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Cheng Y, Gadd DA, Gieger C, Monterrubio-Gómez K, Zhang Y, Berta I, Stam MJ, Szlachetka N, Lobzaev E, Wrobel N, Murphy L, Campbell A, Nangle C, Walker RM, Fawns-Ritchie C, Peters A, Rathmann W, Porteous DJ, Evans KL, McIntosh AM, Cannings TI, Waldenberger M, Ganna A, McCartney DL, Vallejos CA, Marioni RE. Development and validation of DNA methylation scores in two European cohorts augment 10-year risk prediction of type 2 diabetes. Nat Aging 2023; 3:450-458. [PMID: 37117793 DOI: 10.1038/s43587-023-00391-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/19/2021] [Accepted: 02/27/2023] [Indexed: 04/30/2023]
Abstract
Type 2 diabetes mellitus (T2D) presents a major health and economic burden that could be alleviated with improved early prediction and intervention. While standard risk factors have shown good predictive performance, we show that the use of blood-based DNA methylation information leads to a significant improvement in the prediction of 10-year T2D incidence risk. Previous studies have been largely constrained by linear assumptions, the use of cytosine-guanine pairs one-at-a-time and binary outcomes. We present a flexible approach (via an R package, MethylPipeR) based on a range of linear and tree-ensemble models that incorporate time-to-event data for prediction. Using the Generation Scotland cohort (training set ncases = 374, ncontrols = 9,461; test set ncases = 252, ncontrols = 4,526) our best-performing model (area under the receiver operating characteristic curve (AUC) = 0.872, area under the precision-recall curve (PRAUC) = 0.302) showed notable improvement in 10-year onset prediction beyond standard risk factors (AUC = 0.839, precision-recall AUC = 0.227). Replication was observed in the German-based KORA study (n = 1,451, ncases = 142, P = 1.6 × 10-5).
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Affiliation(s)
- Yipeng Cheng
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK
- Institute for Molecular Medicine Finland, University of Helsinki, Helsinki, Finland
| | - Danni A Gadd
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK
| | - Christian Gieger
- Research Unit Molecular Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- German Center for Diabetes Research, München-Neuherberg, Germany
| | - Karla Monterrubio-Gómez
- MRC Human Genetics Unit, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK
| | - Yufei Zhang
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK
| | - Imrich Berta
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK
| | - Michael J Stam
- School of Informatics, University of Edinburgh, Edinburgh, UK
| | | | - Evgenii Lobzaev
- School of Informatics, University of Edinburgh, Edinburgh, UK
| | - Nicola Wrobel
- Edinburgh Clinical Research Facility, University of Edinburgh, Western General Hospital, Edinburgh, UK
| | - Lee Murphy
- Edinburgh Clinical Research Facility, University of Edinburgh, Western General Hospital, Edinburgh, UK
| | - Archie Campbell
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK
| | - Cliff Nangle
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK
| | - Rosie M Walker
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh BioQuarter, Edinburgh, UK
| | - Chloe Fawns-Ritchie
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK
- Department of Psychology, University of Edinburgh, Edinburgh, UK
| | - Annette Peters
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- German Center for Diabetes Research, München-Neuherberg, Germany
- German Centre for Cardiovascular Research, Partner Site Munich Heart Alliance, München, Germany
| | - Wolfgang Rathmann
- German Center for Diabetes Research, München-Neuherberg, Germany
- Institute for Biometrics and Epidemiology, German Diabetes Center, Leibniz Institute for Diabetes Research at Heinrich Heine University, Düsseldorf, Germany
| | - David J Porteous
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK
| | - Kathryn L Evans
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK
| | - Andrew M McIntosh
- Division of Psychiatry, Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
| | | | - Melanie Waldenberger
- Research Unit Molecular Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
| | - Andrea Ganna
- Institute for Molecular Medicine Finland, University of Helsinki, Helsinki, Finland
| | - Daniel L McCartney
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK
| | - Catalina A Vallejos
- MRC Human Genetics Unit, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK.
- The Alan Turing Institute, London, UK.
| | - Riccardo E Marioni
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK.
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Jajcay N, Bezak B, Segev A, Matetzky S, Jankova J, Spartalis M, El Tahlawi M, Guerra F, Friebel J, Thevathasan T, Berta I, Pölzl L, Nägele F, Pogran E, Cader FA, Jarakovic M, Gollmann-Tepeköylü C, Kollarova M, Petrikova K, Tica O, Krychtiuk KA, Tavazzi G, Skurk C, Huber K, Böhm A. Data processing pipeline for cardiogenic shock prediction using machine learning. Front Cardiovasc Med 2023; 10:1132680. [PMID: 37034352 PMCID: PMC10077147 DOI: 10.3389/fcvm.2023.1132680] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/27/2022] [Accepted: 03/07/2023] [Indexed: 04/11/2023] Open
Abstract
Introduction Recent advances in machine learning provide new possibilities to process and analyse observational patient data to predict patient outcomes. In this paper, we introduce a data processing pipeline for cardiogenic shock (CS) prediction from the MIMIC III database of intensive cardiac care unit patients with acute coronary syndrome. The ability to identify high-risk patients could possibly allow taking pre-emptive measures and thus prevent the development of CS. Methods We mainly focus on techniques for the imputation of missing data by generating a pipeline for imputation and comparing the performance of various multivariate imputation algorithms, including k-nearest neighbours, two singular value decomposition (SVD)-based methods, and Multiple Imputation by Chained Equations. After imputation, we select the final subjects and variables from the imputed dataset and showcase the performance of the gradient-boosted framework that uses a tree-based classifier for cardiogenic shock prediction. Results We achieved good classification performance thanks to data cleaning and imputation (cross-validated mean area under the curve 0.805) without hyperparameter optimization. Conclusion We believe our pre-processing pipeline would prove helpful also for other classification and regression experiments.
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Affiliation(s)
- Nikola Jajcay
- Premedix Academy, Bratislava, Slovakia
- Department of Complex Systems, Institute of Computer Science, Czech Academy of Sciences, Prague, Czech Republic
| | - Branislav Bezak
- Premedix Academy, Bratislava, Slovakia
- Clinic of Cardiac Surgery, National Institute of Cardiovascular Diseases, Bratislava, Slovakia
- Faculty of Medicine, Comenius University in Bratislava, Bratislava, Slovakia
- Correspondence: Branislav Bezak
| | - Amitai Segev
- The Leviev Cardiothoracic & Vascular Center, Chaim Sheba Medical Center, Ramat Gan, Israel
- Affiliated to the Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel
| | - Shlomi Matetzky
- The Leviev Cardiothoracic & Vascular Center, Chaim Sheba Medical Center, Ramat Gan, Israel
- Affiliated to the Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel
| | | | - Michael Spartalis
- 3rd Department of Cardiology, National and Kapodistrian University of Athens, Athens, Greece
- Global Clinical Scholars Research Training (GCSRT) Program, Harvard Medical School, Boston, MA, United States
| | - Mohammad El Tahlawi
- Department of Cardiology, Faculty of Human Medicine, Zagazig University, Zagazig, Egypt
| | - Federico Guerra
- Cardiology and Arrhythmology Clinic, Marche Polytechnic University, University Hospital “Umberto I - Lancisi - Salesi”, Ancona, Italy
| | - Julian Friebel
- Department of Cardiology Angiology and Intensive Care Medicine, Deutsches Herzzentrum der Charité (DHZC), Campus Benjamin Franklin, Charité - Universitätsmedizin Berlin, Berlin, Germany
| | - Tharusan Thevathasan
- Department of Cardiology Angiology and Intensive Care Medicine, Deutsches Herzzentrum der Charité (DHZC), Campus Benjamin Franklin, Charité - Universitätsmedizin Berlin, Berlin, Germany
- Berlin Institute of Health, Charité—Universitätsmedizin Berlin, Berlin, Germany
- Deutsches Zentrum für Herz-Kreislauf-Forschung e.V., Berlin, Germany
- Institute of Medical Informatics, Charité—Universitätsmedizin Berlin, Berlin, Germany
| | | | - Leo Pölzl
- Department for Cardiac Surgery, Cardiac Regeneration Research, Medical University of Innsbruck, Innsbruck, Austria
| | - Felix Nägele
- Department for Cardiac Surgery, Cardiac Regeneration Research, Medical University of Innsbruck, Innsbruck, Austria
| | - Edita Pogran
- 3rd Medical Department, Cardiology and Intensive Care Medicine, Wilhelminen Hospital, Vienna, Austria
| | - F. Aaysha Cader
- Department of Cardiology, Ibrahim Cardiac Hospital & Research Institute, Dhaka, Bangladesh
| | - Milana Jarakovic
- Cardiac Intensive Care Unit, Institute for Cardiovascular Diseases of Vojvodina, Sremska Kamenica, Serbia
- Faculty of Medicine, University of Novi Sad, Novi Sad, Serbia
| | - Can Gollmann-Tepeköylü
- Department for Cardiac Surgery, Cardiac Regeneration Research, Medical University of Innsbruck, Innsbruck, Austria
| | | | | | - Otilia Tica
- Cardiology Department, Emergency County Clinical Hospital of Oradea, Oradea, Romania
- Institute of Cardiovascular Sciences, University of Birmingham, Medical School, Birmingham, United Kingdom
| | - Konstantin A. Krychtiuk
- Department of Internal Medicine II, Division of Cardiology, Medical University of Vienna, Vienna, Austria
- Duke Clinical Research Institute Durham, NC, United States
| | - Guido Tavazzi
- Department of Clinical-Surgical, Diagnostic and Paediatric Sciences, University of Pavia, Pavia, Italy
- Anesthesia and Intensive Care, Fondazione Policlinico San Matteo Hospital IRCCS, Pavia, Italy
| | - Carsten Skurk
- Department of Cardiology Angiology and Intensive Care Medicine, Deutsches Herzzentrum der Charité (DHZC), Campus Benjamin Franklin, Charité - Universitätsmedizin Berlin, Berlin, Germany
- Deutsches Zentrum für Herz-Kreislauf-Forschung e.V., Berlin, Germany
| | - Kurt Huber
- 3rd Medical Department, Cardiology and Intensive Care Medicine, Wilhelminen Hospital, Vienna, Austria
| | - Allan Böhm
- Premedix Academy, Bratislava, Slovakia
- Faculty of Medicine, Comenius University in Bratislava, Bratislava, Slovakia
- Department of Acute Cardiology, National Institute of Cardiovascular Diseases, Bratislava, Slovakia
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Jánošíková L, Jankovič P, Kvet M, Ivanov G, Holod J, Berta I. Reorganization of an Emergency Medical System in a Mixed Urban-Rural Area. Int J Environ Res Public Health 2022; 19:12369. [PMID: 36231668 PMCID: PMC9564519 DOI: 10.3390/ijerph191912369] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 08/22/2022] [Revised: 09/23/2022] [Accepted: 09/25/2022] [Indexed: 06/16/2023]
Abstract
The reorganization of an emergency medical system means that we look for new locations of ambulance stations with the aim of improving the accessibility of the service. We applied two tools that are well known in the operations research community, namely mathematical programming, and computer simulation. Using the hierarchical pq-median model, we proposed optimal locations of the stations throughout the country and within large towns. Several solutions have been calculated that differ in the number of stations that are supposed to be relocated to new positions. The locations proposed by the mathematical programming model were evaluated via computer simulation. The approach was demonstrated under the conditions of the Slovak Republic using real historical data on ambulance dispatches. We have concluded that (i) the distribution of the stations proposed by the hierarchical pq-median model overcomes the current distribution; the performance of the system has significantly improved even if only 10% of the stations are relocated to new municipalities; (ii) the variant that relocates 40% of the stations is a reasonable compromise between the benefits and induced costs; (iii) optimizing station locations in big towns can significantly improve the local as well as the nationwide performance indicators; the response times in two regional capitals has reduced by more than 4 min.
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Affiliation(s)
- L’udmila Jánošíková
- Faculty of Management Science and Informatics, University of Žilina, Univerzitná 1, 010 26 Žilina, Slovakia
| | - Peter Jankovič
- Faculty of Management Science and Informatics, University of Žilina, Univerzitná 1, 010 26 Žilina, Slovakia
| | - Marek Kvet
- Faculty of Management Science and Informatics, University of Žilina, Univerzitná 1, 010 26 Žilina, Slovakia
| | - Gaston Ivanov
- EMS Command and Control Centre of the Slovak Republic, Trnavská Cesta 8/A, 820 05 Bratislava, Slovakia
| | - Jakub Holod
- EMS Command and Control Centre of the Slovak Republic, Trnavská Cesta 8/A, 820 05 Bratislava, Slovakia
| | - Imrich Berta
- EMS Command and Control Centre of the Slovak Republic, Trnavská Cesta 8/A, 820 05 Bratislava, Slovakia
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