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      The paradigm change from reactive medical services to 3PM in ischemic stroke: a holistic approach utilising tear fluid multi-omics, mitochondria as a vital biosensor and AI-based multi-professional data interpretation

      research-article
      1 , , 2 , 3 , 4 , 5 , 6 , 7 , 8 , 8 , 9 , 10 , 9 , 10 , 11 , 12 , 13 , 14 , 15 , 16 , 17 , 18 , 19 , 20 , 21 , 22 , 23 , 24 , 25 , 25 , 26 , 27 , 4
      The EPMA Journal
      Springer International Publishing
      Predictive preventive personalised medicine (PPPM / 3PM), Ischemic stroke, Sudden cardiac arrest/death, Suboptimal health, Health-to-disease transition, Primary and secondary care, Patient-friendly non-invasive approach, Tear fluid analysis, Viromics and metabolomics, Mitochondrial health, Mitophagy, Inflammation, Cytokine storm (COVID-19), Diabetes mellitus, Diabetic retinopathy, Flammer syndrome, Health risk assessment, Sleep medicine, Behavioural patterns, Individualised patient profile, Artificial intelligence, Population screening, Healthcare economy, Health policy, Expert recommendations

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          Abstract

          Worldwide stroke is the second leading cause of death and the third leading cause of death and disability combined. The estimated global economic burden by stroke is over US$891 billion per year. Within three decades (1990–2019), the incidence increased by 70%, deaths by 43%, prevalence by 102%, and DALYs by 143%. Of over 100 million people affected by stroke, about 76% are ischemic stroke (IS) patients recorded worldwide. Contextually, ischemic stroke moves into particular focus of multi-professional groups including researchers, healthcare industry, economists, and policy-makers. Risk factors of ischemic stroke demonstrate sufficient space for cost-effective prevention interventions in primary (suboptimal health) and secondary (clinically manifested collateral disorders contributing to stroke risks) care. These risks are interrelated. For example, sedentary lifestyle and toxic environment both cause mitochondrial stress, systemic low-grade inflammation and accelerated ageing; inflammageing is a low-grade inflammation associated with accelerated ageing and poor stroke outcomes. Stress overload, decreased mitochondrial bioenergetics and hypomagnesaemia are associated with systemic vasospasm and ischemic lesions in heart and brain of all age groups including teenagers. Imbalanced dietary patterns poor in folate but rich in red and processed meat, refined grains, and sugary beverages are associated with hyperhomocysteinaemia, systemic inflammation, small vessel disease, and increased IS risks. Ongoing 3PM research towards vulnerable groups in the population promoted by the European Association for Predictive, Preventive and Personalised Medicine (EPMA) demonstrates promising results for the holistic patient-friendly non-invasive approach utilising tear fluid-based health risk assessment, mitochondria as a vital biosensor and AI-based multi-professional data interpretation as reported here by the EPMA expert group. Collected data demonstrate that IS-relevant risks and corresponding molecular pathways are interrelated. For examples, there is an evident overlap between molecular patterns involved in IS and diabetic retinopathy as an early indicator of IS risk in diabetic patients. Just to exemplify some of them such as the 5-aminolevulinic acid/pathway, which are also characteristic for an altered mitophagy patterns, insomnia, stress regulation and modulation of microbiota-gut-brain crosstalk. Further, ceramides are considered mediators of oxidative stress and inflammation in cardiometabolic disease, negatively affecting mitochondrial respiratory chain function and fission/fusion activity, altered sleep–wake behaviour, vascular stiffness and remodelling. Xanthine/pathway regulation is involved in mitochondrial homeostasis and stress-driven anxiety-like behaviour as well as molecular mechanisms of arterial stiffness. In order to assess individual health risks, an application of machine learning (AI tool) is essential for an accurate data interpretation performed by the multiparametric analysis. Aspects presented in the paper include the needs of young populations and elderly, personalised risk assessment in primary and secondary care, cost-efficacy, application of innovative technologies and screening programmes, advanced education measures for professionals and general population—all are essential pillars for the paradigm change from reactive medical services to 3PM in the overall IS management promoted by the EPMA.

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          Expert consensus document. The International Scientific Association for Probiotics and Prebiotics consensus statement on the scope and appropriate use of the term probiotic.

          An expert panel was convened in October 2013 by the International Scientific Association for Probiotics and Prebiotics (ISAPP) to discuss the field of probiotics. It is now 13 years since the definition of probiotics and 12 years after guidelines were published for regulators, scientists and industry by the Food and Agriculture Organization of the United Nations and the WHO (FAO/WHO). The FAO/WHO definition of a probiotic--"live microorganisms which when administered in adequate amounts confer a health benefit on the host"--was reinforced as relevant and sufficiently accommodating for current and anticipated applications. However, inconsistencies between the FAO/WHO Expert Consultation Report and the FAO/WHO Guidelines were clarified to take into account advances in science and applications. A more precise use of the term 'probiotic' will be useful to guide clinicians and consumers in differentiating the diverse products on the market. This document represents the conclusions of the ISAPP consensus meeting on the appropriate use and scope of the term probiotic.
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            Global, regional, and national burden of stroke and its risk factors, 1990–2019: a systematic analysis for the Global Burden of Disease Study 2019

            Summary Background Regularly updated data on stroke and its pathological types, including data on their incidence, prevalence, mortality, disability, risk factors, and epidemiological trends, are important for evidence-based stroke care planning and resource allocation. The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) aims to provide a standardised and comprehensive measurement of these metrics at global, regional, and national levels. Methods We applied GBD 2019 analytical tools to calculate stroke incidence, prevalence, mortality, disability-adjusted life-years (DALYs), and the population attributable fraction (PAF) of DALYs (with corresponding 95% uncertainty intervals [UIs]) associated with 19 risk factors, for 204 countries and territories from 1990 to 2019. These estimates were provided for ischaemic stroke, intracerebral haemorrhage, subarachnoid haemorrhage, and all strokes combined, and stratified by sex, age group, and World Bank country income level. Findings In 2019, there were 12·2 million (95% UI 11·0–13·6) incident cases of stroke, 101 million (93·2–111) prevalent cases of stroke, 143 million (133–153) DALYs due to stroke, and 6·55 million (6·00–7·02) deaths from stroke. Globally, stroke remained the second-leading cause of death (11·6% [10·8–12·2] of total deaths) and the third-leading cause of death and disability combined (5·7% [5·1–6·2] of total DALYs) in 2019. From 1990 to 2019, the absolute number of incident strokes increased by 70·0% (67·0–73·0), prevalent strokes increased by 85·0% (83·0–88·0), deaths from stroke increased by 43·0% (31·0–55·0), and DALYs due to stroke increased by 32·0% (22·0–42·0). During the same period, age-standardised rates of stroke incidence decreased by 17·0% (15·0–18·0), mortality decreased by 36·0% (31·0–42·0), prevalence decreased by 6·0% (5·0–7·0), and DALYs decreased by 36·0% (31·0–42·0). However, among people younger than 70 years, prevalence rates increased by 22·0% (21·0–24·0) and incidence rates increased by 15·0% (12·0–18·0). In 2019, the age-standardised stroke-related mortality rate was 3·6 (3·5–3·8) times higher in the World Bank low-income group than in the World Bank high-income group, and the age-standardised stroke-related DALY rate was 3·7 (3·5–3·9) times higher in the low-income group than the high-income group. Ischaemic stroke constituted 62·4% of all incident strokes in 2019 (7·63 million [6·57–8·96]), while intracerebral haemorrhage constituted 27·9% (3·41 million [2·97–3·91]) and subarachnoid haemorrhage constituted 9·7% (1·18 million [1·01–1·39]). In 2019, the five leading risk factors for stroke were high systolic blood pressure (contributing to 79·6 million [67·7–90·8] DALYs or 55·5% [48·2–62·0] of total stroke DALYs), high body-mass index (34·9 million [22·3–48·6] DALYs or 24·3% [15·7–33·2]), high fasting plasma glucose (28·9 million [19·8–41·5] DALYs or 20·2% [13·8–29·1]), ambient particulate matter pollution (28·7 million [23·4–33·4] DALYs or 20·1% [16·6–23·0]), and smoking (25·3 million [22·6–28·2] DALYs or 17·6% [16·4–19·0]). Interpretation The annual number of strokes and deaths due to stroke increased substantially from 1990 to 2019, despite substantial reductions in age-standardised rates, particularly among people older than 70 years. The highest age-standardised stroke-related mortality and DALY rates were in the World Bank low-income group. The fastest-growing risk factor for stroke between 1990 and 2019 was high body-mass index. Without urgent implementation of effective primary prevention strategies, the stroke burden will probably continue to grow across the world, particularly in low-income countries. Funding Bill & Melinda Gates Foundation.
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              Global, regional, and national burden of stroke, 1990–2016: a systematic analysis for the Global Burden of Disease Study 2016

              Summary Background Stroke is a leading cause of mortality and disability worldwide and the economic costs of treatment and post-stroke care are substantial. The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) provides a systematic, comparable method of quantifying health loss by disease, age, sex, year, and location to provide information to health systems and policy makers on more than 300 causes of disease and injury, including stroke. The results presented here are the estimates of burden due to overall stroke and ischaemic and haemorrhagic stroke from GBD 2016. Methods We report estimates and corresponding uncertainty intervals (UIs), from 1990 to 2016, for incidence, prevalence, deaths, years of life lost (YLLs), years lived with disability (YLDs), and disability-adjusted life-years (DALYs). DALYs were generated by summing YLLs and YLDs. Cause-specific mortality was estimated using an ensemble modelling process with vital registration and verbal autopsy data as inputs. Non-fatal estimates were generated using Bayesian meta-regression incorporating data from registries, scientific literature, administrative records, and surveys. The Socio-demographic Index (SDI), a summary indicator generated using educational attainment, lagged distributed income, and total fertility rate, was used to group countries into quintiles. Findings In 2016, there were 5·5 million (95% UI 5·3 to 5·7) deaths and 116·4 million (111·4 to 121·4) DALYs due to stroke. The global age-standardised mortality rate decreased by 36·2% (−39·3 to −33·6) from 1990 to 2016, with decreases in all SDI quintiles. Over the same period, the global age-standardised DALY rate declined by 34·2% (−37·2 to −31·5), also with decreases in all SDI quintiles. There were 13·7 million (12·7 to 14·7) new stroke cases in 2016. Global age-standardised incidence declined by 8·1% (−10·7 to −5·5) from 1990 to 2016 and decreased in all SDI quintiles except the middle SDI group. There were 80·1 million (74·1 to 86·3) prevalent cases of stroke globally in 2016; 41·1 million (38·0 to 44·3) in women and 39·0 million (36·1 to 42·1) in men. Interpretation Although age-standardised mortality rates have decreased sharply from 1990 to 2016, the decrease in age-standardised incidence has been less steep, indicating that the burden of stroke is likely to remain high. Planned updates to future GBD iterations include generating separate estimates for subarachnoid haemorrhage and intracerebral haemorrhage, generating estimates of transient ischaemic attack, and including atrial fibrillation as a risk factor. Funding Bill & Melinda Gates Foundation
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                Author and article information

                Contributors
                Olga.Golubnitschaja@ukbonn.de
                Journal
                EPMA J
                EPMA J
                The EPMA Journal
                Springer International Publishing (Cham )
                1878-5077
                1878-5085
                27 February 2024
                27 February 2024
                March 2024
                : 15
                : 1
                : 1-23
                Affiliations
                [1 ]GRID grid.10388.32, ISNI 0000 0001 2240 3300, Predictive, Preventive and Personalised (3P) Medicine, Department of Radiation Oncology, , University Hospital Bonn, Rheinische Friedrich-Wilhelms-Universität Bonn, ; 53127 Bonn, Germany
                [2 ]Department of Histology and Embryology, Faculty of Medicine in Plzen, Charles University, ( https://ror.org/024d6js02) Prague, Czech Republic
                [3 ]Biomedical Centre, Faculty of Medicine in Plzen, Charles University, ( https://ror.org/024d6js02) Prague, Czech Republic
                [4 ]GRID grid.4491.8, ISNI 0000 0004 1937 116X, Department of Neurology, , University Hospital Plzen and Faculty of Medicine in Plzen, Charles University, ; Prague, Czech Republic
                [5 ]Department of Biology, Faculty of Medicine in Plzen, Charles University, ( https://ror.org/024d6js02) Prague, Czech Republic
                [6 ]GRID grid.4491.8, ISNI 0000 0004 1937 116X, Department of Neurology, , University Hospital Kralovske Vinohrady, Third Faculty of Medicine, Charles University, ; Prague, Czech Republic
                [7 ]Department of Anatomy, Jessenius Faculty of Medicine, Comenius University in Bratislava, ( https://ror.org/0587ef340) Martin, Slovakia
                [8 ]Department of Histology and Embryology, Jessenius Faculty of Medicine, Comenius University in Bratislava, ( https://ror.org/0587ef340) Martin, Slovakia
                [9 ]Experimental Ophthalmology, University of Geneva, ( https://ror.org/01swzsf04) 1205 Geneva, Switzerland
                [10 ]Ophthalmology Department, University Hospitals of Geneva, ( https://ror.org/01m1pv723) 1205 Geneva, Switzerland
                [11 ]Private Institute of Applied Ophthalmology, Berlin, Germany
                [12 ]Artificial Intelligence & Data Science Group, Fraunhofer SCAI, ( https://ror.org/00trw9c49) Sankt Augustin, Germany
                [13 ]Bonn-Aachen International Center for IT (B-It), University of Bonn, ( https://ror.org/041nas322) 53115 Bonn, Germany
                [14 ]Edith Cowan University, ( https://ror.org/05jhnwe22) Perth, Australia
                [15 ]Beijing Municipal Key Laboratory of Clinical Epidemiology, Capital Medical University, ( https://ror.org/013xs5b60) Beijing, China
                [16 ]The Dental College of Georgia, Departments of Neurology and Surgery, The Medical College of Georgia, Augusta University, ( https://ror.org/012mef835) Augusta, USA
                [17 ]Negentropic Systems, Ružomberok, Slovakia
                [18 ]PPPM Centre, s.r.o., Ruzomberok, Slovakia
                [19 ]Department of Nutrition, School of Health Sciences, Ashkelon Academic College, ( https://ror.org/00sfwx025) Ashkelon, Israel
                [20 ]CuraMed Tagesklinik Nürnberg GmbH, Nuremberg, Germany
                [21 ]GRID grid.454272.2, ISNI 0000 0000 9721 4128, Technische Hochschule Nürnberg GSO, ; Nuremberg, Germany
                [22 ]GRID grid.511981.5, University Clinic for Psychiatry and Psychotherapy, Paracelsus Medical University, ; Nuremberg, Germany
                [23 ]Department of Psychology, Clinical Psychology II, University of Innsbruck, ( https://ror.org/054pv6659) Innsbruck, Austria
                [24 ]University Clinic of Endocrinology, Diabetes and Metabolic Disorders Skopje, University Goce Delcev, Faculty of Medical Sciences, ( https://ror.org/058q1cn43) Stip, North Macedonia
                [25 ]GRID grid.10388.32, ISNI 0000 0001 2240 3300, Department of Radiation Oncology, , University Hospital Bonn, Rheinische Friedrich-Wilhelms-Universität Bonn, ; 53127 Bonn, Germany
                [26 ]GRID grid.6363.0, ISNI 0000 0001 2218 4662, Charité University Medicine Berlin, ; Berlin, Germany
                [27 ]GRID grid.24381.3c, ISNI 0000 0000 9241 5705, Cardio Metabolic Unit, Department of Medicine Huddinge, and Department of Laboratory Medicine, Karolinska Institutet, and Medicine Unit of Endocrinology, Theme Inflammation and Ageing, , Karolinska University Hospital, ; Stockholm, Sweden
                Article
                356
                10.1007/s13167-024-00356-6
                10923756
                38463624
                9b4cec52-2937-4830-abd8-55a2e897e9ea
                © The Author(s) 2024

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 1 February 2024
                : 8 February 2024
                Funding
                Funded by: Universitätsklinikum Bonn (8930)
                Categories
                Research
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                © European Association for Predictive, Preventive and Personalised Medicine (EPMA) 2024

                Molecular medicine
                predictive preventive personalised medicine (pppm / 3pm),ischemic stroke,sudden cardiac arrest/death,suboptimal health,health-to-disease transition,primary and secondary care,patient-friendly non-invasive approach,tear fluid analysis,viromics and metabolomics,mitochondrial health,mitophagy,inflammation,cytokine storm (covid-19),diabetes mellitus,diabetic retinopathy,flammer syndrome,health risk assessment,sleep medicine,behavioural patterns,individualised patient profile,artificial intelligence,population screening,healthcare economy,health policy,expert recommendations

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