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Patients with active inflammatory bowel disease (IBD) and mental illnesses experience worse IBD outcomes.To describe the incidence of mental illnesses, including deliberate self-harm, in IBD patients.A population-based retrospective cohort study using IQVIA medical research data of a primary care database covering the whole UK, between January 1995 and January 2021. IBD patients of all ages were matched 4:1 by demographics and primary care practice to unexposed controls. Following exclusion of patients with mental ill health at study entry, adjusted hazard ratios (HR) of developing depression, anxiety, deliberate self-harm, severe mental illness and insomnia were calculated using a Cox proportional hazards model.We included 48,799 incident IBD patients: 28,352 with ulcerative colitis and 20,447 with Crohn's disease. Incidence rate ratios of mental illness were higher in IBD patients than controls (all p 0.001): deliberate self-harm 1.31 (95% CI 1.16-1.47), anxiety 1.17 (1.11-1.24), depression 1.36 (1.31-1.42) and insomnia 1.62 (1.54-1.69). Patients with Crohn's disease were more likely to develop deliberate self-harm HR 1.51 (95% CI 1.28-1.78), anxiety 1.38 (1.16-1.65), depression 1.36 (1.26-1.47) and insomnia 1.74 (1.62-1.86). Patients with IBD are at increased risk of deliberate self-harm (HR 1.20 [1.07-1.35]). The incidence rate ratios of mental illnesses were particularly high during the first year following IBD diagnosis: anxiety 1.28 (1.13-1.46), depression 1.62 (1.48-1.77) and insomnia 1.99 (1.78-2.21).Deliberate self-harm, depression, anxiety and insomnia were more frequent among patients with IBD. IBD is independently associated with an increased risk of deliberate self-harm.

Background/ObjectivesPatients with referable diabetic retinopathy are treated or regularly observed for the need and timing of treatment and to prevent vision loss under hospital eye service/surveillance clinics. A small proportion progress, but presently there is no mechanism to easily identify these patients at higher risk of the outcome in this population. We aimed to develop and internally validate a risk prediction model for progression of retinopathy in patients with referable diabetic retinopathy population.Methods Anonymized data on 13,691 patients with diabetes joining the IQVIA Medical Research database (a structured primary care routine practice database with over 15 million patient records) from 2004 to 2018 were used to fit a Cox regression model. We used backward elimination with p< 0.2 to select predictors. Internal validation was performed using bootstrapping. Predictive performance was evaluated using the C-statistic and D statistic for discrimination as well as assessing calibration using the calibration slope and calibration plot at 5 years.ResultsThere were a total of 2079 outcome events in our dataset. The prediction model included Diabetic Retinopathy stage, eGFR, HbA1c, Cholesterol, systolic blood pressure, Insulin and Statin as final predictors, retinopathy stage being the strongest. The model had good discrimination (C-statistic=0.74) and very little optimism in the internal validation due to the large sample size.ConclusionThis new algorithm can calculate the absolute risk of progression from referable retinopathy based on an individual’s risk factors. External validation and net clinical benefit analysis will be required before use in clinical practice.

IntroductionThe number of people with diabetes mellitus is increasing globally and consequently so too is diabetic retinopathy (DR). Most patients with diabetes are monitored through the diabetic eye screening programme (DESP) until they have signs of retinopathy and these changes progress, requiring referral into hospital eye services (HES). Here, they continue to be monitored until they require treatment. Due to current pressures on HES, delays can occur, leading to harm. There is a need to triage patients based on their individual risk. At present, patients are stratified according to retinopathy stage alone, yet other risk factors like glycated haemoglobin (HbA1c) may be useful. Therefore, a prediction model that combines multiple prognostic factors to predict progression will be useful for triage in this setting to improve care.We previously developed a Diabetic Retinopathy Progression model to Treatment or Vision Loss (DRPTVL-UK) using a large primary care database. The aim of the present study is to externally validate the DRPTVL-UK model in a secondary care setting, specifically in a population under care by HES. This study will also provide an opportunity to update the model by considering additional predictors not previously available.Methods and analysisWe will use a retrospective cohort of 2400 patients with diabetes aged 12 years and over, referred from DESP to the NHS hospital trusts with referable DR between 2013 and 2016, with follow-up information recorded until December 2021.We will evaluate the external validity of the DRPTVL-UK model using measures of discrimination, calibration and net benefit. In addition, consensus meetings will be held to agree on acceptable risk thresholds for triage within the HES system.Ethics and disseminationThis study was approved by REC (ref 22/SC/0425, 05/12/2022, Hampshire A Research Ethics Committee). The results of the study will be published in a peer-reviewed journal, presented at clinical conferences.Trial Registration numberISRCTN 10956293.

As the SARS-CoV-2 virus (COVID-19) continues to affect people across the globe, there is limited understanding of the long term implications for infected patients1–3. While some of these patients have documented follow-ups on clinical records, or participate in longitudinal surveys, these datasets are usually designed by clinicians, and not granular enough to understand the natural history or patient experiences of ‘long COVID’. In order to get a complete picture, there is a need to use patient generated data to track the long-term impact of COVID-19 on recovered patients in real time. There is a growing need to meticulously characterize these patients’ experiences, from infection to months post-infection, and with highly granular patient generated data rather than clinician narratives. In this work, we present a longitudinal characterization of post-COVID-19 symptoms using social media data from Twitter. Using a combination of machine learning, natural language processing techniques, and clinician reviews, we mined 296,154 tweets to characterize the post-acute infection course of the disease, creating detailed timelines of symptoms and conditions, and analyzing their symptomatology during a period of over 150 days.

We aimed to evaluate adjusted hazard ratio (aHR) for new-onset headache as well as headache medi- cation prescribing, opiate use and headache burden in women with idiopathic intracranial hypertension (IIH) compared to matched women with migraine and population controls.Data from IQVIA Medical Research Data, an anonymised, nationally representative UK database, from January-1995 to September-2019, was used. Women with IIH were matched by age and body mass index with women without IIH with migraine (migraine controls), and women without IIH or migraine (popula- tion controls).3411 IIH patients, 30,879 migraine and 33,495 population controls were included. aHR for new onset headache in IIH compared to population controls was 3.09 (95%-confidence interval=2.78-3.43). In the first year post-diagnosis, 58% of IIH patients were prescribed acetazolamide and 20% topiramate. 20% of IIH patients were prescribed opiates within the first year of diagnosis, reducing to 17% after six years. In migraine, 8% and 11% were prescribed opiates within one year and six years post-diagnosis, respec- tively. More headache preventative medications were prescribed in IIH compared to migraine controls.Opiate and simple analgesics are more likely to be prescribed in IIH, with patients trialling more preven- tative medications compared to controls, suggesting headaches may be more refractory to treatment.

Incidence rates for depression and anxiety has not been previously evaluated in a large matched cohort study in idiopathic intracranial hypertension (IIH).We analysed data collected between January-1995 and September-2019 from IQVIA Medical Research Data, an anonymised and nationally representative UK database. Crude incident rates for depression and anxiety were calculated in IIH, migraine controls and population controls matched by age and body mass index (BMI). Cox proportional hazards regression was used to calculate hazard ratios (HR) and 95% confidence intervals (CI).Anxiety incidence was 12.4, 12.6 and 8.2 per 1000 person-years in IIH, migraine and controls, respectively. For IIH, the adjusted HR for anxiety was 1.40 (CI=1.19-1.64) compared to controls, and 0.98 (CI=0.83-1.14) compared to migraine. Depression incidence was 20.1, 19.5 and 13.3 per 1000 person-years in IIH, migraine and controls, respectively. Compared to controls, depression adjusted HR in IIH was 1.38 (CI 1.20-1.58); compared to migraine, adjusted HR was 0.98 (CI 0.86-1.13).Anxiety and depression are not more common in IIH compared to matched migraine population, but the hazard of anxiety and depression was approximately 40% higher compared to healthy age and BMI-matched controls. Physician recognition and management of this co-morbidity is an unmet clinical need in IIH.

ObjectivesOphthalmic conditions including anterior uveitis (AU), episcleritis and scleritis may occur in association with the inflammatory bowel diseases (IBD) as ophthalmic extraintestinal manifestations. The aim of this study was to assess the risk of a later IBD diagnosis in those presenting with IBD associated ocular inflammation (IAOI).DesignRetrospective cohort study.SettingPrimary care UK database.Participants38 805 subjects with an IAOI were identified (median age 51 (38–65), 57% women) and matched to 153 018 subjects without IAOI.MeasuresThe risk of a subsequent diagnosis of IBD in subjects with IAOIs compared with age/sex matched subjects without IAOI. HRs were adjusted for age, sex, body mass index, deprivation, comorbidity, smoking, baseline axial arthropathy, diarrhoea, loperamide prescription, anaemia, lower gastrointestinal bleeding and abdominal pain.Logistic regression was used to produce a prediction model for a diagnosis of IBD within 3 years of an AU diagnosis.Results213 (0.6%) subsequent IBD diagnoses (102 ulcerative colitis (UC) and 111 Crohn’s disease (CD)) were recorded in those with IAOIs and 329 (0.2%) (215 UC and 114 CD) in those without. Median time to IBD diagnosis was 882 (IQR 365–2043) days in those with IAOI and 1403 (IQR 623–2516) in those without. The adjusted HR for a subsequent diagnosis of IBD was 2.25 (95% CI 1.89 to 2.68), pWithin 3 years of an AU diagnosis, 84 (0.5%) subjects had a recorded diagnosis of IBD. The prediction model performed well with a C-statistic of 0.75 (95% CI 0.69 to 0.80).ConclusionsSubjects with IAOI have a twofold increased risk of a subsequent IBD diagnosis. Healthcare professionals should be alert for potential signs and symptoms of IBD in those presenting with ophthalmic conditions associated with IBD.

No single value of BAL lymphocyte % in fibrotic hypersensitivity pneumonitis will be diagnostic for all, and it must be considered in the context of other clinical, radiological and histopathological featureshttps://bit.ly/3qSwUDo

BackgroundThe role of bronchoalveolar lavage fluid (BALF) lymphocyte percentage in diagnosing chronic hypersensitivity pneumonitis (CHP) is unclear. We conducted a systematic review and meta-analysis of bronchoalveolar lavage (BAL) lymphocyte percentage in the diagnosis of CHP.MethodsWe searched Medline, Embase and the Cochrane Library from inception to August 2019. Individual patient data were obtained to test performance characteristics of BAL lymphocyte percentage at different thresholds. Random-effects models were used for pooled estimates, with comparisons made between CHP and non-CHP interstitial lung diseases (ILDs).ResultsFifty-three studies were included in the systematic review and 42 in the meta-analysis. The pooled estimate for BAL lymphocyte percentage was 42.8% (95% CI 37.7–47.8, I2=95.3%) in CHP, 10.0% (95% CI 6.9–13.1, I2=91.2%) in idiopathic pulmonary fibrosis (IPF), 23.1% (95% CI 3.0–43.2, I2=85.2%) in non-IPF idiopathic interstitial pneumonia (IIP), 23.4% (95% CI 11.0–35.9, I2=45.7%) in connective-tissue disease associated ILD (CTD-ILD) and 31.2% (95% CI 17.6–44.8, I2=95.2%) in sarcoidosis. Results differed between CHP and IPF (p20% provided a sensitivity of 68.1% and a specificity of 64.8% for CHP. Higher thresholds provided lower sensitivity with higher specificity. Older age and ever having smoked were associated with lower lymphocyte percentage in CHP.ConclusionsBAL lymphocyte percentage is higher in CHP compared to IPF and other IIPs, with higher thresholds providing improved specificity at the cost of sensitivity. However, the parent studies are at risk of incorporation bias and prospective studies should evaluate the additive discriminate value of BAL lymphocyte percentage to accurately diagnose CHP.