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Journal articleDixon P, Kallis C, Grainger R, et al., 2021,
Care After Presenting with Seizures (CAPS): An analysis of the impact of a seizure referral pathway and nurse support on neurology referral rates for patients admitted with a seizure
, SEIZURE-EUROPEAN JOURNAL OF EPILEPSY, Vol: 92, Pages: 18-23, ISSN: 1059-1311 -
Conference paperKoteci A, Morgan AD, Whittaker HR, et al., 2021,
INCIDENCE AND PREVALENCE OF LEFT-SIDED HEART FAILURE IN PATIENTS WITH IDIOPATHIC PULMONARY FIBROSIS: A POPULATION-BASED STUDY
, Publisher: BMJ PUBLISHING GROUP, Pages: A148-A149, ISSN: 0040-6376 -
Conference paperLenoir A, Whittaker HR, Gayle A, et al., 2021,
Clinical characteristics, mortality rates and causes of death in non-exacerbating COPD patients. A longitudinal cohort analysis of UK primary care data
, Publisher: EUROPEAN RESPIRATORY SOC JOURNALS LTD, ISSN: 0903-1936- Author Web Link
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- Citations: 1
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Conference paperKallis C, Morgan A, Maslova E, et al., 2021,
Trends in asthma incidence in children: a UK population-based cohort study
, European-Respiratory-Society (ERS) International Congress, Publisher: EUROPEAN RESPIRATORY SOC JOURNALS LTD, ISSN: 0903-1936- Author Web Link
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- Citations: 1
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Journal articleWhittaker H, Kiddle S, Quint J, 2021,
Challenges and pitfalls of using repeat spirometry recordings in routine primary care data to measure FEV1 decline in a COPD population
, Pragmatic and Observational Research, Vol: 2021, Pages: 119-130, ISSN: 1179-7266BackgroundElectronic healthcare records (EHR) are increasingly used for epidemiological studies but are often viewed as lacking quality compared to randomised control trials and prospective cohorts. Studies of patients with chronic obstructive pulmonary disease (COPD) often use rate of forced expiratory volume in 1 second (FEV1) decline as an outcome however, its definition and robustness in EHR has not be investigated. We aimed to investigate how rate of FEV1 decline differs by the criteria used in an EHR database.MethodsClinical Practice Research Datalink and Hospital Episode Statistics were used. Patient populations were defined using 8 sets of criteria around repeated FEV1 measurements. At a minimum, patients had a diagnosis of COPD, were ≥35 years old, were current or ex-smokers, and had data recorded from 2004. FEV1 measurements recorded during follow-up were identified. Thereafter, eight populations were defined based on criteria around: i) the exclusion of patients or individual measurements with potential measurement error; ii) minimum number of FEV1 measurements; iii) minimum time interval between measurements; iv) specific timing of measurements; v) minimum follow-up time; and vi) the use of linked data. For each population, rate of FEV1 decline was estimated using mixed linear regression. ResultsFor 7/8 patient populations, rates of FEV1 decline (age and sex adjusted) were similar and ranged from -18.7ml/year (95%CI -19.2 to -18.2) to -16.5ml/year (95%CI -17.3 to -15.7). Rates of FEV1 decline in populations that excluded patients with potential measurement error ranged from -79.4ml/year (95%CI -80.7 to -78.2) to -46.8ml/year (95%CI -47.6 to -46.0). ConclusionsFEV1 decline remained similar in a COPD population regardless of number of FEV1 measurements, time intervals between measurements, follow-up period, exclusion of specific FEV1 measurements, and linkage to HES. However, exclusion of individuals with questionable data led to selection bias and fast
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Journal articleWild JM, Porter JC, Molyneaux PL, et al., 2021,
Understanding the burden of interstitial lung disease post-COVID-19: the UK Interstitial Lung Disease-Long COVID Study (UKILD-Long COVID)
, BMJ Open Respiratory Research, Vol: 8, Pages: 1-10, ISSN: 2052-4439Introduction The COVID-19 pandemic has led to over 100 million cases worldwide. The UK has had over 4 million cases, 400 000 hospital admissions and 100 000 deaths. Many patients with COVID-19 suffer long-term symptoms, predominantly breathlessness and fatigue whether hospitalised or not. Early data suggest potentially severe long-term consequence of COVID-19 is development of long COVID-19-related interstitial lung disease (LC-ILD).Methods and analysis The UK Interstitial Lung Disease Consortium (UKILD) will undertake longitudinal observational studies of patients with suspected ILD following COVID-19. The primary objective is to determine ILD prevalence at 12 months following infection and whether clinically severe infection correlates with severity of ILD. Secondary objectives will determine the clinical, genetic, epigenetic and biochemical factors that determine the trajectory of recovery or progression of ILD. Data will be obtained through linkage to the Post-Hospitalisation COVID platform study and community studies. Additional substudies will conduct deep phenotyping. The Xenon MRI investigation of Alveolar dysfunction Substudy will conduct longitudinal xenon alveolar gas transfer and proton perfusion MRI. The POST COVID-19 interstitial lung DiseasE substudy will conduct clinically indicated bronchoalveolar lavage with matched whole blood sampling. Assessments include exploratory single cell RNA and lung microbiomics analysis, gene expression and epigenetic assessment.Ethics and dissemination All contributing studies have been granted appropriate ethical approvals. Results from this study will be disseminated through peer-reviewed journals.Conclusion This study will ensure the extent and consequences of LC-ILD are established and enable strategies to mitigate progression of LC-ILD.
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Journal articleBachtiger P, Adamson A, Maclean WA, et al., 2021,
Determinants of shielding behaviour during the COVID-19 pandemic and associations with wellbeing in >7,000 NHS patients: 17-week longitudinal observational study.
, JMIR Public Health and Surveillance, Vol: 7, Pages: 1-14, ISSN: 2369-2960BACKGROUND: The UK National Health Service (NHS) classified 2.2 million people as clinically extremely vulnerable (CEV) during the first wave of the 2020 COVID-19 pandemic, advising them to 'shield' - to not leave home for any reason. OBJECTIVE: The aim of this study was to measure the determinants of shielding behaviour and associations with wellbeing in a large NHS patient population, towards informing future health policy. METHODS: Patients contributing to an ongoing longitudinal participatory epidemiology study (LoC-19, n = 42,924) received weekly email invitations to complete questionnaires (17-week shielding period starting 9th April 2020) within their NHS personal electronic health record. Question items focused on wellbeing. Participants were stratified into four groups by self-reported CEV status (qualifying condition) and adoption of shielding behaviour (baselined at week 1 or 2). Distribution of CEV criteria is reported alongside situational variables and uni- and multivariable logistic regression. Longitudinal trends in physical and mental wellbeing were displayed graphically. Free-text responses reporting variables impacting wellbeing were semi-quantified using natural language processing. In the lead up to a second national lockdown (October 23rd, 2020), a follow-up questionnaire evaluated subjective concern if further shielding were advised. RESULTS: 7,240 participants were included. Among the CEV (2,391), 1,133 (47.3%) assumed shielding behaviour at baseline, compared with 633 (15.0%) in the non-CEV group. Those CEV who shielded were more likely to be Asian (Odds Ratio OR 2.02 [1.49-2.76]), female (OR 1.24 [1.05-1.45]), older (OR per year increase 1.01 [1.00-1.02]) and live in a home with outdoor space (OR 1.34 [1.06-1.70]) or 3-4 other inhabitants (3 = OR 1.49 [1.15-1.94], 4 = OR 1.49 [1.10-2.01]); and be solid organ transplant recipients (2.85 [2.18-3.77]) or have severe chronic lung disease (OR 1.63 [1.30-2.04]). Receipt of a government letter adv
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Journal articlegroves D, karsanji U, evans R, et al., 2021,
Predicting future health risk in COPD: Differential impact of disease specific and multi-morbidity based risk stratification
, International Journal of COPD, Vol: 2021, Pages: 1741-1754, ISSN: 1176-9106Objective: Multi-morbidity contributes to mortality and hospitalisation in COPD but it is uncertain how this interacts with disease severity in risk prediction. We compared contributions of multi-morbidity and disease severity factors in modelling future health risk using UK primary care healthcare data. Method: Health records from 103,955 patients with COPD identified from the Clinical Practice Research Datalink were analysed. We compared Area Under The Curve (AUC) statistics for logistic regression (LR) models incorporating disease indices with models incorporating categorised co-morbidities. We also compared these models with performance of The John Hopkins Adjusted Clinical Groups® System (ACG) risk prediction algorithm. Results: LR models predicting all-cause mortality outperformed models predicting hospitalisation. Mortality was best predicted by disease severity (AUC & 95% CI: 0.816 (0.805 - 0.827)) and prediction was enhanced only marginally by the addition of multi-morbidity indices (AUC & 95% CI: 0.829 (0.818 – 0.839)). The model combining disease severity and multi-morbidity indices was a better predictor of hospitalisation (AUC & 95% CI: 0.679 (0.672 – 0.686)). ACG derived LR models outperformed conventional regression models for hospitalisation (AUC & 95% CI: 0.697 (0.690 – 0.704)) but not for mortality (AUC & 95% CI: 0.816 (0.805 – 0.827)). Conclusion: Stratification of future health risk in COPD can be undertaken using clinical and demographic data recorded in primary care but the impact of disease severity and multi-morbidity varies depending on the choice of health outcome. A more comprehensive risk modelling algorithm such as ACG offers enhanced prediction for hospitalisation by incorporating a wider range of coded diagnoses.
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Journal articleCook S, Eggen AE, Hopstock L, et al., 2021,
Chronic Obstructive Pulmonary Disease (COPD) in population studies in Russia and Norway: comparison of prevalence, awareness and management
, International Journal of COPD, Vol: 16, Pages: 1353-1368, ISSN: 1176-9106Background: Chronic obstructive pulmonary disease (COPD) is a major cause of morbidity and mortality worldwide. Despite a high prevalence of smoking and respiratory symptoms, two recent population-based studies in Russia found a relatively low prevalence of obstructive lung function. Here, we investigated the prevalence of both obstructive lung disease and respiratory symptoms in a population-based study conducted in two Russian cities and compared the findings with a similar study from Norway conducted in the same time period.Methods: The study population was a sub-sample of participants aged 40– 69 years participating in the Know Your Heart (KYH) study in Russia in 2015– 18 (n=1883) and in the 7th survey of the Tromsø Study (n=5271) carried out in Norway in 2015– 16 (Tromsø 7) who participated in spirometry examinations. The main outcome was obstructive lung function (FEV1/FVC ratio< lower limit of normal on pre-bronchodilator spirometry examination) with and without respiratory symptoms (chronic cough and breathlessness). In those with obstructive lung function, awareness (known diagnosis) and management (use of medications, smoking cessation) were compared.Results: The age-standardized prevalence of obstructive lung function was similar among men in both studies (KYH 11.0% vs Tromsø 7 9.8%, p=0.21) and higher in the Norwegian (9.4%) than Russian (6.8%) women (p=0.006). In contrast, the prevalence of obstructive lung function plus respiratory symptoms was higher in Russian men (KYH 8.3% vs Tromsø 7 4.7%, p< 0.001) but similar in women (KYH 5.9% vs Tromsø 7 6.4%, p=0.18). There was a much higher prevalence of respiratory symptoms in Russian than Norwegian participants of both sexes regardless of presence of obstructive lung function.Conclusion: The prevalence of respiratory symptoms was strikingly high among Russian participants but this was not explained by a higher burden of obstructive lung function on
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Journal articleWhittaker HR, Gulea C, Koteci A, et al., 2021,
Post-acute COVID-19 sequelae in cases managed in the community or hospital in the UK: a population based study
<jats:title>Abstract</jats:title><jats:sec><jats:title>Objective</jats:title><jats:p>To compare post-COVID-19 sequelae between hospitalised and non-hospitalised individuals</jats:p></jats:sec><jats:sec><jats:title>Design</jats:title><jats:p>Population-based cohort study</jats:p></jats:sec><jats:sec><jats:title>Setting</jats:title><jats:p>1,383 general practices in England contributing to Clinical Practice Research Database Aurum</jats:p></jats:sec><jats:sec><jats:title>Participants</jats:title><jats:p>46,687 COVID-19 cases diagnosed between 1<jats:sup>st</jats:sup> August to 17<jats:sup>th</jats:sup> October 2020 (45.4% male; mean age 40), either hospitalised within two weeks of diagnosis or non-hospitalised, and followed-up for a maximum of three months.</jats:p></jats:sec><jats:sec><jats:title>Main outcome measures</jats:title><jats:p>Event rates of new symptoms, diseases, prescriptions and healthcare utilisation in hospitalised and non-hospitalised individuals, with between-group comparison using Cox regression. Outcomes compared at 6 and 12 months prior to index date, equating to first UK wave and pre-pandemic. Non-hospitalised group outcomes stratified by age and sex.</jats:p></jats:sec><jats:sec><jats:title>Results</jats:title><jats:p>45,272 of 46,687 people were non-hospitalised; 1,415 hospitalised. Hospitalised patients had higher rates of 13/26 symptoms and 11/19 diseases post-COVID-19 than the community group, received more prescriptions and utilised more healthcare. The largest differences were noted for rates per 100,000 person-weeks [95%CI] of <jats:italic>breathlessness:</jats:italic> 536 [432 to 663] v. 85 [77 to 93]; <jats:italic>joint pain:</jats:italic> 295 [221 to 392] v. 168 [158 to 179]
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