Machine Learning based Early Prediction of End-stage Renal Disease in Patients with Diabetic Kidney Disease using Clinical Trials Data

AimTo predict end‐stage renal disease (ESRD) in patients with type 2 diabetes by using machine‐learning models with multiple baseline demographic and clinical characteristics.Materials and methodsIn total, 11 789 patients with type 2 diabetes and nephropathy from three clinical trials, RENAAL (n = 1513), IDNT (n = 1715) and ALTITUDE (n = 8561), were used in this study. Eighteen baseline demographic and clinical characteristics were used as predictors to train machine‐learning models to predict ESRD (doubling of serum creatinine and/or ESRD). We used the area under the receiver operator curve (AUC) to assess the prediction performance of models and compared this with traditional Cox proportional hazard regression and kidney failure risk equation models.ResultsThe feed forward neural network model predicted ESRD with an AUC of 0.82 (0.76‐0.87), 0.81 (0.75‐0.86) and 0.84 (0.79‐0.90) in the RENAAL, IDNT and ALTITUDE trials, respectively. The feed forward neural network model selected urinary albumin to creatinine ratio, serum albumin, uric acid and serum creatinine as important predictors and obtained a state‐of‐the‐art performance for predicting long‐term ESRD.ConclusionsDespite large inter‐patient variability, non‐linear machine‐learning models can be used to predict long‐term ESRD in patients with type 2 diabetes and nephropathy using baseline demographic and clinical characteristics. The proposed method has the potential to create accurate and multiple outcome prediction automated models to identify high‐risk patients who could benefit from therapy in clinical practice.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/163629/2/dom14178.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/163629/1/dom14178_am.pd

Exploring the role of competing demands and routines during the implementation of a self-management tool for type 2 diabetes: A theory-based qualitative interview study

Background The implementation of new medical interventions into routine care involves healthcare professionals adopting new clinical behaviours and changing existing ones. Whilst theory-based approaches can help understand healthcare professionals’ behaviours, such approaches often focus on a single behaviour and conceptualise its performance in terms of an underlying reflective process. Such approaches fail to consider the impact of non-reflective influences (e.g. habit and automaticity) and how the myriad of competing demands for their time may influence uptake. The current study aimed to apply a dual process theoretical approach to account for reflective and automatic determinants of healthcare professional behaviour while integrating a multiple behaviour approach to understanding the implementation and use of a new self-management tool by healthcare professionals in the context of diabetes care. Methods Following Diabetes UK’s national release of the ‘Information Prescription’ (DUK IP; a self-management tool targeting the management of cholesterol, blood pressure and HbA1c) in January 2015, we conducted semi-structured interviews with 13 healthcare professionals (general practitioners and nurses) who had started to use the DUK IP during consultations to provide self-management advice to people with type 2 diabetes. A theory-based topic guide included pre-specified constructs from a previously developed logic model. We elicited healthcare professionals’ views on reflective processes (outcome expectations, self-efficacy, intention, action and coping planning), automatic processes (habit), and multiple behaviour processes (goal priority, goal conflict and goal facilitation). All interviews were audio recorded and transcribed verbatim and all transcripts were independently double coded and analysed using content analysis. Results The majority of healthcare professionals interviewed reported strong intentions to use the DUK IP and having formed a habit of using them after a minimum of one month continuous use. Pop-up cues in the electronic patient records were perceived to facilitate the use of the tool. Factors that conflicted with the use of the DUK IP included existing pathways of providing self-management advice. Conclusion Data suggests that constructs from dual process and multiple behaviour approaches are useful to provide supplemental understanding of the implementation of new self-management tools such as the DUK IP and may help to advance behavioural approaches to implementation science

International comparisons of laboratory values from the 4CE collaborative to predict COVID-19 mortality

Given the growing number of prediction algorithms developed to predict COVID-19 mortality, we evaluated the transportability of a mortality prediction algorithm using a multi-national network of healthcare systems. We predicted COVID-19 mortality using baseline commonly measured laboratory values and standard demographic and clinical covariates across healthcare systems, countries, and continents. Specifically, we trained a Cox regression model with nine measured laboratory test values, standard demographics at admission, and comorbidity burden pre-admission. These models were compared at site, country, and continent level. Of the 39,969 hospitalized patients with COVID-19 (68.6% male), 5717 (14.3%) died. In the Cox model, age, albumin, AST, creatine, CRP, and white blood cell count are most predictive of mortality. The baseline covariates are more predictive of mortality during the early days of COVID-19 hospitalization. Models trained at healthcare systems with larger cohort size largely retain good transportability performance when porting to different sites. The combination of routine laboratory test values at admission along with basic demographic features can predict mortality in patients hospitalized with COVID-19. Importantly, this potentially deployable model differs from prior work by demonstrating not only consistent performance but also reliable transportability across healthcare systems in the US and Europe, highlighting the generalizability of this model and the overall approach

Long-term kidney function recovery and mortality after COVID-19-associated acute kidney injury: An international multi-centre observational cohort study

Background: While acute kidney injury (AKI) is a common complication in COVID-19, data on post-AKI kidney function recovery and the clinical factors associated with poor kidney function recovery is lacking. Methods: A retrospective multi-centre observational cohort study comprising 12,891 hospitalized patients aged 18 years or older with a diagnosis of SARS-CoV-2 infection confirmed by polymerase chain reaction from 1 January 2020 to 10 September 2020, and with at least one serum creatinine value 1–365 days prior to admission. Mortality and serum creatinine values were obtained up to 10 September 2021. Findings: Advanced age (HR 2.77, 95%CI 2.53–3.04, p < 0.0001), severe COVID-19 (HR 2.91, 95%CI 2.03–4.17, p < 0.0001), severe AKI (KDIGO stage 3: HR 4.22, 95%CI 3.55–5.00, p < 0.0001), and ischemic heart disease (HR 1.26, 95%CI 1.14–1.39, p < 0.0001) were associated with worse mortality outcomes. AKI severity (KDIGO stage 3: HR 0.41, 95%CI 0.37–0.46, p < 0.0001) was associated with worse kidney function recovery, whereas remdesivir use (HR 1.34, 95%CI 1.17–1.54, p < 0.0001) was associated with better kidney function recovery. In a subset of patients without chronic kidney disease, advanced age (HR 1.38, 95%CI 1.20–1.58, p < 0.0001), male sex (HR 1.67, 95%CI 1.45–1.93, p < 0.0001), severe AKI (KDIGO stage 3: HR 11.68, 95%CI 9.80–13.91, p < 0.0001), and hypertension (HR 1.22, 95%CI 1.10–1.36, p = 0.0002) were associated with post-AKI kidney function impairment. Furthermore, patients with COVID-19-associated AKI had significant and persistent elevations of baseline serum creatinine 125% or more at 180 days (RR 1.49, 95%CI 1.32–1.67) and 365 days (RR 1.54, 95%CI 1.21–1.96) compared to COVID-19 patients with no AKI. Interpretation: COVID-19-associated AKI was associated with higher mortality, and severe COVID-19-associated AKI was associated with worse long-term post-AKI kidney function recovery. Funding: Authors are supported by various funders, with full details stated in the acknowledgement section

EPMA-World Congress 2015: Bonn, Germany. 3-5 September 2015

Table of contents A1 Predictive and prognostic biomarker panel for targeted application of radioembolisation improving individual outcomes in hepatocellular carcinoma Jella-Andrea Abraham, Olga Golubnitschaja A2 Integrated market access approach amplifying value of “Rx-CDx” Ildar Akhmetov A3 Disaster response: an opportunity to improve global healthcare Russell J. Andrews, Leonidas Quintana A4 USA PPPM: proscriptive, profligate, profiteering medicine-good for 1 % wealthy, not for 99 % unhealthy Russell J. Andrews A5 The role of IDO in a murine model of gingivitis: predictive and therapeutic potentials Babak Baban, Jun Yao Liu, Xu Qin, Tailing Wang, Mahmood S. Mozaffari A6 Specific diets for personalised treatment of diabetes type 2 Viktoriia V. Bati, Tamara V. Meleshko, Olga B. Levchuk, Nadiya V. Boyko A7 Towards personalized physiotherapeutic approach Joanna Bauer, Ewa Boerner, Halina Podbielska A8 Cells, animal, SHIME and in silico models for detection and verification of specific biomarkers of non-communicable chronic diseases Alojz Bomba, Viktor O. Petrov, Volodymyr G. Drobnych, Rostyslav V. Bubnov, Oksana M. Bykova, Nadiya V. Boyko A9 INTERACT-chronic care model: Self-treatment by patients with decision support e-Health solution Hans-Peter Brunner-La Rocca, Lutz Fleischhacker, Olga Golubnitschaja, Frank Heemskerk, Thomas Helms, Tiny Jaarsma, Judita Kinkorova, Jan Ramaekers, Peter Ruff, Ivana Schnur, Emilio Vanoli, Jose Verdu A10 PPPM in cardiovascular medicine in 2015 Hans-Peter Brunner-La Rocca A11 Magnetic resonance imaging of nanoparticles in mice, potential for theranostic and contrast media development – pilot results Rostyslav V. Bubnov, Sergiy A. Grabovetskyi, Olena M. Mykhalchenko, Natalia O. Tymoshok, Oleksandr B. Shcherbakov, Igor P. Semeniv, Mykola Y. Spivak A12 Ultrasound diagnosis for diabetic neuropathy - comparative study Rostyslav V. Bubnov, Tetyana V. Ostapenko A13 Ultrasound for stratification patients with diabetic foot ulcers for prevention and personalized treatment - pilot results Rostyslav V. Bubnov, Nazarii M. Kobyliak, Nadiya M. Zholobak, Mykola Ya. Spivak A14 Project ImaGenX – designing and executing a questionnaire on environment and lifestyle risk of breast cancer John Paul Cauchi A15 Genomics – a new structural brand of predictive, preventive and personalized medicine or the new driver as well? Dmitrii Cherepakhin, Marina Bakay, Artem Borovikov, Sergey Suchkov A16 Survey of questionnaires for evaluation of the quality of life in various medical fields Barbara Cieślik, Agnieszka Migasiewicz, Maria-Luiza Podbielska, Markus Pelleter, Agnieszka Giemza, Halina Podbielska A17 Personalized molecular treatment for muscular dystrophies Sebahattin Cirak A18 Secondary mutations in circulating tumour DNA for acquired drug resistance in patients with advanced ALK + NSCLC Marzia Del Re, Paola Bordi, Valentina Citi, Marta Palombi, Carmine Pinto, Marcello Tiseo, Romano Danesi A19 Recombinant species-specific FcεRI alpha proteins for diagnosis of IgE-mediated allergies in dogs, cats and horses Lukas Einhorn, Judit Fazekas, Martina Muhr, Alexandra Schoos, Lucia Panakova, Ina Herrmann, Krisztina Manzano-Szalai, Kumiko Oida, Edda Fiebiger, Josef Singer, Erika Jensen-Jarolim A20 Global methodology for developmental neurotoxicity testing in humans and animals early and chronically exposed to chemical contaminants Arpiné A. Elnar, Nadia Ouamara, Nadiya Boyko, Xavier Coumoul, Jean-Philippe Antignac, Bruno Le Bizec, Gauthier Eppe, Jenny Renaut, Torsten Bonn, Cédric Guignard, Margherita Ferrante, Maria Liusa Chiusano, Salvatore Cuzzocrea, Gerard O'Keeffe, John Cryan, Michelle Bisson, Amina Barakat, Ihsane Hmamouchi, Nasser Zawia, Anumantha Kanthasamy, Glen E. Kisby, Rui Alves, Oscar Villacañas Pérez, Kim Burgard, Peter Spencer, Norbert Bomba, Martin Haranta, Nina Zaitseva, Irina May, Stéphanie Grojean, Mathilde Body-Malapel, Florencia Harari, Raul Harari, Kristina Yeghiazaryan, Olga Golubnitschaja, Vittorio Calabrese, Christophe Nemos, Rachid Soulimani A21 Mental indicators at young people with attributes hypertension and pre-hypertension Maria E. Evsevyeva, Elena A. Mishenko, Zurida V. Kumukova, Evgeniy V. Chudnovsky, Tatyana A. Smirnova A22 On the approaches to the early diagnosis of stress-induced hypertension in young employees of State law enforcement agencies Maria E. Evsevyeva, Ludmila V. Ivanova, Michail V. Eremin, Maria V. Rostovtseva A23 Сentral aortic pressure and indexes of augmentation in young persons in view of risk factors Maria E. Evsevyeva, Michail V. Eremin, Vladimir I. Koshel, Oksana V. Sergeeva, Nadesgda M. Konovalova A24 Breast cancer prediction and prevention: Are reliable biomarkers in horizon? Shantanu Girotra, Olga Golubnitschaja A25 Flammer Syndrome and potential formation of pre-metastatic niches: A multi-centred study on phenotyping, patient stratification, prediction and potential prevention of aggressive breast cancer and metastatic disease Olga Golubnitschaja, Manuel Debald, Walther Kuhn, Kristina Yeghiazaryan, Rostyslav V. Bubnov, Vadym M. Goncharenko, Ulyana Lushchyk, Godfrey Grech, Katarzyna Konieczka A26 Innovative tools for prenatal diagnostics and monitoring: improving individual pregnancy outcomes and health-economy in EU Olga Golubnitschaja, Jan Jaap Erwich, Vincenzo Costigliola, Kristina Yeghiazaryan, Ulrich Gembruch A27 Immunohistochemical assessment of APUD cells in endometriosis Vadym M. Goncharenko, Vasyl O. Beniuk, Olga V. Kalenska, Rostyslav V. Bubnov A28 Updating personalized management algorithm of endometrial hyperplasia in pre-menopause women Vadym M. Goncharenko, Vasyl O. Beniuk, Rostyslav V. Bubnov, Olga Melnychuk A29 The personified treatment approach of polimorbid patients with periodontal inflammatory diseases Irina A. Gorbacheva, Lyudmila Y. Orekhova, Vadim V. Tachalov A30 Ukrainian experience in hybrid war – the challenge to update algorithms for personalized care and early prevention of different military injuries Olena I. Grechanyk, Rizvan Ya. Abdullaiev, Rostyslav V. Bubnov A31 Tear fluid biomarkers: a comparison of tear fluid sampling and storage protocols Suzanne Hagan, Eilidh Martin, Ian Pearce, Katherine Oliver A32 The correlation of dietary habits with gingival problems during menstruation Cenk Haytac, Fariz Salimov, Servin Yoksul, Anatoly A. Kunin, Natalia S. Moiseeva A33 Genomic medicine in a contemporary Spanish population of prostate cancer: our experience Bernardo Herrera-Imbroda, Sergio del Río-González, Maria Fernanda Lara, Antonia Angulo, Francisco Javier Machuca Santa-Cruz A34 Challenges, opportunities and collaborations for personalized medicine applicability in uro-oncological disease Bernardo Herrera-Imbroda, Sergio del Río-González, Maria Fernanda Lara A35 Metabolic hallmarks of cancer as targets for a personalized therapy John Ionescu A36 Influence of genetic polymorphism as a predictor of the development of periodontal disease in patients with gastric ulcer and 12 duodenal ulcer Alfiya Z. Isamulaeva, Anatoly A. Kunin, Shamil Sh. Magomedov, Aida I. Isamulaeva A37 Challenges in diabetic macular edema Tatjana Josifova A38 Overview of the EPMA strategies in laboratory medicine relevant for PPPM Marko Kapalla, Juraj Kubáň, Olga Golubnitschaja, Vincenzo Costigliola A39 EPMA initiative for effective organization of medical travel: European concepts and criteria Vincenzo Costigliola, Marko Kapalla, Juraj Kubáň, Olga Golubnitschaja A40 Design and innovation in e-textiles: implications for PPPM Anthony Kent, Tom Fisher, Tilak Dias A41 Biobank in Pilsen as a member of national node BBMRI_CZ Judita Kinkorová, Ondřej Topolčan A42 Big data in personalized medicine: hype and hope Matthias Kohl A43 The 3P approach as the platform of the European Dentistry Department (DPPPD) Anatoly A. Kunin, Natalia S. Moiseeva A44 The endometrium cytokine patterns for predictive diagnosis of proliferation severity and cancer prevention Andrii I. Kurchenko, Vasyl A. Beniuk, Vadym M. Goncharenko, Rostyslav V. Bubnov, Nadiya V. Boyko, Andriy M. Strokan A45 A monocyte-based in-vitro system for testing individual responses to the implanted material: future for personalized implant construction Julia Kzhyshkowska, Alexandru Gudima, Ksenia S. Stankevich, Victor D. Filimonov4, Harald Klüter, Evgeniya M. Mamontova, Sergei I. Tverdokhlebov A46 Prediction and prevention of adverse health effects by meteorological factors: Biomarker patterns and creation of a device for self-monitoring and integrated care Ulyana B. Lushchyk, Viktor V. Novytskyy, Igor P. Babii, Nadiya G. Lushchyk, Lyudmyla S. Riabets, Ivanna I. Legka A47 Targeting "disease signatures" towards personalized healthcare Mira Marcus-Kalish, Alexis Mitelpunkt, Tal Galili, Neta Shachar, Yoav Benjamini A48 Influence of the skin imperfection on the personal quality of life and possible tools for objective diagnosis Agnieszka Migasiewicz, Markus Pelleter, Joanna Bauer, Ewelina Dereń, Halina Podbielska A49 The new direction in caries prevention based on the ultrastructure of dental hard tissues and filling materials Natalia S. Moiseeva, Anatoly A. Kunin, Dmitry A. Kunin A50 The use of LED radiation in prevention of dental diseases Natalia S. Moiseeva, Yury A. Ippolitov, Dmitry A. Kunin, Alexei N. Morozov, Natalia V. Chirkova, Nakhid T. Aliev A51 Status of endothelial progenitor cells in diabetic nephropathy: predictive and preventive potentials Mahmood S. Mozaffari, Jun Yao Liu, Babak Baban A52 The status of glucocorticoid-induced leucine zipper protein in salivary gland in Sjögren’s syndrome: predictive and personalized treatment potentials Mahmood S. Mozaffari, Jun Yao Liu, Rafik Abdelsayed, Xing-Ming Shi, Babak Baban A53 Maximal aerobic capacity - important quality marker of health Jaroslav Novák, Milan Štork, Václav Zeman A54 The EMPOWER project: laboratory medicine and Horizon 2020 Wytze P. Oosterhuis, Elvar Theodorsson A55 Personality profile manifestations in patient’s attitude to oral care and adherence to doctor’s prescriptions Lyudmila Y. Orekhova, Tatyana V. Kudryavtseva, Elena R. Isaeva, Vadim V. Tachalov, Ekaterina S. Loboda A56 Results of an European survey on personalized medicine addressed to directions of laboratory medicine Mario Pazzagli, Francesca Malentacchi, Irene Mancini, Ivan Brandslund, Pieter Vermeersch, Matthias Schwab, Janja Marc, Ron H.N. van Schaik, Gerard Siest, Elvar Theodorsson, Chiara Di Resta A57 MCI or early dementia predictive speech based diagnosis techniques Matus Pleva, Jozef Juhar A58 Personalized speech based mobile application for eHealth Matus Pleva, Jozef Juhar A59 Circulating tumor cell-free DNA as the biomarker in the management of cancer patients Jiří Polívka jr., Filip Janků, Martin Pešta, Jan Doležal, Milena Králíčková, Jiří Polívka A60 Complex stroke care – educational programme in Stroke Centre University Hospital Plzen Jiří Polívka, Alena Lukešová, Nina Müllerová, Petr Ševčík, Vladimír Rohan A61 Sleep apnea and sleep fragmentation contribute to brain aging Kneginja Richter, Lence Miloseva, Günter Niklewski A62 Personalised approach for sleep disturbances in shift workers Kneginja Richter, Jens Acker, Guenter Niklewski A63 Medical travel and innovative PPPM clusters: new concept of integration Olga Safonicheva, Vincenzo Costigliola A64 Medical travel and women health Olga Safonicheva A65 Continuity of generations in the training of specialists in the field of reconstructive microsurgery Maxim Sautin, Janna Sinelnikova, Sergey Suchkov A66 Telemonitoring of stroke patients – empirical evidence of individual risk management results from an observational study in Germany Songül Secer, Stephan von Bandemer A67 Women’s increasing breast cancer risk with n-6 fatty acid intake explained by estrogen-fatty acid interactive effect on DNA damage: implications for gender-specific nutrition within personalized medicine Niva Shapira A68 Cytobacterioscopy of the gingival crevicular fluid as a method for preventive diagnosis of periodontal diseases Aleksandr Shcherbakov, Anatoly A. Kunin, Natalia S. Moiseeva A69 Use of specially treated composites in dentistry to avoid violations of aesthetics Bogdan R. Shumilovich, Zhanna Lipkind, Yulia Vorobieva, Dmitry A. Kunin, Anastasiia V. Sudareva A70 National eHealth system – platform for preventive, predictive and personalized diabetes care Ivica Smokovski, Tatjana Milenkovic A72 The common energy levels of Prof. Szent-Györgyi, the intrinsic chemistry of melanin, and the muscle physiopathology. Implications in the context of Preventive, Predictive, and Personalized Medicine Arturo Solís-Herrera, María del Carmen Arias-Esparza, Sergey Suchkov A73 Plurality and individuality of hepatocellular carcinoma: PPPM perspectives Krishna Chander Sridhar, Olga Golubnitschaja A74 Strategic aspects of higher medical education reforms to secure newer educational platforms for getting biopharma professionals matures Maria Studneva, Sihong Song, James Creeden, Мark Мandrik, Sergey Suchkov A75 Overview of the strategies and activities of the European Federation of Clinical Chemistry and Laboratory Medicine, (EFLM) Elvar Theodorsson, EFLM A76 New spectroscopic techniques for point of care label free diagnostics Syed A. M. Tofail A77 Tumor markers for personalized medicine and oncology - the role of Laboratory Medicine Ondřej Topolčan, Judita Kinkorová, Ondřej Fiala, Marie Karlíková, Šárka Svobodová, Radek Kučera, Radka Fuchsová, Vladislav Třeška, Václav Šimánek, Ladislav Pecen, Jan Šoupal, Štěpán Svačina2 A78 Modern medical terminology (MMT) as a driver of the global educational reforms Evgeniya Tretyak, Maria Studneva, Sergey Suchkov A79 Juvenile hypertension; the relevance of novel predictive, preventive and personalized assessment of its determinants Francesca M. Trovato, G. Fabio Martines, Daniela Brischetto, Daniela Catalano, Giuseppe Musumeci, Guglielmo M. Trovato A80 Proteomarkers Biotech George Th. Tsangaris, Athanasios K. Anagnostopoulos A81 Proteomics and mass spectrometry based non-invasive prenatal testing of fetal health and pregnancy complications George Th. Tsangaris, Athanasios K. Anagnostopoulos A82 Integrated Ecosystem for an Integrated Care model for Heart Failure (HF) patients including related comorbidities (ZENITH) José Verdú, German Gutiérrez, Jordi Rovira, Marta Martinez, Lutz Fleischhacker, Donna Green, Arthur Garson, Elena Tamburini, Stefano Cuomo, Juan Martinez-Leon, Teresa Abrisqueta, Hans-Peter Brunner-La Rocca, Tiny Jaarsma, Teresa Arredondo, Cecilia Vera, Giuseppe Fico, Olga Golubnitschaja, Fernando Arribas, Martina Onderco, Isabel Vara, on behalf of ZENITH consortium A83 Predictive, preventive and personalized medicine in diabetes onset and complication (MOSAIC project) José Verdú, Francesco Sambo, Barbara Di Camillo, Claudio Cobelli, Andrea Facchinetti, Giuseppe Fico, Riccardo Bellazzi, Lucia Sacchi, Arianna Dagliati, Daniele Segnani, Valentina Tibollo, Manuel Ottaviano, Rafael Gabriel, Leif Groop, Jacqueline Postma, Antonio Martinez, Liisa Hakaste, Tiinamaija Tuomi, Konstantia Zarkogianni, on behalf of MOSAIC consortium A84 Possibilities for personalized therapy of diabetes using in vitro screening of insulin and oral hypoglycemic agents Igor Volchek, Nina Pototskaya, Andrey Petrov A85 The innovative technology for personalized therapy of human diseases based on in vitro drug screening Igor Volchek, Nadezhda Pototskaya, Andrey Petrov A86 Bone destruction and temporomandibular joint: predictive markers, pathogenetic aspects and quality of life Ülle Voog-Oras, Oksana Jagur, Edvitar Leibur, Priit Niibo, Triin Jagomägi, Minh Son Nguyen, Chris Pruunsild, Dagmar Piikov, Mare Saag A87 Sub-optimal health management – global vision for concepts in medical travel Wei Wang A88 Sub-optimal health management: synergic PPPM-TCAM approach Wei Wang A89 Innovative technologies for minimal invasive diagnostics Andreas Weinhäusel, Walter Pulverer, Matthias Wielscher, Manuela Hofner, Christa Noehammer, Regina Soldo, Peter Hettegger, Istvan Gyurjan, Ronald Kulovics, Silvia Schönthaler, Gabriel Beikircher, Albert Kriegner, Stephan Pabinger, Klemens Vierlinger A90 Rare disease diobanks for personalized medicine Ayşe Yüzbaşıoğlu, Meral Özgüç, Member of EuroBioBank - European Network of DNA, Cell and Tissue Banks for Rare Disease

Analyzing Complex Patients’ Temporal Histories: New Frontiers in Temporal Data MiningData Mining in Clinical Medicine

In recent years, data coming from hospital information systems (HIS) and local healthcare organizations have started to be intensively used for research purposes. This rising amount of available data allows reconstructing the compete histories of the patients, which have a strong temporal component. This chapter introduces the major challenges faced by temporal data mining researchers in an era when huge quantities of complex clinical temporal data are becoming available. The analysis is focused on the peculiar features of this kind of data and describes the methodological and technological aspects that allow managing such complex framework. The chapter shows how heterogeneous data can be processed to derive a homogeneous representation. Starting from this representation, it illustrates different techniques for jointly analyze such kind of data. Finally, the technological strategies that allow creating a common data warehouse to gather data coming from different sources and with different formats are presented

Health informatics and EHR to support clinical research in the COVID-19 pandemic: An overview

The coronavirus disease 2019 (COVID-19) pandemic has clearly shown that major challenges and threats for humankind need to be addressed with global answers and shared decisions. Data and their analytics are crucial components of such decision-making activities. Rather interestingly, one of the most difficult aspects is reusing and sharing of accurate and detailed clinical data collected by Electronic Health Records (EHR), even if these data have a paramount importance. EHR data, in fact, are not only essential for supporting day-by-day activities, but also they can leverage research and support critical decisions about effectiveness of drugs and therapeutic strategies. In this paper, we will concentrate our attention on collaborative data infrastructures to support COVID-19 research and on the open issues of data sharing and data governance that COVID-19 had made emerge. Data interoperability, healthcare processes modelling and representation, shared procedures to deal with different data privacy regulations, and data stewardship and governance are seen as the most important aspects to boost collaborative research. Lessons learned from COVID-19 pandemic can be a strong element to improve international research and our future capability of dealing with fast developing emergencies and needs, which are likely to be more frequent in the future in our connected and intertwined world

Sex and apoe genotype differences related to statin use in the aging population

Background: Significant evidence suggests that the cholesterol-lowering statins can affect cognitive function and reduce the risk for Alzheimer’s disease (AD) and dementia. These potential effects may be constrained by specific combinations of an individual’s sex and apolipoprotein E (APOE) genotype. Methods: Here we examine data from 252,327 UK Biobank participants, aged 55 or over, and compare the effects of statin use in males and females. We assessed difference in statin treatments taking a matched cohort approach, and identified key stratifiers using regression models and conditional inference trees. Using statistical modeling, we further evaluated the effect of statins on survival, cognitive decline over time, and on AD prevalence. Results: We identified that in the selected population, males were older, had a higher level of education, better cognitive scores, higher incidence of cardiovascular and metabolic diseases, and a higher rate of statin use. We observed that males and those participants with an APOE ε4–positive genotype had higher probabilities of being treated with statins; while participants with an AD diagnosis had slightly lower probabilities. We found that use of statins was not significantly associated with overall higher rates of survival. However, when considering the interaction of statin use with sex, the results suggest higher survival rates in males treated with statins. Finally, examination of cognitive function indicates a potential beneficial effect of statins that is selective for APOE ε4–positive genotypes. Discussion: Our evaluation of the aging population in a large cohort from the UK Biobank confirms sex and APOE genotype as fundamental risk stratifiers for AD and cognitive function, furthermore it extends them to the specific area of statin use, clarifying their specific interactions with treatments. © 2021 The Authors. Alzheimer’s & Dementia: Translational Research & Clinical Interventions published by Wiley Periodicals LLC on behalf of Alzheimer’s Association.Open access journalThis item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]