Severe Mental Illness as a risk factor for recorded diagnosis of osteoporosis and fragility fractures in people aged 50 and above: retrospective cohort study using UK primary care data.

BACKGROUND: Severe Mental Illness (SMI) has been associated with reduced bone density and increased risk of fractures, although some studies have shown inconsistent results. AIM: Examine the association between SMI and recorded diagnosis of osteoporosis (OP) and fragility fracture (FF) in people aged ≥50years. DESIGN AND SETTING: Population-based cohort study; UK Primary care. METHOD: We used anonymised primary care data (IQVIA Medical Research Database). Patients with a diagnosis of SMI aged 50-99y (2000-2018) were matched to individuals without SMI. We used Cox Proportional Hazards models to estimate Hazard Ratios (HR) and 95% Confidence Intervals (95%CI). We stratified analyses by sex and age, accounting for social deprivation, year, smoking, alcohol, and Body Mass Index (BMI). RESULTS: In total 444,480 people were included (SMI N=50,006; unexposed N=394,474). In men, diagnosis of SMI increased the likelihood of OP diagnosis, with differences mainly observed amongst the youngest (50-54y:HR=2.12;95%CI 1.61-2.79) and oldest (85-99y:HR=2.15;95%CI 1.05-4.37), and also increased the risk of FF across all ages. In women, SMI increased the risk of OP diagnosis only in those aged 50-54y:HR=1.16;95%CI 1.01-1.34, but increased the risk of FF across all ages. There were more than twice as many men with SMI with FF records than with OP diagnosis: FF:OP=2.10, compared to FF:OP=1.89 in men without SMI. The FF:OP ratio was 1.56 in women with SMI vs.1.11 in women without SMI. CONCLUSION: SMI is associated with increased likelihood of fragility fractures and osteoporosis underdiagnosis. Interventions should be considered to mitigate the increased risk of fractures in people with SMI.

Could primary care records be used to identify women at risk of perinatal anxiety? A mixed-methods study.

BACKGROUND: Perinatal anxiety (PNA) occurs throughout the antenatal period or up to 1 year after childbirth, with a prevalence of 21%. AIM: To investigate if primary care records could be used to identify women at 'higher risk' of PNA. METHOD: Mixed-methods approach using quantitative and qualitative methods. Quantitative data analysis used Clinical Practice Research Datalink and IQVIA Medical Research Data to identify risk factors for PNA. Interviews explored the lived experiences of women with PNA about predisposing factors for PNA and acceptability of being informed of risk; and perspectives of primary healthcare professionals and Voluntary, Community, and Social Enterprise practitioners about risk communication. Interviews were conducted online, digitally recorded with consent, transcribed, and anonymised prior to analysis. Data were thematically analysed. Patient and clinical advisory groups informed each stage of the research. RESULTS: Women reflected on both positive and negative impacts of being identified at higher risk of PNA, a lack of understanding of how primary care records are used, and who has access to them. All interview participants suggested predisposing factors that would not be coded in primary care records. Quantitative analysis demonstrated that some predisposing factors for PNA can be identified in a woman's primary care records. Initial analysis suggests associations between PNA and infant health and healthcare use. CONCLUSION: While identification of higher risk of PNA may be acceptable, some factors that may contribute to PNA are not coded in primary care records. Identifying and managing PNA is needed to improve infant health.

Panel stacking is a threat to consensus statement validity.

Consensus statements can be very influential in medicine and public health. Some of these statements use systematic evidence synthesis but others fail on this front. Many consensus statements use panels of experts to deduce perceived consensus through Delphi processes. We argue that stacking of panel members toward one particular position or narrative is a major threat, especially in absence of systematic evidence review. Stacking may involve financial conflicts of interest, but nonfinancial conflicts of strong advocacy can also cause major bias. Given their emerging importance, we describe here how such consensus statements may be misleading, by analyzing in depth a recent high-impact Delphi consensus statement on COVID-19 recommendations as a case example. We demonstrate that many of the selected panel members and at least 35% of the core panel members had advocated toward COVID-19 elimination (Zero-COVID) during the pandemic and were leading members of aggressive advocacy groups. These advocacy conflicts were not declared in the Delphi consensus publication, with rare exceptions. Therefore, we propose that consensus statements should always require rigorous evidence synthesis and maximal transparency on potential biases toward advocacy or lobbyist groups to be valid. While advocacy can have many important functions, its biased impact on consensus panels should be carefully avoided.

The first 100 days after childbirth: cross-sectional study of maternal clinical events and health needs from primary care.

BACKGROUND: The first 100 days after childbirth are important for women recovering from pregnancy and birth. AIM: To describe the most common clinical events or health needs documented in women's primary care records in the first 100 days after childbirth. DESIGN AND SETTING: Cross-sectional study using electronic health records from UK primary care data. METHOD: Primary care records were examined from childbirth up to 100 days after childbirth for women aged 16-49 years who had given birth to a single live infant between 2006 and 2016 using IQVIA Medical Research Data. The most common clinical events or health needs based on documented symptoms, diagnoses, and medications were identified. How these varied by patient characteristic was explored. RESULTS: In total, 925 712 contacts were identified during the 100 days following 309 573 births. Women were most likely to use primary care to have a postnatal visit or check (60.6%, n = 187 455), for monitoring (such as a blood pressure reading) (49.9%, n = 154 328), and to access contraception (49.7%, n = 153 876). Younger women were more likely to have contacts for preventive care compared with older women, but were less likely to have contacts for ongoing mental and physical symptoms or conditions and pre-existing conditions. The highest peak in contacts occurred 42 days after birth, and related to a postnatal check or visit, monitoring a patient, and recording lifestyle factors (such as smoking status). CONCLUSION: Primary care services should seek to match the needs of new mothers, taking account of a high volume of contacts, for a broad range of planned and responsive care following childbirth.

Associations between prior healthcare use, time to diagnosis, and clinical outcomes in inflammatory bowel disease: a nationally representative population-based cohort study.

BACKGROUND: Timely diagnosis and treatment of inflammatory bowel disease (IBD) may improve clinical outcomes. OBJECTIVE: Examine associations between time to diagnosis, patterns of prior healthcare use, and clinical outcomes in IBD. DESIGN: Using the Clinical Practice Research Datalink we identified incident cases of Crohn's disease (CD) and ulcerative colitis (UC), diagnosed between January 2003 and May 2016, with a first primary care gastrointestinal consultation during the 3-year period prior to IBD diagnosis. We used multivariable Cox regression to examine the association of primary care consultation frequency (n=1, 2, >2), annual consultation intensity, hospitalisations for gastrointestinal symptoms, and time to diagnosis with a range of key clinical outcomes following diagnosis. RESULTS: We identified 2645 incident IBD cases (CD: 782; UC: 1863). For CD, >2 consultations were associated with intestinal surgery (adjusted HR (aHR)=2.22, 95% CI 1.45 to 3.39) and subsequent CD-related hospitalisation (aHR=1.80, 95% CI 1.29 to 2.50). For UC, >2 consultations were associated with corticosteroid dependency (aHR=1.76, 95% CI 1.28 to 2.41), immunomodulator use (aHR=1.68, 95% CI 1.24 to 2.26), UC-related hospitalisation (aHR=1.43, 95% CI 1.05 to 1.95) and colectomy (aHR=2.01, 95% CI 1.22 to 3.27). For CD, hospitalisation prior to diagnosis was associated with CD-related hospitalisation (aHR=1.30, 95% CI 1.01 to 1.68) and intestinal surgery (aHR=1.71, 95% CI 1.13 to 2.58); for UC, it was associated with immunomodulator use (aHR=1.42, 95% CI 1.11 to 1.81), UC-related hospitalisation (aHR=1.36, 95% CI 1.06 to 1.95) and colectomy (aHR=1.54, 95% CI 1.01 to 2.34). For CD, consultation intensity in the year before diagnosis was associated with CD-related hospitalisation (aHR=1.19, 95% CI 1.12 to 1.28) and intestinal surgery (aHR=1.13, 95% CI 1.03 to 1.23); for UC, it was associated with corticosteroid use (aHR=1.08, 95% CI 1.04 to 1.13), corticosteroid dependency (aHR=1.05, 95% CI 1.00 to 1.11), and UC-related hospitalisation (aHR=1.12, 95% CI 1.03 to 1.21). For CD, time to diagnosis was associated with risk of CD-related hospitalisation (aHR=1.03, 95% CI 1.01 to 1.68); for UC, it was associated with reduced risk of UC-related hospitalisation (aHR=0.83, 95% CI 0.70 to 0.98) and colectomy (aHR=0.59, 95% CI 0.43 to 0.80). CONCLUSION: Electronic records contain valuable information about patterns of healthcare use that can be used to expedite timely diagnosis and identify aggressive forms of IBD.

Exploring the co-occurrence of depression, anxiety and insomnia symptoms, diagnoses and treatments in primary care: observational study using UK primary care data.

BACKGROUND: Depression, anxiety and insomnia often co-occur. However, there is a lack of research regarding how they cluster and how this is related to medication used to treat them. AIMS: To describe the frequencies and associations between depression, anxiety and insomnia, and treatment for these conditions in primary care. METHOD: A retrospective cohort study using UK electronic primary care records. We included individuals aged between 18 and 99 years old with one or more records suggesting they had a diagnosis, symptom or drug treatment for anxiety, depression or insomnia between 2015 and 2017. We report the conditional probabilities of having different combinations of diagnoses, symptoms and treatments recorded. RESULTS: There were 1 325 960 records indicative of depression, anxiety or insomnia, for 739 834 individuals. Depression was the most common condition (n = 106 117 records), and SSRIs were the most commonly prescribed medication (n = 347 751 records). Overall, individuals with a record of anxiety were most likely to have co-occurring symptoms and diagnoses of other mental health conditions. For example, of the individuals with a record of generalised anxiety disorder (GAD), 24% also had a diagnosis of depression. In contrast, only 0.6% of those who had a diagnosis of depression had a diagnosis or symptom of GAD. Prescribing of more than one psychotropic medication within the same year was common. For example, of those who were prescribed an SNRI (serotonin-norepinephrine reuptake inhibitor), 40% were also prescribed an SSRI (selective serotonin reuptake inhibitor). CONCLUSIONS: The conditional probabilities of co-occurring anxiety, depression and insomnia symptoms, diagnoses and treatments are high.

Risk of Parkinson's disease in people aged ≥50 years with new-onset anxiety: a retrospective cohort study in UK primary care.

BACKGROUND: A history of anxiety is more common in people with Parkinson's disease (PD). The prospective risk of PD in those newly presenting with anxiety and factors that increase the risk of PD in patients with anxiety have not been investigated. AIM: To investigate the incidence of PD in people with anxiety aged ≥50 years and clinical features associated with later diagnosis of PD in people with anxiety. DESIGN AND SETTING: A retrospective cohort study using UK primary care data between 2008 and 2018, assessing patients with new-onset anxiety aged ≥50 years. METHOD: Weibull survival regression models were fitted and hazard ratios (HRs) for modelling time-to-PD was estimated in those with and without anxiety, and when determining the risk of developing PD in those with anxiety. Results were adjusted for sociodemographic and lifestyle factors, and relevant physical and mental health conditions. RESULTS: The risk of PD increased two-fold compared with the non-anxiety group after adjustment for age, sex, social deprivation, lifestyle factors, severe mental illness, head trauma, and dementia (HR 2.1, 95% confidence interval = 1.9 to 2.4). In those with anxiety, the presence of depression, hypotension, tremor, rigidity, balance impairment, constipation, sleep disturbance, fatigue, and cognitive impairment were associated with an increased risk of developing PD. CONCLUSION: The risk of developing PD was at least doubled in people with anxiety compared with those without. The clinical features of those who developed PD can help identify patients presenting with anxiety who are in the prodromal phase of PD.

Ethnicity data resource in population-wide health records: completeness, coverage and granularity of diversity.

Intersectional social determinants including ethnicity are vital in health research. We curated a population-wide data resource of self-identified ethnicity data from over 60 million individuals in England primary care, linking it to hospital records. We assessed ethnicity data in terms of completeness, consistency, and granularity and found one in ten individuals do not have ethnicity information recorded in primary care. By linking to hospital records, ethnicity data were completed for 94% of individuals. By reconciling SNOMED-CT concepts and census-level categories into a consistent hierarchy, we organised more than 250 ethnicity sub-groups including and beyond "White", "Black", "Asian", "Mixed" and "Other, and found them to be distributed in proportions similar to the general population. This large observational dataset presents an algorithmic hierarchy to represent self-identified ethnicity data collected across heterogeneous healthcare settings. Accurate and easily accessible ethnicity data can lead to a better understanding of population diversity, which is important to address disparities and influence policy recommendations that can translate into better, fairer health for all.

Estimating life expectancy and years of life lost for autistic people in the UK: a matched cohort study.

Background: Previous research has shown that people who have been diagnosed autistic are more likely to die prematurely than the general population. However, statistics on premature mortality in autistic people have often been misinterpreted. In this study we aimed to estimate the life expectancy and years of life lost experienced by autistic people living in the UK. Methods: We studied people in the IQVIA Medical Research Database with an autism diagnosis between January 1, 1989 and January 16, 2019. For each participant diagnosed autistic, we included ten comparison participants without an autism diagnosis, matched by age, sex, and primary care practice. We calculated age- and sex-standardised mortality ratios comparing people diagnosed autistic to the reference group. We used Poisson regression to estimate age-specific mortality rates, and life tables to estimate life expectancy at age 18 and years of life lost. We analysed the data separately by sex, and for people with and without a record of intellectual disability. We discuss the findings in the light of the prevalence of recorded diagnosis of autism in primary care compared to community estimates. Findings: From a cohort of nearly 10 million people, we identified 17,130 participants diagnosed autistic without an intellectual disability (matched with 171,300 comparison participants), and 6450 participants diagnosed autistic with an intellectual disability (matched with 64,500 comparison participants). The apparent estimates indicated that people diagnosed with autism but not intellectual disability had 1.71 (95% CI: 1.39-2.11) times the mortality rate of people without these diagnoses. People diagnosed with autism and intellectual disability had 2.83 (95% CI: 2.33-3.43) times the mortality rate of people without these diagnoses. Likewise, the apparent reduction in life expectancy for people diagnosed with autism but not intellectual disability was 6.14 years (95% CI: 2.84-9.07) for men and 6.45 years (95% CI: 1.37-11.58 years) for women. The apparent reduction in life expectancy for people diagnosed with autism and intellectual disability was 7.28 years (95% CI: 3.78-10.27) for men and 14.59 years (95% CI: 9.45-19.02 years) for women. However, these findings are likely to be subject to exposure misclassification biases: very few autistic adults and older-adults have been diagnosed, meaning that we could only study a fraction of the total autistic population. Those who have been diagnosed may well be those with greater support needs and more co-occurring health conditions than autistic people on average. Interpretation: The findings indicate that there is a group of autistic people who experience premature mortality, which is of significant concern. There is an urgent need for investigation into the reasons behind this. However, our estimates suggest that the widely reported statistic that autistic people live 16-years less on average is likely incorrect. Nine out of 10 autistic people may have been undiagnosed across the time-period studied. Hence, the results of our study do not generalise to all autistic people. Diagnosed autistic adults, and particularly older adults, are likely those with greater-than-average support needs. Therefore, we may have over-estimated the reduction in life expectancy experienced by autistic people on average. The larger reduction in life expectancy for women diagnosed with autism and intellectual disability vs. men may in part reflect disproportionate underdiagnosis of autism and/or intellectual disability in women. Funding: Dunhill Medical Trust, Medical Research Council, National Institute for Health and Care Research, and the Royal College of Psychiatrists.

Understanding the impact of non-shared unmeasured confounding on the sibling comparison analysis.

BACKGROUND: The sibling comparison analysis is used to deal with unmeasured confounding. It has previously been shown that in the presence of non-shared unmeasured confounding, the sibling comparison analysis may introduce substantial bias depending on the sharedness of the unmeasured confounder and the sharedness of the exposure. We aimed to improve the awareness of this challenge of the sibling comparison analysis. METHODS: First, we simulated sibling pairs with an exposure, a confounder and an outcome. We simulated sibling pairs with no effect of the exposure on the outcome and with positive confounding. For varying degrees of sharedness of the confounder and the exposure and for varying prevalence of the exposure, we calculated the sibling comparison odds ratio (OR). Second, we provided measures for sharedness of selected treatments based on Danish health data. RESULTS: The confounded sibling comparison OR was visualized for varying degrees of sharedness of the confounder and the exposure and for varying prevalence of the exposure. The confounded sibling comparison OR was seen to increase with increasing sharedness of the exposure and the confounded sibling comparison OR decreased with an increasing prevalence of exposure. Measures for sharedness of treatments based on Danish health data showed that treatments of chronic diseases have the highest sharedness and treatments of non-chronic diseases have the lowest sharedness. CONCLUSIONS: Researchers should be aware of the challenge regarding non-shared unmeasured confounding in the sibling comparison analysis, before applying the analysis in non-randomized studies. Otherwise, the sibling comparison analysis may lead to substantial bias.

Clinical effectiveness of pharmacological and non-pharmacological treatments for the management of anxiety in community dwelling people living with dementia: A systematic review and meta-analysis.

People living with dementia commonly experience anxiety, which is often challenging to manage. We investigated the effectiveness of treatments for the management of anxiety in this population. We conducted a systematic review and meta-analysis of randomised controlled trials, and searched EMBASE, CINAHL, MEDLINE and PsycInfo. We estimated standardised mean differences at follow-up between treatments relative to control groups and pooled these across studies using random-effects models where feasible. Thirty-one studies were identified. Meta-analysis demonstrated non-pharmacological interventions were effective in reducing anxiety in people living with dementia, compared to care as usual or active controls. Specifically, music therapy (SMD-1.92(CI:-2.58,-1.25)), muscular approaches (SMD-0.65(CI:-1.02,-0.28)) and stimulating cognitive and physical activities (SMD-0.31(CI:-0.53,-0.09)). Pharmacological interventions with evidence of potential effectiveness included Ginkgo biloba, probiotics, olanzapine, loxapine and citalopram compared to placebo, olanzapine compared to bromazepam and buspirone and risperidone compared to haloperidol. Meta-analyses were not performed for pharmacological interventions due to studies' heterogeneity. This has practice implications when promoting the use of more non-pharmacological interventions to help reduce anxiety among people living with dementia.