COVID-19 infection, admission and death and the impact of corticosteroids amongst people with rare autoimmune rheumatic disease during the second wave of covid-19 in England: results from the RECORDER Project.

OBJECTIVES: To calculate the rates of COVID-19 infection and COVID-19-related death among people with rare autoimmune rheumatic diseases (RAIRD) during the second wave of the COVID-19 pandemic in England, and describe the impact of corticosteroids on outcomes. METHODS: Hospital Episode Statistics data were used to identify people alive 01 August 2020 with ICD-10 codes for RAIRD from the whole population of England. Linked national health records were used to calculate rates and rate ratios of COVID-19 infection and death up to 30 April 2021. Primary definition of COVID-19-related death was mention of COVID-19 on the death certificate. NHS Digital and Office for National Statistics general population data were used for comparison. The association between 30-day corticosteroid usage and COVID-19-related death, COVID-19-related hospital admissions and all-cause deaths were also described. RESULTS: Of 168 330 people with RAIRD, 9,961 (5.92%) had a positive COVID-19 PCR test. The age-standardised infection rate ratio between RAIRD and the general population was 0.99 (95% CI 0.97-1.00). 1,342 (0.80%) people with RAIRD died with COVID-19 on their death certificate and the age-sex-standardised mortality rate for COVID-19-related death was 2.76 (2.63-2.89) times higher than in the general population. There was a dose-dependent relationship between 30-day corticosteroid usage and COVID-19-related death. There was no increase in deaths due to other causes. CONCLUSIONS: During the second wave of COVID-19 in England, people with RAIRD had the same risk of COVID-19 infection but a 2.76-fold increased risk of COVID-19-related death compared with the general population, with corticosteroids associated with increased risk.

The Impact of COVID-19 on Lung Cancer Incidence in England: Analysis of the National Lung Cancer Audit 2019 and 2020 Rapid Cancer Registration Datasets.

BACKGROUND: The COVID-19 pandemic has caused significant disruption to health-care services and delivery worldwide. The impact of the pandemic and associated national lockdowns on lung cancer incidence in England have yet to be assessed. RESEARCH QUESTION: What was the impact of the first year of the COVID-19 pandemic on the incidence and presentation of lung cancer in England? STUDY DESIGN AND METHODS: In this retrospective observational study, incidence rates for lung cancer were calculated from The National Lung Cancer Audit Rapid Cancer Registration Datasets for 2019 and 2020, using midyear population estimates from the Office of National Statistics as the denominators. Rates were compared using Poisson regression according to time points related to national lockdowns in 2020. RESULTS: Sixty-four thousand four hundred fifty-seven patients received a diagnosis of lung cancer across 2019 (n = 33,088) and 2020 (n = 31,369). During the first national lockdown, a 26% reduction in lung cancer incidence was observed compared with the equivalent calendar period of 2019 (adjusted incidence rate ratio [IRR], 0.74; 95% CI, 0.71-0.78). This included a 23% reduction in non-small cell lung cancer (adjusted IRR, 0.77; 95% CI, 0.74-0.81) and a 45% reduction in small cell lung cancer (adjusted IRR, 0.55; 95% CI, 0.46-0.65) incidence. Thereafter, incidence rates almost recovered to baseline, without overcompensation (adjusted IRR, 0.96; 95% CI, 0.94-0.98). INTERPRETATION: The incidence rates of lung cancer in England fell significantly by 26% during the first national lockdown in 2020 and did not compensate later in the year.

Background rate estimations for thrombosis with thrombocytopaenia: challenges in evaluating rare safety signals following vaccination in real time during a pandemic.

OBJECTIVES: During COVID-19 vaccination programmes, new safety signals have emerged for vaccines, including extremely rare cases of thrombosis with thrombocytopaenia syndrome (TTS). Background event rates before and during the pandemic are essential for contextualisation of such infrequent events. In the literature, most studies do not report an overall TTS event rate. Rather, background rates are mainly reported for subtypes of thrombotic/thromboembolic diagnoses included in the TTS clinical definition mostly by anatomical location, with reported rates for TTS subtypes varying widely. The objective of this study was to report prepandemic TTS background event rates in the general population. METHODS: Prepandemic background TTS rates were generated via secondary data analysis using a cohort design in the IBM Truven MarketScan (now Merative MarketScan) US health insurance claims database, from 1 January 2019 to 31 December 2019. Two algorithms were applied: thrombocytopaenia occurring±7 days (algorithm 1) or occurring 1 day prior to ≤14 days after the thrombotic/thromboembolic event (algorithm 2). RESULTS: The study population derived from the MarketScan database analysis included approximately 9.8 million adults (aged ≥18 years; mean age 45 years, 52% females). Using this study population, prepandemic background TTS incidence was estimated as 9.8-11.1 per 100 000 person-years. Event rates were higher in males and increased with age. Similar patterns were observed with both algorithms. CONCLUSIONS: This study presents an estimate of aggregate prepandemic background TTS event rates including by type of thrombosis/thromboembolism and age group. The background event rates are dependent on the precision of capturing underlying TTS events in variable data sources, and the ability of electronic health records or insurance claims databases to reflect the TTS clinical definition. Differences between reported event rates demonstrate that estimating background event rates for rare, unprecedented safety events is methodologically challenging.

COVID-19 infection, admission and death among people with rare autoimmune rheumatic disease in England: results from the RECORDER project.

OBJECTIVES: To calculate the rates of COVID-19 infection and COVID-19-related death among people with rare autoimmune rheumatic diseases (RAIRD) during the first wave of the COVID-19 pandemic in England compared with the general population. METHODS: We used Hospital Episode Statistics to identify all people alive on 1 March 2020 with ICD-10 codes for RAIRD from the whole population of England. We used linked national health records (demographic, death certificate, admissions and PCR testing data) to calculate rates of COVID-19 infection and death up to 31 July 2020. Our primary definition of COVID-19-related death was mention of COVID-19 on the death certificate. General population data from Public Health England and the Office for National Statistics were used for comparison. We also describe COVID-19-related hospital admissions and all-cause deaths. RESULTS: We identified a cohort of 168 680 people with RAIRD, of whom 1874 (1.11%) had a positive COVID-19 PCR test. The age-standardized infection rate was 1.54 (95% CI: 1.50, 1.59) times higher than in the general population. A total of 713 (0.42%) people with RAIRD died with COVID-19 on their death certificate and the age-sex-standardized mortality rate for COVID-19-related death was 2.41 (2.30-2.53) times higher than in the general population. There was no evidence of an increase in deaths from other causes in the RAIRD population. CONCLUSIONS: During the first wave of COVID-19 in England, people with RAIRD had a 54% increased risk of COVID-19 infection and more than twice the risk of COVID-19-related death compared with the general population. These increases were seen despite shielding policies.

Ninety-day mortality following lung cancer surgery: outcomes from the English national clinical outcomes audit.

Accurately explaining perioperative mortality and risk to patients is an essential part of shared decision making. In the case of lung cancer surgery, the currently available multivariable mortality prediction tools perform poorly, and could mislead patients. Using data from 2004 to 2012, this group has previously produced data tables for 90-day postoperative mortality, to be used as a communication aid in the consenting process. Using National Lung Cancer Clinical Outcomes audit data from 2017 to 2018, we have produced updated early mortality tables, to reflect current thoracic surgery practice.

An intelligent early warning system of analyzing Twitter data using machine learning on COVID-19 surveillance in the US.

The World Health Organization (WHO) declared on 11th March 2020 the spread of the coronavirus disease 2019 (COVID-19) a pandemic. The traditional infectious disease surveillance had failed to alert public health authorities to intervene in time and mitigate and control the COVID-19 before it became a pandemic. Compared with traditional public health surveillance, harnessing the rich data from social media, including Twitter, has been considered a useful tool and can overcome the limitations of the traditional surveillance system. This paper proposes an intelligent COVID-19 early warning system using Twitter data with novel machine learning methods. We use the natural language processing (NLP) pre-training technique, i.e., fine-tuning BERT as a Twitter classification method. Moreover, we implement a COVID-19 forecasting model through a Twitter-based linear regression model to detect early signs of the COVID-19 outbreak. Furthermore, we develop an expert system, an early warning web application based on the proposed methods. The experimental results suggest that it is feasible to use Twitter data to provide COVID-19 surveillance and prediction in the US to support health departments' decision-making.

The Anesthesiologist's Perspective and Experience in Global Congenital Cardiac Surgery: Results of a Survey of the Congenital Cardiac Anesthesia Society Membership.

Anesthesiologists are important components of volunteer teams which perform congenital cardiac surgery in low-resource settings throughout the world, but limited data exist to characterize the nature and breadth of their work. A survey of Congenital Cardiac Anesthesia Society (CCAS) members was conducted with the objective of understanding the type of voluntary care being provided, its geographic reach, the frequency of volunteer activities, and factors which may encourage or limit anesthesiologists' involvement in this work. The survey was completed by 108 participants. Respondents reported a total of 115 volunteer trips during the study period, including work in 41 countries on 5 continents. Frequent motivating factors to begin volunteering included invitations from charitable groups, encouragement from senior colleagues, and direct connections to individual locations. Discouraging factors included familial responsibilities, the need to use vacation time, and a lack of support from home institutions. The year 2020 saw a marked decrease in reported volunteer activity, and respondents reported multiple pandemic-related factors which might discourage future volunteer activities. The results of this study demonstrate the global reach of anesthesiologists in providing care for children having cardiac surgery. It also offers insights into the challenges faced by interested individuals, many of which are related to a lack of institutional support. These challenges have only mounted under the COVID-pandemic, leading to a dramatic downturn in volunteer activities. Finally, the survey reinforces the need for better coordination of volunteer activities to optimize clinical impact.

Risk of death among people with rare autoimmune diseases compared with the general population in England during the 2020 COVID-19 pandemic.

OBJECTIVES: To quantify the risk of death among people with rare autoimmune rheumatic diseases (RAIRD) during the UK 2020 COVID-19 pandemic compared with the general population, and compared with their pre-COVID risk. METHODS: We conducted a cohort study in Hospital Episode Statistics for England from 2003 onwards, and linked data from the NHS Personal Demographics Service. We used ONS published data for general population mortality rates. RESULTS: We included 168 691 people with a recorded diagnosis of RAIRD alive on 1 March 2020. Their median age was 61.7 (IQR 41.5-75.4) years, and 118 379 (70.2%) were female. Our case ascertainment methods had a positive predictive value of 85%. A total of 1815 (1.1%) participants died during March and April 2020. The age-standardized mortality rate (ASMR) among people with RAIRD (3669.3; 95% CI: 3500.4, 3838.1 per 100 000 person-years) was 1.44 (95% CI: 1.42, 1.45) times higher than the average ASMR during the same months of the previous 5 years, whereas in the general population of England it was 1.38 times higher. Age-specific mortality rates in people with RAIRD compared with the pre-COVID rates were higher from the age of 35 upwards, whereas in the general population the increased risk began from age 55 upwards. Women had a greater increase in mortality rates during COVID-19 compared with men. CONCLUSION: The risk of all-cause death is more prominently raised during COVID-19 among people with RAIRD than among the general population. We urgently need to quantify how much risk is due to COVID-19 infection and how much is due to disruption to health-care services.