC) of the Oxford Royal College of General Practitioners (RCGP) Research and Surveillance Centre (RSC) database. This network was recruited to be nationally representative of the English population. We developed an LC phenotype using our established 3-step ontological method: (1) ontological step (defining the reasoning process underpinning the phenotype, (2) coding step (exploring what clinical terms are available, and (3) logical extract model (testing performance). We created a version of this phenotype using Protégé in the ontology web language for BioPortal and using PhenoFlow. Next, we used the phenotype to compare people with LC (1) with regard to their symptoms in the year prior to acquiring COVID-19 and (2) with people with acute COVID-19. We also compared hospitalized people with LC with those not hospitalized. We compared sociodemographic details, comorbidities, and Office of National Statistics-defined LC symptoms between groups. We used descriptive statistics and logistic regression. RESULTS: The long-COVID phenotype differentiated people hospitalized with LC from people who were not and where no index infection was identified. The PCSC (N=7.4 million) includes 428,479 patients with acute COVID-19 diagnosis confirmed by a laboratory test and 10,772 patients with clinically diagnosed COVID-19. A total of 7471 (1.74%, 95% CI 1.70-1.78) people were coded as having LC, 1009 (13.5%, 95% CI 12.7-14.3) had a hospital admission related to acute COVID-19, and 6462 (86.5%, 95% CI 85.7-87.3) were not hospitalized, of whom 2728 (42.2%) had no COVID-19 index date recorded. In addition, 1009 (13.5%, 95% CI 12.73-14.28) people with LC were hospitalized compared to 17,993 (4.5%, 95% CI 4.48-4.61; P<.001) with uncomplicated COVID-19. CONCLUSIONS: Our LC phenotype enables the identification of individuals with the condition in routine data sets, facilitating their comparison with unaffected people through retrospective research. This phenotype and study protocol to explore its face validity contributes to a better understanding of LC.

Delayed surgery for localised and metastatic renal cell carcinoma: a systematic review and meta-analysis for the COVID-19 pandemic.

PURPOSE: The COVID-19 pandemic has led to the cancellation or deferment of many elective cancer surgeries. We performed a systematic review on the oncological effects of delayed surgery for patients with localised or metastatic renal cell carcinoma (RCC) in the targeted therapy (TT) era. METHOD: The protocol of this review is registered on PROSPERO(CRD42020190882). A comprehensive literature search was performed on Medline, Embase and Cochrane CENTRAL using MeSH terms and keywords for randomised controlled trials and observational studies on the topic. Risks of biases were assessed using the Cochrane RoB tool and the Newcastle-Ottawa Scale. For localised RCC, immediate surgery [including partial nephrectomy (PN) and radical nephrectomy (RN)] and delayed surgery [including active surveillance (AS) and delayed intervention (DI)] were compared. For metastatic RCC, upfront versus deferred cytoreductive nephrectomy (CN) were compared. RESULTS: Eleven studies were included for quantitative analysis. Delayed surgery was significantly associated with worse cancer-specific survival (HR 1.67, 95% CI 1.23-2.27, p < 0.01) in T1a RCC, but no significant difference was noted for overall survival. For localised ≥ T1b RCC, there were insufficient data for meta-analysis and the results from the individual reports were contradictory. For metastatic RCC, upfront TT followed by deferred CN was associated with better overall survival when compared to upfront CN followed by deferred TT (HR 0.61, 95% CI 0.43-0.86, p < 0.001). CONCLUSION: Noting potential selection bias, there is insufficient evidence to support the notion that delayed surgery is safe in localised RCC. For metastatic RCC, upfront TT followed by deferred CN should be considered.

Characteristics and outcomes of patients with COVID-19 at a district general hospital in Surrey, UK.

BACKGROUND: This retrospective cohort study aims to define the clinical findings and outcomes of every patient admitted to a district general hospital in Surrey with COVID-19 in March 2020, providing a snapshot of the first wave of infection in the UK. This study is the first detailed insight into the impact of frailty markers on patient outcomes and provides the infection rate among healthcare workers. METHODS: Data were obtained from medical records. Outcome measures were level of oxygen therapy, discharge and death. Patients were followed up until 21 April 2020. RESULTS: 108 patients were included. 34 (31%) died in hospital or were discharged for palliative care. 43% of patients aged over 65 died. The commonest comorbidities were hypertension (49; 45%) and diabetes (25; 23%). Patients who died were older (mean difference ±SEM, 13.76±3.12 years; p<0.0001) with a higher NEWS2 score (median 6, IQR 2.5-7.5 vs median 2, IQR 2-6) and worse renal function (median differences: urea 2.7 mmol/L, p<0.01; creatinine 4 µmol/L, p<0.05; eGFR 14 mL/min, p<0.05) on admission compared with survivors. Frailty markers were identified as risk factors for death. Clinical Frailty Scale (CFS) was higher in patients over 65 who died than in survivors (median 5, IQR 4-6 vs 3.5, IQR 2-5; p<0.01). Troponin and creatine kinase levels were higher in patients who died than in those who recovered (p<0.0001). Lymphopenia was common (median 0.8, IQR 0.6-1.2; p<0.005). Every patient with heart failure died (8). 26 (24%) were treated with continuous positive airway pressure (CPAP; median 3 days, IQR 2-7.3) and 9 (8%) were intubated (median 14 days, IQR 7-21). All patients who died after discharge (4; 6%) were care home residents. 276 of 699 hospital staff tested were positive for COVID-19. CONCLUSIONS: This study identifies older patients with frailty as being particularly vulnerable and reinforces government policy to protect this group at all costs.