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Mollalo A, Hamidi B, Lenert L, Alekseyenko AV. Application of Spatial Analysis for Electronic Health Records: Characterizing Patient Phenotypes and Emerging Trends. RESEARCH SQUARE 2024:rs.3.rs-3443865. [PMID: 37886509 PMCID: PMC10602163 DOI: 10.21203/rs.3.rs-3443865/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/28/2023]
Abstract
Background Electronic health records (EHR) commonly contain patient addresses that provide valuable data for geocoding and spatial analysis, enabling more comprehensive descriptions of individual patients for clinical purposes. Despite the widespread use of EHR in clinical decision support and interventions, no systematic review has examined the extent to which spatial analysis is used to characterize patient phenotypes. Objective This study reviews advanced spatial analyses that employed individual-level health data from EHR within the US to characterize patient phenotypes. Methods We systematically evaluated English-language peer-reviewed articles from PubMed/MEDLINE, Scopus, Web of Science, and Google Scholar databases from inception to August 20, 2023, without imposing constraints on time, study design, or specific health domains. Results Only 49 articles met the eligibility criteria. These articles utilized diverse spatial methods, with a predominant focus on clustering techniques, while spatiotemporal analysis (frequentist and Bayesian) and modeling were relatively underexplored. A noteworthy surge (n = 42, 85.7%) in publications was observed post-2017. The publications investigated a variety of adult and pediatric clinical areas, including infectious disease, endocrinology, and cardiology, using phenotypes defined over a range of data domains, such as demographics, diagnoses, and visits. The primary health outcomes investigated were asthma, hypertension, and diabetes. Notably, patient phenotypes involving genomics, imaging, and notes were rarely utilized. Conclusions This review underscores the growing interest in spatial analysis of EHR-derived data and highlights knowledge gaps in clinical health, phenotype domains, and spatial methodologies. Additionally, this review proposes guidelines for harnessing the potential of spatial analysis to enhance the context of individual patients for future clinical decision support.
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Bieber K, Hundt JE, Yu X, Ehlers M, Petersen F, Karsten CM, Köhl J, Kridin K, Kalies K, Kasprick A, Goletz S, Humrich JY, Manz RA, Künstner A, Hammers CM, Akbarzadeh R, Busch H, Sadik CD, Lange T, Grasshoff H, Hackel AM, Erdmann J, König I, Raasch W, Becker M, Kerstein-Stähle A, Lamprecht P, Riemekasten G, Schmidt E, Ludwig RJ. Autoimmune pre-disease. Autoimmun Rev 2023; 22:103236. [PMID: 36436750 DOI: 10.1016/j.autrev.2022.103236] [Citation(s) in RCA: 21] [Impact Index Per Article: 21.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/22/2022] [Accepted: 11/17/2022] [Indexed: 11/27/2022]
Abstract
Approximately 5% of the world-wide population is affected by autoimmune diseases. Overall, autoimmune diseases are still difficult to treat, impose a high burden on patients, and have a significant economic impact. Like other complex diseases, e.g., cancer, autoimmune diseases develop over several years. Decisive steps in the development of autoimmune diseases are (i) the development of autoantigen-specific lymphocytes and (often) autoantibodies and (ii) potentially clinical disease manifestation at a later stage. However, not all healthy individuals with autoantibodies develop disease manifestations. Identifying autoantibody-positive healthy individuals and monitoring and inhibiting their switch to inflammatory autoimmune disease conditions are currently in their infancy. The switch from harmless to inflammatory autoantigen-specific T and B-cell and autoantibody responses seems to be the hallmark for the decisive factor in inflammatory autoimmune disease conditions. Accordingly, biomarkers allowing us to predict this progression would have a significant impact. Several factors, such as genetics and the environment, especially diet, smoking, exposure to pollutants, infections, stress, and shift work, might influence the progression from harmless to inflammatory autoimmune conditions. To inspire research directed at defining and ultimately targeting autoimmune predisease, here, we review published evidence underlying the progression from health to autoimmune predisease and ultimately to clinically manifest inflammatory autoimmune disease, addressing the following 3 questions: (i) what is the current status, (ii) what is missing, (iii) and what are the future perspectives for defining and modulating autoimmune predisease.
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Affiliation(s)
- Katja Bieber
- Lübeck Institute of Experimental Dermatology and Center for Research on Inflammation of the Skin, University of Lübeck, Germany
| | - Jennifer E Hundt
- Lübeck Institute of Experimental Dermatology and Center for Research on Inflammation of the Skin, University of Lübeck, Germany
| | - Xinhua Yu
- Priority Area Chronic Lung Diseases, Research Center Borstel, Airway Research Center North (ARCN), Member of the German Center for Lung Research (DZL), Borstel, Germany
| | - Marc Ehlers
- Institute of Nutritional Medicine, University of Lübeck and University Hospital Schleswig-Holstein, Lübeck, Germany
| | - Frank Petersen
- Priority Area Chronic Lung Diseases, Research Center Borstel, Airway Research Center North (ARCN), Member of the German Center for Lung Research (DZL), Borstel, Germany
| | - Christian M Karsten
- Institute for Systemic Inflammation Research, University of Lübeck, 23562 Lübeck, Germany
| | - Jörg Köhl
- Institute for Systemic Inflammation Research, University of Lübeck, 23562 Lübeck, Germany; Division of Immunobiology, Cincinnati Children's Hospital and University of Cincinnati College of Medicine, Cincinnati, OH 45229, USA
| | - Khalaf Kridin
- Lübeck Institute of Experimental Dermatology and Center for Research on Inflammation of the Skin, University of Lübeck, Germany; Azrieli Faculty of Medicine, Bar-Ilan University, Safed, Israel; Unit of Dermatology and Skin Research Laboratory, Baruch Padeh Medical Center, Poriya, Israel
| | - Kathrin Kalies
- Institute of Anatomy, University of Lübeck, Lübeck, Germany
| | - Anika Kasprick
- Lübeck Institute of Experimental Dermatology and Center for Research on Inflammation of the Skin, University of Lübeck, Germany
| | - Stephanie Goletz
- Lübeck Institute of Experimental Dermatology and Center for Research on Inflammation of the Skin, University of Lübeck, Germany
| | - Jens Y Humrich
- Department of Rheumatology and Clinical Immunology, University of Lübeck, Lübeck, Germany
| | - Rudolf A Manz
- Institute for Systemic Inflammation Research, University of Lübeck, 23562 Lübeck, Germany
| | - Axel Künstner
- Lübeck Institute of Experimental Dermatology and Center for Research on Inflammation of the Skin, University of Lübeck, Germany
| | - Christoph M Hammers
- Lübeck Institute of Experimental Dermatology and Center for Research on Inflammation of the Skin, University of Lübeck, Germany
| | - Reza Akbarzadeh
- Department of Rheumatology and Clinical Immunology, University of Lübeck, Lübeck, Germany
| | - Hauke Busch
- Lübeck Institute of Experimental Dermatology and Center for Research on Inflammation of the Skin, University of Lübeck, Germany
| | | | - Tanja Lange
- Department of Rheumatology and Clinical Immunology, University of Lübeck, Lübeck, Germany
| | - Hanna Grasshoff
- Department of Rheumatology and Clinical Immunology, University of Lübeck, Lübeck, Germany
| | - Alexander M Hackel
- Department of Rheumatology and Clinical Immunology, University of Lübeck, Lübeck, Germany
| | - Jeanette Erdmann
- Institute of Medical Biometry and Statistics, University of Lübeck, Lübeck, Germany
| | - Inke König
- Institute for Cardiogenetics, University of Lübeck, Lübeck, Germany
| | - Walter Raasch
- Institute of Experimental and Clinical Pharmacology and Toxicology, University of Lübeck, Lübeck, Germany
| | - Mareike Becker
- Department of Dermatology, University of Lübeck, Lübeck, Germany
| | - Anja Kerstein-Stähle
- Department of Rheumatology and Clinical Immunology, University of Lübeck, Lübeck, Germany
| | - Peter Lamprecht
- Department of Rheumatology and Clinical Immunology, University of Lübeck, Lübeck, Germany
| | - Gabriela Riemekasten
- Department of Rheumatology and Clinical Immunology, University of Lübeck, Lübeck, Germany
| | - Enno Schmidt
- Lübeck Institute of Experimental Dermatology and Center for Research on Inflammation of the Skin, University of Lübeck, Germany; Department of Dermatology, University of Lübeck, Lübeck, Germany
| | - Ralf J Ludwig
- Lübeck Institute of Experimental Dermatology and Center for Research on Inflammation of the Skin, University of Lübeck, Germany.
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Hossain MM, Wilkerson J, McGrath JA, Farhadi PN, Brokamp C, Khan MTF, Goldberg B, Brunner HI, Macaluso M, Miller FW, Rider LG. The Geospatial Distribution of Myositis and Its Phenotypes in the United States and Associations With Roadways: Findings From a National Myositis Patient Registry. Front Med (Lausanne) 2022; 9:842586. [PMID: 35372396 PMCID: PMC8966380 DOI: 10.3389/fmed.2022.842586] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/23/2021] [Accepted: 02/04/2022] [Indexed: 11/23/2022] Open
Abstract
Background Little is known about the spatial distribution of idiopathic inflammatory myopathies (IIM) in the United States (U.S.), or their geospatial associations. Methods We studied a national myositis patient registry, with cases diagnosed in the contiguous U.S. from 1985–2011 and comprised of dermatomyositis (DM, n = 484), polymyositis (PM, n = 358), and inclusion body myositis (IBM, n = 318) patients. To assess the association of myositis prevalence with distance from roads, we employed log-Gaussian Cox process models, offset with population density. Results The U.S. IIM case distribution demonstrated a higher concentration in the Northest. DM, IBM, and cases with lung disease were more common in the East, whereas PM cases were more common in the Southeast. One area in the West and one area in the South had a significant excess in cases of DM relative to PM and of cases with lung disease relative to those without lung disease, respectively. IIM cases tended to cluster, with between-points interactions more intense in the Northeast and less in the South. There was a trend of a higher prevalence of IIM and its major phenotypes among people living within 50 m of a roadway relative to living beyond 200 m. Demographic characteristics, rural-urban commuting area, and female percentage were significantly associated with the prevalence of IIM and with major phenotypes. Conclusions Using a large U.S. database to evaluate the spatial distribution of IIM and its phenotypes, this study suggests clustering in some regions of the U.S. and a possible association of proximity to roadways.
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Affiliation(s)
- Md M Hossain
- Division of Biostatistics and Epidemiology, Cincinnati Children's Hospital and Medical Center, Cincinnati, OH, United States.,Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, OH, United States
| | - Jesse Wilkerson
- Social and Scientific Systems, A DLH Holdings Corp Company, Durham, NC, United States
| | - John A McGrath
- Social and Scientific Systems, A DLH Holdings Corp Company, Durham, NC, United States
| | - Payam N Farhadi
- Environmental Autoimmunity Group, Clinical Research Branch, National Institute of Environmental Health Sciences, National Institutes of Health, Department of Health and Human Services, Bethesda, MD, United States.,Kelly Government Solutions, Rockville, MD, United States
| | - Cole Brokamp
- Division of Biostatistics and Epidemiology, Cincinnati Children's Hospital and Medical Center, Cincinnati, OH, United States.,Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, OH, United States
| | - Md T F Khan
- Division of Biostatistics and Bioinformatics, University of Cincinnati, Cincinnati, OH, United States
| | - Bob Goldberg
- The Myositis Association, Alexandria, VA, United States
| | - Hermine I Brunner
- Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, OH, United States.,Division of Rheumatology, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, United States
| | - Maurizio Macaluso
- Division of Biostatistics and Epidemiology, Cincinnati Children's Hospital and Medical Center, Cincinnati, OH, United States.,Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, OH, United States
| | - Frederick W Miller
- Environmental Autoimmunity Group, Clinical Research Branch, National Institute of Environmental Health Sciences, National Institutes of Health, Department of Health and Human Services, Bethesda, MD, United States
| | - Lisa G Rider
- Environmental Autoimmunity Group, Clinical Research Branch, National Institute of Environmental Health Sciences, National Institutes of Health, Department of Health and Human Services, Bethesda, MD, United States
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Bax CE, Maddukuri S, Ravishankar A, Pappas-Taffer L, Werth VP. Environmental triggers of dermatomyositis: a narrative review. ANNALS OF TRANSLATIONAL MEDICINE 2021; 9:434. [PMID: 33842655 PMCID: PMC8033368 DOI: 10.21037/atm-20-3719] [Citation(s) in RCA: 19] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 12/02/2022]
Abstract
Dermatomyositis (DM) is an autoimmune disease that affects the skin, lungs, and muscle. Although the pathogenesis of DM is not completely understood, several environmental triggers have been linked to DM onset or flare. This article specifically examines the effects of herbal supplements, drugs, infections, ultraviolet (UV) radiation, and environmental pollutants on the onset or exacerbation of DM. Herbal supplements such as Spirulina platensis, Aphanizomenon flos-aquae, Chlorella, Echinacea, and Alfalfa have been implicated and are frequently used in health foods. Medications such as hydroxyurea, TNF-α inhibitors, immune checkpoint inhibitors (ICI), and penicillamine, as well as certain viral infections, such as parvovirus B19, coxsackie virus, polyomavirus, Epstein-Barr virus (EBV), hepatitis, influenza, and human immunodeficiency viruses (HIV) have been associated with DM onset. Bacterial infections and vaccinations have also been linked to the development of DM. Additional environmental factors, including UV radiation and air pollutants, such as silica, biological/mineral dust, and particulate air matter from vehicle and industrial emissions, may also play a role in DM pathogenesis. Overall, there is general agreement that an autoimmune attack of the skin, muscle, and lungs in DM can be triggered by various environmental factors and warrants further investigation.
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Affiliation(s)
- Christina E Bax
- Corporal Michael J. Crescenz VAMC, Philadelphia, PA, USA.,Department of Dermatology, University of Pennsylvania, Philadelphia, PA, USA
| | - Spandana Maddukuri
- Corporal Michael J. Crescenz VAMC, Philadelphia, PA, USA.,Department of Dermatology, University of Pennsylvania, Philadelphia, PA, USA
| | - Adarsh Ravishankar
- Corporal Michael J. Crescenz VAMC, Philadelphia, PA, USA.,Department of Dermatology, University of Pennsylvania, Philadelphia, PA, USA
| | - Lisa Pappas-Taffer
- Corporal Michael J. Crescenz VAMC, Philadelphia, PA, USA.,Department of Dermatology, University of Pennsylvania, Philadelphia, PA, USA
| | - Victoria P Werth
- Corporal Michael J. Crescenz VAMC, Philadelphia, PA, USA.,Department of Dermatology, University of Pennsylvania, Philadelphia, PA, USA
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