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Aims: To identify individuals with incidental fatty liver disease (FLD), and to evaluate its prevalence, metabolic co-morbidities and impact on follow-up., Methods: We leveraged the data-lake of Helsinki Uusimaa Hospital district (Finland) with a population of 1.7 million (specialist and primary care). A phrase recognition script on abdominal imaging reports (2008-2020) identified/excluded FLD or cirrhosis; we extracted ICD-codes, laboratory and BMI data., Results: Excluding those with other liver diseases, the prevalence of FLD was 29% (steatosis yes/no, N=61,271/155,521; cirrhosis, N=3502). The false positive and negative rates were 5-6%. Only 1.6% of the FLD cases had the ICD code recorded and 32% had undergone full clinical evaluation for associated co-morbidities. Of the 35-65-year-old individuals with FLD, 20% had diabetes, 42% prediabetes and 28% a high liver fibrosis index. FLD was independently predicted by diabetes (OR 1.56, CI 1.46-1.66, p = 2.3 * 10^-41), BMI (1.46, 1.42-1.50, p = 1.7 * 10^-154) and plasma triglyceride level (1.5, 1.43-1.57, p = 3.5 * 10^-68). Alanine aminotransferase level mildly increased (1.12, 1.08-1.16, p = 2.2 * 10^-9) and high age decreased the risk (0.92, 0.89-0.94, p = 4.65*10^-09). Half of the cases had normal ALT., Conclusions: The incidental radiological finding of FLD is reliable and associated with metabolic risks but largely ignored, although it should lead to metabolic and hepatic follow-up., Competing Interests: Declaration of competing interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: IK has previously worked in the administration of a private health care concern Mehiläinen and has received lecture fees from Novo Nordisk and Astra Zeneca and has received support concerning congress travel costs and participation fees from Bayer and Novo Nordisk. SK received consultancy fees from Pfizer during 2019-2020. SK received consultancy fees from Pfizer during 2019-2020. Other authors have no competing interests to declare., (Copyright © 2024. Published by Elsevier B.V.)

Background: Different barriers that hinder migrants' access to healthcare may have detrimental effect on health but also contribute to health inequalities. Given the lack of evidence on unmet healthcare needs among European migrant population, the study aimed to analyse the demographic, socio-economic and health-related patterning of unmet healthcare needs among migrants in Europe., Methods: European Health Interview Survey data from 2013-2015 covering 26 countries was used to analyse associations of individual-level factors and unmet healthcare needs among migrants (n = 12,817). Prevalences and 95% confidence intervals for unmet healthcare needs were presented for geographical regions and countries. Associations between unmet healthcare needs and demographic, socio-economic, and health indicators were analysed using Poisson regression models., Results: The overall prevalence of unmet healthcare needs among migrants was 27.8% (95% CI 27.1-28.6) but the estimate varied substantially across geographical regions in Europe. Unmet healthcare needs due to cost or access were patterned by various demographic, socio-economic, and health-related indicators but higher prevalence of UHN were universally found for women, those with the lowest income, and poor health., Conclusions: While the high level of unmet healthcare needs illustrate migrants' vulnerability to health risks, the regional variations in the prevalence estimates and individual-level predictors highlight the variations in national policies regarding migration and healthcare legislations and differences in welfare-systems across Europe in general., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2023 Kullamaa, Reile. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Background: Identification of rheumatoid arthritis (RA) patients at high risk of adverse health outcomes remains a major challenge. We aimed to develop and validate prediction models for a variety of adverse health outcomes in RA patients initiating first-line methotrexate (MTX) monotherapy., Methods: Data from 15 claims and electronic health record databases across 9 countries were used. Models were developed and internally validated on Optum® De-identified Clinformatics® Data Mart Database using L1-regularized logistic regression to estimate the risk of adverse health outcomes within 3 months (leukopenia, pancytopenia, infection), 2 years (myocardial infarction (MI) and stroke), and 5 years (cancers [colorectal, breast, uterine] after treatment initiation. Candidate predictors included demographic variables and past medical history. Models were externally validated on all other databases. Performance was assessed using the area under the receiver operator characteristic curve (AUC) and calibration plots., Findings: Models were developed and internally validated on 21,547 RA patients and externally validated on 131,928 RA patients. Models for serious infection (AUC: internal 0.74, external ranging from 0.62 to 0.83), MI (AUC: internal 0.76, external ranging from 0.56 to 0.82), and stroke (AUC: internal 0.77, external ranging from 0.63 to 0.95), showed good discrimination and adequate calibration. Models for the other outcomes showed modest internal discrimination (AUC < 0.65) and were not externally validated., Interpretation: We developed and validated prediction models for a variety of adverse health outcomes in RA patients initiating first-line MTX monotherapy. Final models for serious infection, MI, and stroke demonstrated good performance across multiple databases and can be studied for clinical use., Funding: This activity under the European Health Data & Evidence Network (EHDEN) has received funding from the Innovative Medicines Initiative 2 Joint Undertaking under grant agreement No 806968. This Joint Undertaking receives support from the European Union's Horizon 2020 research and innovation programme and EFPIA., Competing Interests: Declaration of Competing Interest CY, RDW, JRA, EB, TDS, MJ, RK, JAK, LK, APU, SR, HMS, and COT report no competing interests related to this work. JNS, AGS, JW, and PR are employees of Janssen Research & Development, a pharmaceutical company of Johnson & Johnson, and shareholders of Johnson & Johnson. At the time the study was conducted, ESB was an employee of Janssen Research & Development, a pharmaceutical company of Johnson & Johnson, shareholder of Johnson & Johnson, and shareholder of Takeda Pharmaceuticals. LC reports her institute has been hired for methodological consultancy by AbbVie Spain, S.L.U., Astellas Pharma, SA, Bristol-Myers Squibb, S.A.U. (BMS), Daiichi-Sankyo España, S.A., Dentsply Sirona Iberia, S.A.U., Eisai Farmacéutica, SA, Fresenius Kabi España, S. A. U., Laboratorios Gebro Pharma, SA, Lilly, S.A., Merck Sharp & Dohme España, S.A., Novartis Farmaceutica, SA, Pfizer, S.L.U., Roche Farma, S.A, Sanofi Aventis, UCB Pharma, S.A., outside the submitted work. KC reports consultancy fees from Eli Lilly, AbbVie, and Pfizer, outside the submitted work. WF is an employee and shareholder of Eli Lilly. AHO is an employee of Lilly Deutschland GmbH. JL reports grants from Versus Arthritis, grants from Medical Research Council, outside the submitted work. AM is an employee of Bayer AG. At the time the study was conducted, KM was an employee of Servier. KV works for a research institute which receives/received unconditional research grants from Yamanouchi, Pfizer/Boehringer Ingelheim, Novartis, GSK, UCB, Amgen, Chiesi, none of these are related to the content of this paper. DV reports personal fees from Bayer, during the conduct of the study and outside the submitted work. DPA reports grants and other (DPA's department has received fees for speaker services and advisory board membership) from AMGEN, grants, non-financial support and other (DPA's department has received fees for consultancy services) from UCB Biopharma, grants from Les Laboratoires Servier, outside the submitted work; and Janssen, on behalf of IMI-funded EHDEN and EMIF consortiums, and Synapse Management Partners have supported training programmes organised by DPA's department and open for external participants. PRR works for a research institute who receives/received unconditional research grants from Yamanouchi, Pfizer-Boehringer Ingelheim, GSK, Amgen, UCB, Novartis, AstraZeneca, Chiesi, Janssen Research and Development, none of which relate to the content of this work., (Copyright © 2022 The Author(s). Published by Elsevier Inc. All rights reserved.)

Objective: To study the population-level mental health responses during the first wave of coronavirus disease 2019 (COVID-19) outbreak in Estonia and analyze its socio-demographic, behavioral, and health-related variations among general population. Methods: This study used nationally representative data on 4,606 individuals, aged 18-79 years from a rapid-response cross-sectional survey conducted in April 2020. Point prevalence and mutually adjusted prevalence rate ratios for perceived stress from log-binomial regression analysis were presented for socio-demographic, behavioral, and health-related variables. Results: This study found that 52.2% of population aged 18-79 reported elevated stress levels in relation to COVID-19 outbreak. Higher levels of perceived stress were found in women, in younger age groups, in Estonians, and in those with higher self-perceived infection risk, presence of respiratory symptoms, and less than optimal health, according to self-reports. Conclusion: Although, the potential long-term health effects of the current crisis are yet unknown, the alarmingly high stress levels among people indicate that the COVID-19 pandemic might have had a widespread effect on people's mental health., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2021 Reile, Kullamaa, Hallik, Innos, Kukk, Laidra, Nurk, Tamson and Vorobjov.)