Subclinical hypothyroidism in Wales from 2000 to 2021: A descriptive cohort study based on electronic health records.

BACKGROUND: Subclinical hypothyroidism (SCH) is a biochemical thyroid disorder characterised by elevated levels of Thyroid Stimulating Hormone (TSH) together with normal levels of thyroid hormones. Evidence on the benefits of treatment is limited, resulting in persistent controversies relating to its clinical management. AIM: This study describes the demographic and clinical characteristics of patients identified as having subclinical hypothyroidism in Wales between 2000 and 2021, the annual cumulative incidence during this period and the testing and treatment patterns associated with this disorder. METHODS: We used linked electronic health records from SAIL Databank. Eligible patients were identified using a combination of diagnostic codes and Thyroid Function Test results. Descriptive analyses were then performed. RESULTS: 199,520 individuals (63.8% female) were identified as having SCH, 23.6% (n = 47,104) of whom received levothyroxine for treatment over the study period. The median study follow-up time was 5.75 person-years (IQR 2.65-9.65). Annual cumulative incidence was highest in 2012 at 502 cases per 100,000 people. 92.5% (n = 184,484) of the study population had TSH levels between the upper limit of normal and 10mIU/L on their first test. 61.9% (n = 5,071) of patients identified using Read v2 codes were in the treated group. 41.9% (n = 19,716) of treated patients had a history of a single abnormal test result before their first prescription. CONCLUSION: In Wales, the number of incident cases of SCH has risen unevenly between 2000 and 2021. Most of the study population had mild SCH on their index test, but more than a third of the identified patients received levothyroxine after a single abnormal test result. Patients with clinically recorded diagnoses were more likely to be treated. Given the expectation of steadily increasing patient numbers, more evidence is required to support the clinical management of subclinical hypothyroidism.

Interim 2023/2024 Season Influenza Vaccine Effectiveness in Primary and Secondary Care in the United Kingdom.

BACKGROUND: We report 2023/2024 season interim influenza vaccine effectiveness for three studies, namely, primary care in Great Britain, hospital settings in Scotland and hospital settings in England. METHODS: A test negative design was used to estimate vaccine effectiveness. RESULTS: Estimated vaccine effectiveness against all influenzas ranged from 63% (95% confidence interval 46 to 75%) to 65% (41 to 79%) among children aged 2-17, from 36% (20 to 49%) to 55% (43 to 65%) among adults 18-64 and from 40% (29 to 50%) to 55% (32 to 70%) among adults aged 65 and over. CONCLUSIONS: During a period of co-circulation of influenza A(H1N1)pdm09 and A(H3N2) in the United Kingdom, evidence for effectiveness of the influenza vaccine in both children and adults was found.

End of 2022/23 Season Influenza Vaccine Effectiveness in Primary Care in Great Britain.

BACKGROUND: The 2022/23 influenza season in the United Kingdom saw the return of influenza to prepandemic levels following two seasons with low influenza activity. The early season was dominated by A(H3N2), with cocirculation of A(H1N1), reaching a peak late December 2022, while influenza B circulated at low levels during the latter part of the season. From September to March 2022/23, influenza vaccines were offered, free of charge, to all aged 2-13 (and 14-15 in Scotland and Wales), adults up to 49 years of age with clinical risk conditions and adults aged 50 and above across the mainland United Kingdom. METHODS: End-of-season adjusted vaccine effectiveness (VE) estimates against sentinel primary-care attendance for influenza-like illness, where influenza infection was laboratory confirmed, were calculated using the test negative design, adjusting for potential confounders. METHODS: Results In the mainland United Kingdom, end-of-season VE against all laboratory-confirmed influenza for all those > 65 years of age, most of whom received adjuvanted quadrivalent vaccines, was 30% (95% CI: -6% to 54%). VE for those aged 18-64, who largely received cell-based vaccines, was 47% (95% CI: 37%-56%). Overall VE for 2-17 year olds, predominantly receiving live attenuated vaccines, was 66% (95% CI: 53%-76%). CONCLUSION: The paper provides evidence of moderate influenza VE in 2022/23.

Phenotype execution and modeling architecture to support disease surveillance and real-world evidence studies: English sentinel network evaluation.

Objective: To evaluate Phenotype Execution and Modelling Architecture (PhEMA), to express sharable phenotypes using Clinical Quality Language (CQL) and intensional Systematised Nomenclature of Medicine (SNOMED) Clinical Terms (CT) Fast Healthcare Interoperability Resources (FHIR) valuesets, for exemplar chronic disease, sociodemographic risk factor, and surveillance phenotypes. Method: We curated 3 phenotypes: Type 2 diabetes mellitus (T2DM), excessive alcohol use, and incident influenza-like illness (ILI) using CQL to define clinical and administrative logic. We defined our phenotypes with valuesets, using SNOMED's hierarchy and expression constraint language, and CQL, combining valuesets and adding temporal elements where needed. We compared the count of cases found using PhEMA with our existing approach using convenience datasets. We assessed our new approach against published desiderata for phenotypes. Results: The T2DM phenotype could be defined as 2 intensionally defined SNOMED valuesets and a CQL script. It increased the prevalence from 7.2% to 7.3%. Excess alcohol phenotype was defined by valuesets that added qualitative clinical terms to the quantitative conceptual definitions we currently use; this change increased prevalence by 58%, from 1.2% to 1.9%. We created an ILI valueset with SNOMED concepts, adding a temporal element using CQL to differentiate new episodes. This increased the weekly incidence in our convenience sample (weeks 26-38) from 0.95 cases to 1.11 cases per 100 000 people. Conclusions: Phenotypes for surveillance and research can be described fully and comprehensibly using CQL and intensional FHIR valuesets. Our use case phenotypes identified a greater number of cases, whilst anticipated from excessive alcohol this was not for our other variable. This may have been due to our use of SNOMED CT hierarchy. Our new process fulfilled a greater number of phenotype desiderata than the one that we had used previously, mostly in the modeling domain. More work is needed to implement that sharing and warehousing domains.

Postpandemic Sentinel Surveillance of Respiratory Diseases in the Context of the World Health Organization Mosaic Framework: Protocol for a Development and Evaluation Study Involving the English Primary Care Network 2023-2024.

BACKGROUND: Prepandemic sentinel surveillance focused on improved management of winter pressures, with influenza-like illness (ILI) being the key clinical indicator. The World Health Organization (WHO) global standards for influenza surveillance include monitoring acute respiratory infection (ARI) and ILI. The WHO's mosaic framework recommends that the surveillance strategies of countries include the virological monitoring of respiratory viruses with pandemic potential such as influenza. The Oxford-Royal College of General Practitioner Research and Surveillance Centre (RSC) in collaboration with the UK Health Security Agency (UKHSA) has provided sentinel surveillance since 1967, including virology since 1993. OBJECTIVE: We aim to describe the RSC's plans for sentinel surveillance in the 2023-2024 season and evaluate these plans against the WHO mosaic framework. METHODS: Our approach, which includes patient and public involvement, contributes to surveillance objectives across all 3 domains of the mosaic framework. We will generate an ARI phenotype to enable reporting of this indicator in addition to ILI. These data will support UKHSA's sentinel surveillance, including vaccine effectiveness and burden of disease studies. The panel of virology tests analyzed in UKHSA's reference laboratory will remain unchanged, with additional plans for point-of-care testing, pneumococcus testing, and asymptomatic screening. Our sampling framework for serological surveillance will provide greater representativeness and more samples from younger people. We will create a biomedical resource that enables linkage between clinical data held in the RSC and virology data, including sequencing data, held by the UKHSA. We describe the governance framework for the RSC. RESULTS: We are co-designing our communication about data sharing and sampling, contextualized by the mosaic framework, with national and general practice patient and public involvement groups. We present our ARI digital phenotype and the key data RSC network members are requested to include in computerized medical records. We will share data with the UKHSA to report vaccine effectiveness for COVID-19 and influenza, assess the disease burden of respiratory syncytial virus, and perform syndromic surveillance. Virological surveillance will include COVID-19, influenza, respiratory syncytial virus, and other common respiratory viruses. We plan to pilot point-of-care testing for group A streptococcus, urine tests for pneumococcus, and asymptomatic testing. We will integrate test requests and results with the laboratory-computerized medical record system. A biomedical resource will enable research linking clinical data to virology data. The legal basis for the RSC's pseudonymized data extract is The Health Service (Control of Patient Information) Regulations 2002, and all nonsurveillance uses require research ethics approval. CONCLUSIONS: The RSC extended its surveillance activities to meet more but not all of the mosaic framework's objectives. We have introduced an ARI indicator. We seek to expand our surveillance scope and could do more around transmissibility and the benefits and risks of nonvaccine therapies.

A Prospective Randomized Study on Whether Computer Navigation Is Better Than Conventional Total Knee Replacement in Terms of Short-Term Functional and Clinical Outcomes.

INTRODUCTION:  Computer navigation results in better radiological alignment in total knee replacement (TKR). However, functional and clinical outcomes are equally good in conventional TKR. This study aims to compare the functional and clinical outcomes in patients undergoing navigated and conventional TKR. METHODS: A prospective randomized study between navigated TKR (NKR/Group I) and conventional TKR (CKR/Group II) was carried out. Functional outcome was analyzed using the Oxford Knee Score (OKS) and Western Ontario and McMaster Universities Arthritis Index (WOMAC) score. Clinical outcome was evaluated as knee range of motion. RESULTS: Thirty-nine patients (68 knees) were randomized into two groups: I and II. The mean follow-up was 26 months. There was no statistically significant difference between the two groups with respect to knee range of motion, OKS, and WOMAC score at the final follow-up. CONCLUSION: We concluded that there is no difference in clinical and functional outcomes between navigated and conventional TKR.

Uptake of COVID-19 vaccinations amongst 3,433,483 children and young people: meta-analysis of UK prospective cohorts.

SARS-CoV-2 infection in children and young people (CYP) can lead to life-threatening COVID-19, transmission within households and schools, and the development of long COVID. Using linked health and administrative data, we investigated vaccine uptake among 3,433,483 CYP aged 5-17 years across all UK nations between 4th August 2021 and 31st May 2022. We constructed national cohorts and undertook multi-state modelling and meta-analysis to identify associations between demographic variables and vaccine uptake. We found that uptake of the first COVID-19 vaccine among CYP was low across all four nations compared to other age groups and diminished with subsequent doses. Age and vaccination status of adults living in the same household were identified as important risk factors associated with vaccine uptake in CYP. For example, 5-11 year-olds were less likely to receive their first vaccine compared to 16-17 year-olds (adjusted Hazard Ratio [aHR]: 0.10 (95%CI: 0.06-0.19)), and CYP in unvaccinated households were less likely to receive their first vaccine compared to CYP in partially vaccinated households (aHR: 0.19, 95%CI 0.13-0.29).

Risk of severe COVID-19 outcomes after autumn 2022 COVID-19 booster vaccinations: a pooled analysis of national prospective cohort studies involving 7.4 million adults in England, Northern Ireland, Scotland and Wales.

Background: UK COVID-19 vaccination policy has evolved to offering COVID-19 booster doses to individuals at increased risk of severe Illness from COVID-19. Building on our analyses of vaccine effectiveness of first, second and initial booster doses, we aimed to identify individuals at increased risk of severe outcomes (i.e., COVID-19 related hospitalisation or death) post the autumn 2022 booster dose. Methods: We undertook a national population-based cohort analysis across all four UK nations through linked primary care, vaccination, hospitalisation and mortality data. We included individuals who received autumn 2022 booster doses of BNT162b2 (Comirnaty) or mRNA-1273 (Spikevax) during the period September 1, 2022 to December 31, 2022 to investigate the risk of severe COVID-19 outcomes. Cox proportional hazard models were used to estimate adjusted hazard ratios (aHR) and 95% confidence intervals (CIs) for the association between demographic and clinical factors and severe COVID-19 outcomes after the autumn booster dose. Analyses were adjusted for age, sex, body mass index (BMI), deprivation, urban/rural areas and comorbidities. Stratified analyses were conducted by vaccine type. We then conducted a fixed-effect meta-analysis to combine results across the four UK nations. Findings: Between September 1, 2022 and December 31, 2022, 7,451,890 individuals ≥18 years received an autumn booster dose. 3500 had severe COVID-19 outcomes (2.9 events per 1000 person-years). Being male (male vs female, aHR 1.41 (1.32-1.51)), older adults (≥80 years vs 18-49 years; 10.43 (8.06-13.50)), underweight (BMI <18.5 vs BMI 25.0-29.9; 2.94 (2.51-3.44)), those with comorbidities (≥5 comorbidities vs none; 9.45 (8.15-10.96)) had a higher risk of COVID-19 hospitalisation or death after the autumn booster dose. Those with a larger household size (≥11 people within household vs 2 people; 1.56 (1.23-1.98)) and from more deprived areas (most deprived vs least deprived quintile; 1.35 (1.21-1.51)) had modestly higher risks. We also observed at least a two-fold increase in risk for those with various chronic neurological conditions, including Down's syndrome, immunodeficiency, chronic kidney disease, cancer, chronic respiratory disease, or cardiovascular disease. Interpretation: Males, older individuals, underweight individuals, those with an increasing number of comorbidities, from a larger household or more deprived areas, and those with specific underlying health conditions remained at increased risk of COVID-19 hospitalisation and death after the autumn 2022 vaccine booster dose. There is now a need to focus on these risk groups for investigating immunogenicity and efficacy of further booster doses or therapeutics. Funding: National Core Studies-Immunity, UK Research and Innovation (Medical Research Council and Economic and Social Research Council), Health Data Research UK, the Scottish Government, and the University of Edinburgh.

Risk of COVID-19 death in adults who received booster COVID-19 vaccinations in England.

The emergence of the COVID-19 vaccination has been critical in changing the course of the COVID-19 pandemic. To ensure protection remains high in vulnerable groups booster vaccinations in the UK have been targeted based on age and clinical vulnerabilities. We undertook a national retrospective cohort study using data from the 2021 Census linked to electronic health records. We fitted cause-specific Cox models to examine the association between health conditions and the risk of COVID-19 death and all-other-cause death for adults aged 50-100-years in England vaccinated with a booster in autumn 2022. Here we show, having learning disabilities or Down Syndrome (hazard ratio=5.07;95% confidence interval=3.69-6.98), pulmonary hypertension or fibrosis (2.88;2.43-3.40), motor neuron disease, multiple sclerosis, myasthenia or Huntington's disease (2.94, 1.82-4.74), cancer of blood and bone marrow (3.11;2.72-3.56), Parkinson's disease (2.74;2.34-3.20), lung or oral cancer (2.57;2.04 to 3.24), dementia (2.64;2.46 to 2.83) or liver cirrhosis (2.65;1.95 to 3.59) was associated with an increased risk of COVID-19 death. Individuals with cancer of the blood or bone marrow, chronic kidney disease, cystic fibrosis, pulmonary hypotension or fibrosis, or rheumatoid arthritis or systemic lupus erythematosus had a significantly higher risk of COVID-19 death relative to other causes of death compared with individuals who did not have diagnoses. Policy makers should continue to priorities vulnerable groups for subsequent COVID-19 booster doses to minimise the risk of COVID-19 death.

Current definitions of advanced multimorbidity: a protocol for a scoping review.

INTRODUCTION: People living with and dying from multimorbidity are increasing in number, and ensuring quality care for this population is one of the major challenges facing healthcare providers. People with multimorbidity often have a high burden of palliative and end-of-life care needs, though they do not always access specialist palliative care services. A key reason for this is that they are often not identified as being in the last stages of their life by current healthcare providers and systems.This scoping review aims to identify and present the available evidence on how people with multimorbidity are currently included in research, policy and clinical practice. METHODS AND ANALYSIS: Scoping review methodology, based on Arksey and O'Malley's framework, will be undertaken and presented using the Preferred Reporting Items for Systematic Review and Meta-Analyses extension for Scoping Reviews. Search terms have been generated using the key themes of 'multimorbidity', 'end of life' and 'palliative care'. Peer-reviewed research will be obtained through systematic searching of Medline, EMBASE, CINAHL, Scopus and PsycINFO. Grey literature will be searched in a systematic manner. Literature containing a definition for adults with multimorbidity in a terminal phase of their illness experience will be included. After screening studies for eligibility, included studies will be described in terms of setting and characteristics as well as using inductive content analysis to highlight the commonalities in definitions. ETHICS AND DISSEMINATION: Ethical approval is not required for this scoping review. The findings of the scoping review will be used internally as part of SPB's PhD thesis at the University of St Andrews through the Multimorbidity Doctoral Training Programme for Health Professionals, which is supported by the Wellcome Trust (223499/Z/21/Z) and published in an open access, peer-reviewed journal for wider dissemination.

Clustering long-term health conditions among 67728 people with multimorbidity using electronic health records in Scotland.

There is still limited understanding of how chronic conditions co-occur in patients with multimorbidity and what are the consequences for patients and the health care system. Most reported clusters of conditions have not considered the demographic characteristics of these patients during the clustering process. The study used data for all registered patients that were resident in Fife or Tayside, Scotland and aged 25 years or more on 1st January 2000 and who were followed up until 31st December 2018. We used linked demographic information, and secondary care electronic health records from 1st January 2000. Individuals with at least two of the 31 Elixhauser Comorbidity Index conditions were identified as having multimorbidity. Market basket analysis was used to cluster the conditions for the whole population and then repeatedly stratified by age, sex and deprivation. 318,235 individuals were included in the analysis, with 67,728 (21·3%) having multimorbidity. We identified five distinct clusters of conditions in the population with multimorbidity: alcohol misuse, cancer, obesity, renal failure, and heart failure. Clusters of long-term conditions differed by age, sex and socioeconomic deprivation, with some clusters not present for specific strata and others including additional conditions. These findings highlight the importance of considering demographic factors during both clustering analysis and intervention planning for individuals with multiple long-term conditions. By taking these factors into account, the healthcare system may be better equipped to develop tailored interventions that address the needs of complex patients.

Adverse events after first and second doses of COVID-19 vaccination in England: a national vaccine surveillance platform self-controlled case series study.

OBJECTIVES: To estimate the incidence of adverse events of interest (AEIs) after receiving their first and second doses of coronavirus disease 2019 (COVID-19) vaccinations, and to report the safety profile differences between the different COVID-19 vaccines. DESIGN: We used a self-controlled case series design to estimate the relative incidence (RI) of AEIs reported to the Oxford-Royal College of General Practitioners national sentinel network. We compared the AEIs that occurred seven days before and after receiving the COVID-19 vaccinations to background levels between 1 October 2020 and 12 September 2021. SETTING: England, UK. PARTICIPANTS: Individuals experiencing AEIs after receiving first and second doses of COVID-19 vaccines. MAIN OUTCOME MEASURES: AEIs determined based on events reported in clinical trials and in primary care during post-license surveillance. RESULTS: A total of 7,952,861 individuals were vaccinated with COVID-19 vaccines within the study period. Among them, 781,200 individuals (9.82%) presented to general practice with 1,482,273 AEIs. Within the first seven days post-vaccination, 4.85% of all the AEIs were reported. There was a 3-7% decrease in the overall RI of AEIs in the seven days after receiving both doses of Pfizer-BioNTech BNT162b2 (RI = 0.93; 95% CI: 0.91-0.94) and 0.96; 95% CI: 0.94-0.98), respectively) and Oxford-AstraZeneca ChAdOx1 (RI = 0.97; 95% CI: 0.95-0.98) for both doses), but a 20% increase after receiving the first dose of Moderna mRNA-1273 (RI = 1.20; 95% CI: 1.00-1.44)). CONCLUSIONS: COVID-19 vaccines are associated with a small decrease in the incidence of medically attended AEIs. Sentinel networks could routinely report common AEI rates, which could contribute to reporting vaccine safety.

Maternal multimorbidity and preterm birth in Scotland: an observational record-linkage study.

BACKGROUND: Multimorbidity is common in women across the life course. Preterm birth is the single biggest cause of neonatal mortality and morbidity. We aim to estimate the prevalence of multimorbidity in pregnant women and to examine the association between maternal multimorbidity and PTB. METHODS: This is a retrospective cohort study using electronic health records from the Scottish Morbidity Records. All pregnancies among women aged 15 to 49 with a conception date between 1 January 2014 and 31 December 2018 were included. Multimorbidity was defined as the presence of two or more pre-existing long-term physical or mental health conditions, and complex multimorbidity as the presence of four or more. It was calculated at the time of conception using a predefined list of 79 conditions published by the MuM-PreDiCT consortium. PTB was defined as babies born alive between 24 and less than 37 completed weeks of gestation. We used Generalised Estimating Equations adjusted for maternal age, socioeconomic status, number of previous pregnancies, BMI, and smoking history to estimate the effect of maternal pre-existing multimorbidity. Absolut rates are reported in the results and tables, whilst Odds Ratios (ORs) are adjusted (aOR). RESULTS: Thirty thousand five hundred fifty-seven singleton births from 27,711 pregnant women were included in the analysis. The prevalence of pre-existing multimorbidity and complex multimorbidity was 16.8% (95% CI: 16.4-17.2) and 3.6% (95% CI: 3.3-3.8), respectively. The prevalence of multimorbidity in the youngest age group was 10.2%(95% CI: 8.8-11.6), while in those 40 to 44, it was 21.4% (95% CI: 18.4-24.4), and in the 45 to 49 age group, it was 20% (95% CI: 8.9-31.1). In women without multimorbidity, the prevalence of PTB was 6.7%; it was 11.6% in women with multimorbidity and 15.6% in women with complex multimorbidity. After adjusting for maternal age, socioeconomic status, number of previous pregnancies, Body Mass Index (BMI), and smoking, multimorbidity was associated with higher odds of PTB (aOR = 1.64, 95% CI: 1.48-1.82). CONCLUSIONS: Multimorbidity at the time of conception was present in one in six women and was associated with an increased risk of preterm birth. Multimorbidity presents a significant health burden to women and their offspring. Routine and comprehensive evaluation of women with multimorbidity before and during pregnancy is urgently needed.

Thrombocytopenic, thromboembolic and haemorrhagic events following second dose with BNT162b2 and ChAdOx1: self-controlled case series analysis of the English national sentinel cohort.

Background: Thrombosis associated with thrombocytopenia was a matter of concern post first and second doses of BNT162b2 and ChAdOx1 COVID-19 vaccines. Therefore, it is important to investigate the risk of thrombocytopenic, thromboembolic and haemorrhagic events following a second dose of BNT162b2 and ChAdOx1 COVID-19 vaccines. Methods: We conducted a large-scale self-controlled case series analysis, using routine primary care data linked to hospital data, among 12.3 million individuals (16 years old and above) in England. We used the nationally representative Oxford-Royal College of General Practitioners (RCGP) sentinel network database with baseline and risk periods between 8th December 2020 and 11th June 2022. We included individuals who received two vaccine (primary) doses of the BNT162b2 mRNA (Pfizer-BioNTech) and two vaccine doses of ChAdOx1 nCoV-19 (Oxford-AstraZeneca) vaccines in our analyses. We carried out a self-controlled case series (SCCS) analysis for each outcome using a conditional Poisson regression model with an offset for the length of risk period. We reported the incidence rate ratios (IRRs) and 95% confidence intervals (CI) of thrombocytopenic, thromboembolic (including arterial and venous events) and haemorrhagic events, in the period of 0-27 days after receiving a second dose of BNT162b2 or ChAdOx1 vaccines compared to the baseline period (14 or more days prior to first dose, 28 or more days after the second dose and the time between 28 or more days after the first and 14 or more days prior to the second dose). We adjusted for a range of potential confounders, including age, sex, comorbidities and deprivation. Findings: Between December 8, 2020 and February 11, 2022, 6,306,306 individuals were vaccinated with two doses of BNT162b2 and 6,046,785 individuals were vaccinated with two doses of ChAdOx1. Compared to the baseline, our analysis show no increased risk of venous thromboembolic events (VTE) for both BNT162b2 (IRR 0.71, 95% CI: 0.65-0.770) and ChAdOx1 (IRR 0.91, 95% CI: 0.84-0.98); and similarly there was no increased risk for cerebral venous sinus thrombosis (CVST) for both BNT162b2 (IRR 0.87, 95% CI: 0.41-1.85) and ChAdOx1 (IRR 1.73, 95% CI: 0.82-3.68). We additionally report no difference in IRR for pulmonary embolus, and deep vein thrombosis, thrombocytopenia, including idiopathic thrombocytopenic purpura (ITP), and haemorrhagic events post second dose for both BNT162b2. Interpretation: Reassuringly, we found no associations between increased risk of thrombocytopenic, thromboembolic and haemorrhagic events post vaccination with second dose for either of these vaccines. Funding: Data and Connectivity: COVID-19 Vaccines Pharmacovigilance study.

Effect on life expectancy of temporal sequence in a multimorbidity cluster of psychosis, diabetes, and congestive heart failure among 1·7 million individuals in Wales with 20-year follow-up: a retrospective cohort study using linked data.

BACKGROUND: To inform targeted public health strategies, it is crucial to understand how coexisting diseases develop over time and their associated impacts on patient outcomes and health-care resources. This study aimed to examine how psychosis, diabetes, and congestive heart failure, in a cluster of physical-mental health multimorbidity, develop and coexist over time, and to assess the associated effects of different temporal sequences of these diseases on life expectancy in Wales. METHODS: In this retrospective cohort study, we used population-scale, individual-level, anonymised, linked, demographic, administrative, and electronic health record data from the Wales Multimorbidity e-Cohort. We included data on all individuals aged 25 years and older who were living in Wales on Jan 1, 2000 (the start of follow-up), with follow-up continuing until Dec 31, 2019, first break in Welsh residency, or death. Multistate models were applied to these data to model trajectories of disease in multimorbidity and their associated effect on all-cause mortality, accounting for competing risks. Life expectancy was calculated as the restricted mean survival time (bound by the maximum follow-up of 20 years) for each of the transitions from the health states to death. Cox regression models were used to estimate baseline hazards for transitions between health states, adjusted for sex, age, and area-level deprivation (Welsh Index of Multiple Deprivation [WIMD] quintile). FINDINGS: Our analyses included data for 1 675 585 individuals (811 393 [48·4%] men and 864 192 [51·6%] women) with a median age of 51·0 years (IQR 37·0-65·0) at cohort entry. The order of disease acquisition in cases of multimorbidity had an important and complex association with patient life expectancy. Individuals who developed diabetes, psychosis, and congestive heart failure, in that order (DPC), had reduced life expectancy compared with people who developed the same three conditions in a different order: for a 50-year-old man in the third quintile of the WIMD (on which we based our main analyses to allow comparability), DPC was associated with a loss in life expectancy of 13·23 years (SD 0·80) compared with the general otherwise healthy or otherwise diseased population. Congestive heart failure as a single condition was associated with mean a loss in life expectancy of 12·38 years (0·00), and with a loss of 12·95 years (0·06) when preceded by psychosis and 13·45 years (0·13) when followed by psychosis. Findings were robust in people of older ages, more deprived populations, and women, except that the trajectory of psychosis, congestive heart failure, and diabetes was associated with higher mortality in women than men. Within 5 years of an initial diagnosis of diabetes, the risk of developing psychosis or congestive heart failure, or both, was increased. INTERPRETATION: The order in which individuals develop psychosis, diabetes, and congestive heart failure as combinations of conditions can substantially affect life expectancy. Multistate models offer a flexible framework to assess temporal sequences of diseases and allow identification of periods of increased risk of developing subsequent conditions and death. FUNDING: Health Data Research UK.

Intranasal steroid use and COVID-19 mortality among patients with asthma and COPD: A retrospective cohort study.

BACKGROUND: Systemic corticosteroids have been widely used for treating patients with severe acute respiratory distress syndrome. Inhaled corticosteroids may have a protective effect for treating acute coronavirus disease 2019 (COVID-19); however, little is known about the potential effect of intranasal corticosteroids (INCS) on COVID-19 outcomes and severity. OBJECTIVE: To assess the impact of prior long-term INCS exposure on COVID-19 mortality among patients with chronic respiratory disease and in the general population. METHODS: A retrospective cohort study was conducted. Cox regression models were used to estimate hazard ratios (HRs) and 95% confidence intervals (CIs) for the association between INCS exposure and all-cause and COVID-19 mortality, adjusted by age, sex, deprivation, exacerbations in the last year, and comorbidities. RESULTS: Exposure to INCS did not have a significant association with COVID-19 mortality among the general population or cohorts with chronic obstructive pulmonary disease or asthma, with HRs of 0.8 (95% CI, 0.6-1.0, P = .06), 0.6 (95% CI, 0.3-1.1, P = .1), and 0.9 (95% CI, 0.2-3.9, P = .9), respectively. Exposure to INCS was, however, significantly associated with reduction in all-cause mortality in all groups, which was 40% lower (HR, 0.6 [95% CI, 0.5-0.6, P < .001]) among the general population, 30% lower (HR, 0.7; 95% CI, 0.6-0.8, P < .001) among patients with chronic obstructive pulmonary disease, and 50% lower (HR, 0.5; 95% CI, 0.3-0.7, P = .003) among patients with asthma. CONCLUSION: The role of INCS in COVID-19 is still unclear, but exposure to INCS does not adversely affect COVID-19 mortality. Further studies are needed to explore the association between their use and inflammatory activation, viral load, angiotensin-converting enzyme 2 gene expression, and outcomes, exploring different types and doses of INCS.

Accelerated waning of the humoral response to COVID-19 vaccines in obesity.

Obesity is associated with an increased risk of severe Coronavirus Disease 2019 (COVID-19) infection and mortality. COVID-19 vaccines reduce the risk of serious COVID-19 outcomes; however, their effectiveness in people with obesity is incompletely understood. We studied the relationship among body mass index (BMI), hospitalization and mortality due to COVID-19 among 3.6 million people in Scotland using the Early Pandemic Evaluation and Enhanced Surveillance of COVID-19 (EAVE II) surveillance platform. We found that vaccinated individuals with severe obesity (BMI > 40 kg/m2) were 76% more likely to experience hospitalization or death from COVID-19 (adjusted rate ratio of 1.76 (95% confidence interval (CI), 1.60-1.94). We also conducted a prospective longitudinal study of a cohort of 28 individuals with severe obesity compared to 41 control individuals with normal BMI (BMI 18.5-24.9 kg/m2). We found that 55% of individuals with severe obesity had unquantifiable titers of neutralizing antibody against authentic severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus compared to 12% of individuals with normal BMI (P = 0.0003) 6 months after their second vaccine dose. Furthermore, we observed that, for individuals with severe obesity, at any given anti-spike and anti-receptor-binding domain (RBD) antibody level, neutralizing capacity was lower than that of individuals with a normal BMI. Neutralizing capacity was restored by a third dose of vaccine but again declined more rapidly in people with severe obesity. We demonstrate that waning of COVID-19 vaccine-induced humoral immunity is accelerated in individuals with severe obesity. As obesity is associated with increased hospitalization and mortality from breakthrough infections, our findings have implications for vaccine prioritization policies.

Prevalence of polypharmacy in pregnancy: a systematic review.

OBJECTIVES: The use of medications among pregnant women has been rising over the past few decades but the reporting of polypharmacy has been sporadic. The objective of this review is to identify literature reporting the prevalence of polypharmacy among pregnant women, the prevalence of multimorbidity in women taking multiple medications in pregnancy and associated effects on maternal and offspring outcomes. DESIGN: MEDLINE and Embase were searched from their inception to 14 September 2021 for interventional trials, observational studies and systematic reviews reporting on the prevalence of polypharmacy or the use of multiple medications in pregnancy were included.Data on prevalence of polypharmacy, prevalence of multimorbidity, combinations of medications and pregnancy and offspring outcomes were extracted. A descriptive analysis was performed. RESULTS: Fourteen studies met the review criteria. The prevalence of women being prescribed two or more medications during pregnancy ranged from 4.9% (4.3%-5.5%) to 62.4% (61.3%-63.5%), with a median of 22.5%. For the first trimester, prevalence ranged from 4.9% (4.7%-5.14%) to 33.7% (32.2%-35.1%). No study reported on the prevalence of multimorbidity, or associated pregnancy outcomes in women exposed to polypharmacy. CONCLUSION: There is a significant burden of polypharmacy among pregnant women. There is a need for evidence on the combinations of medications prescribed in pregnancy, how this specifically affects women with multiple long-term conditions and the associated benefits and harms. TWEETABLE ABSTRACT: Our systematic review shows significant burden of polypharmacy in pregnancy but outcomes for women and offspring are unknown. PROSPERO REGISTRATION NUMBER: CRD42021223966.

Radiomic analysis in contrast-enhanced mammography using a multivendor data set: accuracy of models according to segmentation techniques.

OBJECTIVE: Radiomic analysis of contrast-enhanced mammographic (CEM) images is an emerging field. The aims of this study were to build classification models to distinguish benign and malignant lesions using a multivendor data set and compare segmentation techniques. METHODS: CEM images were acquired using Hologic and GE equipment. Textural features were extracted using MaZda analysis software. Lesions were segmented with freehand region of interest (ROI) and ellipsoid_ROI. Benign/Malignant classification models were built using extracted textural features. Subset analysis according to ROI and mammographic view was performed. RESULTS: 269 enhancing mass lesions (238 patients) were included. Oversampling mitigated benign/malignant imbalance. Diagnostic accuracy of all models was high (>0.9). Segmentation with ellipsoid_ROI produced a more accurate model than with FH_ROI, accuracy:0.947 vs 0.914, AUC:0.974 vs 0.86, p < 0.05. Regarding mammographic view all models were highly accurate (0.947-0.955) with no difference in AUC (0.985-0.987). The CC-view model had the greatest specificity:0.962, the MLO-view and CC + MLO view models had higher sensitivity:0.954, p < 0.05. CONCLUSIONS: Accurate radiomics models can be built using a real-life multivendor data set segmentation with ellipsoid-ROI produces the highest level of accuracy. The marginal increase in accuracy using both mammographic views, may not justify the increased workload. ADVANCES IN KNOWLEDGE: Radiomic modelling can be successfully applied to a multivendor CEM data set, ellipsoid_ROI is an accurate segmentation technique and it may be unnecessary to segment both CEM views. These results will help further developments aimed at producing a widely accessible radiomics model for clinical use.