Estimating the contribution of respiratory pathogens to acute exacerbations of COPD using routine data.

OBJECTIVES: To characterise microbiology testing and results associated with emergency admissions for acute exacerbation of COPD (AECOPD), and determine the accuracy of ICD-10 codes in retrospectively identifying laboratory-confirmed respiratory pathogens in this setting. METHODS: Using person-level data from the Secure Anonymised Information Linkage Databank in Wales, we extracted emergency admissions for COPD from 1/12/2016 to 30/11/2018 and undertook linkage of admissions data to microbiology data to identify laboratory-confirmed infection. We further used these data to assess the accuracy of pathogen-specific ICD-10 codes. RESULTS: We analysed data from 15,950 people who had 25,715 emergency admissions for COPD over the two-year period. 99.5% of admissions could be linked to a laboratory test within 7 days of admission date. Sputum was collected in 5,013 (19.5%) of admissions, and respiratory virus testing in 1,219 (4.7%). Where respiratory virus testing was undertaken, 46.7% returned any positive result. Influenza was the virus most frequently detected, in 21.5% of admissions where testing was conducted. ICD-10 codes exhibited low sensitivity in detecting laboratory-confirmed respiratory pathogens. CONCLUSIONS: In people admitted to hospital with AECOPD, increased testing for respiratory viruses could enable more effective antibiotic stewardship and isolation of cases. Linkage with microbiology data achieves more accurate and reliable case definitions.

SARS-CoV-2 infection risk among 77,587 healthcare workers: a national observational longitudinal cohort study in Wales, United Kingdom, April to November 2020.

OBJECTIVES: To better understand the risk of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection among healthcare workers, leading to recommendations for the prioritisation of personal protective equipment, testing, training and vaccination. DESIGN: Observational, longitudinal, national cohort study. SETTING: Our cohort were secondary care (hospital-based) healthcare workers employed by NHS Wales (United Kingdom) organisations from 1 April 2020 to 30 November 2020. PARTICIPANTS: We included 577,756 monthly observations among 77,587 healthcare workers. Using linked anonymised datasets, participants were grouped into 20 staff roles. Additionally, each role was deemed either patient-facing, non-patient-facing or undetermined. This was linked to individual demographic details and dates of positive SARS-CoV-2 PCR tests. MAIN OUTCOME MEASURES: We used univariable and multivariable logistic regression models to determine odds ratios (ORs) for the risk of a positive SARS-CoV-2 PCR test. RESULTS: Patient-facing healthcare workers were at the highest risk of SARS-CoV-2 infection with an adjusted OR (95% confidence interval [CI]) of 2.28 (95% CI 2.10-2.47). We found that after adjustment, foundation year doctors (OR 1.83 [95% CI 1.47-2.27]), healthcare support workers [OR 1.36 [95% CI 1.20-1.54]) and hospital nurses (OR 1.27 [95% CI 1.12-1.44]) were at the highest risk of infection among all staff groups. Younger healthcare workers and those living in more deprived areas were at a higher risk of infection. We also observed that infection rates varied over time and by organisation. CONCLUSIONS: These findings have important policy implications for the prioritisation of vaccination, testing, training and personal protective equipment provision for patient-facing roles and the higher risk staff groups.

Identifying COPD in routinely collected electronic health records: a systematic scoping review.

Although routinely collected electronic health records (EHRs) are widely used to examine outcomes related to COPD, consensus regarding the identification of cases from electronic healthcare databases is lacking. We systematically examine and summarise approaches from the recent literature. MEDLINE via EBSCOhost was searched for COPD-related studies using EHRs published from January 1, 2018 to November 30, 2019. Data were extracted relating to the case definition of COPD and determination of COPD severity and phenotypes. From 185 eligible studies, we found widespread variation in the definitions used to identify people with COPD in terms of code sets used (with 20 different code sets in use based on the ICD-10 classification alone) and requirement of additional criteria (relating to age (n=139), medication (n=31), multiplicity of events (n=21), spirometry (n=19) and smoking status (n=9)). Only seven studies used a case definition which had been validated against a reference standard in the same dataset. Various proxies of disease severity were used since spirometry results and patient-reported outcomes were not often available. To enable the research community to draw reliable insights from EHRs and aid comparability between studies, clear reporting and greater consistency of the definitions used to identify COPD and related outcome measures is key.

Impact of COVID-19 lockdown on the incidence and mortality of acute exacerbations of chronic obstructive pulmonary disease: national interrupted time series analyses for Scotland and Wales.

BACKGROUND: The COVID-19 pandemic and ensuing national lockdowns have dramatically changed the healthcare landscape. The pandemic's impact on people with chronic obstructive pulmonary disease (COPD) remains poorly understood. We hypothesised that the UK-wide lockdown restrictions were associated with reductions in severe COPD exacerbations. We provide the first national level analyses of the impact of the COVID-19 pandemic and first lockdown on severe COPD exacerbations resulting in emergency hospital admissions and/or leading to death as well as those recorded in primary care or emergency departments. METHODS: Using data from Public Health Scotland and the Secure Anonymised Information Linkage Databank in Wales, we accessed weekly counts of emergency hospital admissions and deaths due to COPD over the first 30 weeks of 2020 and compared these to the national averages over the preceding 5 years. For both Scotland and Wales, we undertook interrupted time-series analyses to model the impact of instigating lockdown on these outcomes. Using fixed-effect meta-analysis, we derived pooled estimates of the overall changes in trends across the two nations. RESULTS: Lockdown was associated with 48% pooled reduction in emergency admissions for COPD in both countries (incidence rate ratio, IRR 0.52, 95% CI 0.46 to 0.58), relative to the 5-year averages. There was no statistically significant change in deaths due to COPD (pooled IRR 1.08, 95% CI 0.87 to 1.33). In Wales, lockdown was associated with 39% reduction in primary care consultations for acute exacerbation of COPD (IRR 0.61, 95% CI 0.52 to 0.71) and 46% reduction in COPD-related emergency department attendances (IRR 0.54, 95% CI 0.36 to 0.81). CONCLUSIONS: The UK-wide lockdown was associated with the most substantial reductions in COPD exacerbations ever seen across Scotland and Wales, with no corresponding increase in COPD deaths. This may have resulted from reduced transmission of respiratory infections, reduced exposure to outdoor air pollution and/or improved COPD self-management.

Impact of COVID-19 lockdown on emergency asthma admissions and deaths: national interrupted time series analyses for Scotland and Wales.

BACKGROUND: The COVID-19 pandemic's impact on people with asthma is poorly understood. We hypothesised that lockdown restrictions were associated with reductions in severe asthma exacerbations requiring emergency asthma admissions and/or leading to death. METHODS: Using data from Public Health Scotland and the Secure Anonymised Information Linkage Databank in Wales, we compared weekly counts of emergency admissions and deaths due to asthma over the first 18 weeks in 2020 with the national averages over 2015-2019. We modelled the impact of instigating lockdown on these outcomes using interrupted time-series analysis. Using fixed-effect meta-analysis, we derived pooled estimates of the overall changes in trends across the two nations. We also investigated trends in asthma-related primary care prescribing and emergency department (ED) attendances in Wales. RESULTS: Lockdown was associated with a 36% pooled reduction in emergency admissions for asthma (incidence rate ratio, IRR: 0.64, 95% CI: 0.49 to 0.83, p value 0.001) across both countries. There was no significant change in asthma deaths (pooled IRR: 0.57, 95% CI: 0.17 to 1.94, p value 0.37). ED asthma attendances in Wales declined during lockdown (IRR: 0.85, 95% CI: 0.73 to 0.99, p value 0.03). A large spike of 121% more inhaled corticosteroids and 133% more oral corticosteroid prescriptions was seen in Wales in the week before lockdown. CONCLUSIONS: National lockdowns were associated with substantial reductions in severe asthma exacerbations leading to hospital admission across both Scotland and Wales, with no corresponding increase in asthma deaths.

Systematic meta-analyses and field synopsis of genetic association studies in colorectal adenomas.

BACKGROUND: Low penetrance genetic variants, primarily single nucleotide polymorphisms, have substantial influence on colorectal cancer (CRC) susceptibility. Most CRCs develop from colorectal adenomas (CRA). Here we report the first comprehensive field synopsis that catalogues all genetic association studies on CRA, with a parallel online database [http://www.chs.med.ed.ac.uk/CRAgene/]. METHODS: We performed a systematic review, reviewing 9750 titles, and then extracted data from 130 publications reporting on 181 polymorphisms in 74 genes. We conducted meta-analyses to derive summary effect estimates for 37 polymorphisms in 26 genes. We applied the Venice criteria and Bayesian False Discovery Probability (BFDP) to assess the levels of the credibility of associations. RESULTS: We considered the association with the rs6983267 variant at 8q24 as 'highly credible', reaching genome-wide statistical significance in at least one meta-analysis model. We identified 'less credible' associations (higher heterogeneity, lower statistical power, BFDP > 0.02) with a further four variants of four independent genes: MTHFR c.677C>T p.A222V (rs1801133), TP53 c.215C>G p.R72P (rs1042522), NQO1 c.559C>T p.P187S (rs1800566), and NAT1 alleles imputed as fast acetylator genotypes. For the remaining 32 variants of 22 genes for which positive associations with CRA risk have been previously reported, the meta-analyses revealed no credible evidence to support these as true associations. CONCLUSIONS: The limited number of credible associations between low penetrance genetic variants and CRA reflects the lower volume of evidence and associated lack of statistical power to detect associations of the magnitude typically observed for genetic variants and chronic diseases. The CRA gene database provides context for CRA genetic association data and will help inform future research directions.

Abundant pleiotropy in human complex diseases and traits.

We present a systematic review of pleiotropy among SNPs and genes reported to show genome-wide association with common complex diseases and traits. We find abundant evidence of pleiotropy; 233 (16.9%) genes and 77 (4.6%) SNPs show pleiotropic effects. SNP pleiotropic status was associated with gene location (p = 0.024; pleiotropic SNPs more often exonic [14.5% versus 4.9% for nonpleiotropic, trait-associated SNPs] and less often intergenic [15.8% versus 23.6%]), "predicted transcript consequence" (p = 0.001; pleiotropic SNPs more often predicted to be structurally deleterious [5% versus 0.4%] but not more often in regulatory sequences), and certain disease classes. We develop a method to calculate the likelihood that pleiotropic links between traits occurred more often than expected and demonstrate that this approach can identify etiological links that are already known (such as between fetal hemoglobin and malaria risk) and those that are not yet established (e.g., between plasma campesterol levels and gallstones risk; and between immunoglobulin A and juvenile idiopathic arthritis). Examples of pleiotropy will accumulate over time, but it is already clear that pleiotropy is a common property of genes and SNPs associated with disease traits, and this will have implications for identification of molecular targets for drug development, future genetic risk-profiling, and classification of diseases.