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Root causes of COVID-19 data backlogs: a mixed methods analysis in four African countries

Oxford open digital health 2024年第SUPPL 1期2卷 i16-i28页

作者： Emily Carnahan Austin Van Grack Brian Kangethe Mamadou Mballo Diallo Dominic Mutai Oury Bah Hassan Mtenga Constant Kingongo Julia Ngomba Jessica Shearer Joy Kamunyori Robert Rosenbaum Colleen Oakes Maya Rivera Hildebrand Matthew Morio Mira Emmanuel-Fabula Center of Digital and Data Excellence PATH 2201 Westlake Ave Suite 200 Seattle WA 98121 USA. Research Department Maternal & Infant Health Consulting 1449 E Winder Lane Salt Lake City Utah 84124-1401. Center of Digital and Data Excellence PATH Megacity Plaza Mezzanine Floor Along Nairobi-Kisumu Road Kisumu 40123 Kenya. Center of Digital and Data Excellence PATH Africa Outsourcing 131 Cité Keur Gorgui 6eme étage immeuble Auchan 99999 Dakar Senegal. Noncommunicable Diseases PATH A.C.S. Plaza 4th floor Lenana Road and Galana Road Nairobi 00100 Kenya. Center of Digital and Data Excellence PATH Oasis Office Park 3rd Floor Off Haile Selassie Rd Oyster Bay Dar es Salaam Tanzania. PO Box 13600. DRC Country Program PATH Matrix Tower Building 119 Blvd du 30 Juin 5th Floor Gombe Kinshasa Kinshasa Congo Democratic Republic of the Congo. Health Systems Innovation and Delivery PATH 455 Massachusetts Ave NW Suite 1000 Washington DC 20001 USA. Bureau for Global Health United States Agency for International Development GHTASC-Credence 500 D Street SW Washington DC 20024 USA. Center of Digital and Data Excellence PATH Rue de Varembe 7 Foundation for Appropriate Technology in Health 1202 Geneva Switzerland. Medical Devices and Health Technologies PATH 2201 Westlake Ave Suite 200 Seattle WA 98121 USA. Market Dynamics PATH Rue de Varembe 7 Foundation for Appropriate Technology in Health 1202 Geneva Switzerland.

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Genetic drivers of heterogeneity in type 2 diabetes pathophysiology

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Nature 2024年第8003期627卷 347-357页

作者： Ken Suzuki Konstantinos Hatzikotoulas Lorraine Southam Henry J Taylor Xianyong Yin Kim M Lorenz Ravi Mandla Alicia Huerta-Chagoya Giorgio E M Melloni Stavroula Kanoni Nigel W Rayner Ozvan Bocher Ana Luiza Arruda Kyuto Sonehara Shinichi Namba Simon S K Lee Michael H Preuss Lauren E Petty Philip Schroeder Brett Vanderwerff Mart Kals Fiona Bragg Kuang Lin Xiuqing Guo Weihua Zhang Jie Yao Young Jin Kim Mariaelisa Graff Fumihiko Takeuchi Jana Nano Amel Lamri Masahiro Nakatochi Sanghoon Moon Robert A Scott James P Cook Jung-Jin Lee Ian Pan Daniel Taliun Esteban J Parra Jin-Fang Chai Lawrence F Bielak Yasuharu Tabara Yang Hai Gudmar Thorleifsson Niels Grarup Tamar Sofer Matthias Wuttke Chloé Sarnowski Christian Gieger Darryl Nousome Stella Trompet Soo-Heon Kwak Jirong Long Meng Sun Lin Tong Wei-Min Chen Suraj S Nongmaithem Raymond Noordam Victor J Y Lim Claudia H T Tam Yoonjung Yoonie Joo Chien-Hsiun Chen Laura M Raffield Bram Peter Prins Aude Nicolas Lisa R Yanek Guanjie Chen Jennifer A Brody Edmond Kabagambe Ping An Anny H Xiang Hyeok Sun Choi Brian E Cade Jingyi Tan K Alaine Broadaway Alice Williamson Zoha Kamali Jinrui Cui Manonanthini Thangam Linda S Adair Adebowale Adeyemo Carlos A Aguilar-Salinas Tarunveer S Ahluwalia Sonia S Anand Alain Bertoni Jette Bork-Jensen Ivan Brandslund Thomas A Buchanan Charles F Burant Adam S Butterworth Mickaël Canouil Juliana C N Chan Li-Ching Chang Miao-Li Chee Ji Chen Shyh-Huei Chen Yuan-Tsong Chen Zhengming Chen Lee-Ming Chuang Mary Cushman John Danesh Swapan K Das H Janaka de Silva George Dedoussis Latchezar Dimitrov Ayo P Doumatey Shufa Du Qing Duan Kai-Uwe Eckardt Leslie S Emery Daniel S Evans Michele K Evans Krista Fischer James S Floyd Ian Ford Oscar H Franco Timothy M Frayling Barry I Freedman Pauline Genter Hertzel C Gerstein Vilmantas Giedraitis Clicerio González-Villalpando Maria Elena González-Villalpando Penny Gordon-Larsen Myron Gross Lindsay A Guare Sophie Hackinger Liisa Hakaste Sohee Han Andrew T Hattersley Christian Herder Momoko Horikoshi Annie-Green Howard Willa Centre for Genetics and Genomics Versus Arthritis Centre for Musculoskeletal Research Division of Musculoskeletal and Dermatological Sciences University of Manchester Manchester UK. Department of Diabetes and Metabolic Diseases Graduate School of Medicine University of Tokyo Tokyo Japan. Department of Statistical Genetics Osaka University Graduate School of Medicine Suita Japan. Institute of Translational Genomics Helmholtz Zentrum München German Research Center for Environmental Health Neuherberg Germany. konstantinos.hatzikotoulas@helmholtz-munich.de. Institute of Translational Genomics Helmholtz Zentrum München German Research Center for Environmental Health Neuherberg Germany. Center for Precision Health Research National Human Genome Research Institute National Institutes of Health Bethesda MD USA. British Heart Foundation Cardiovascular Epidemiology Unit Department of Public Health and Primary Care University of Cambridge Cambridge UK. Heart and Lung Research Institute University of Cambridge Cambridge UK. Department of Epidemiology School of Public Health Nanjing Medical University Nanjing China. Department of Biostatistics and Center for Statistical Genetics University of Michigan Ann Arbor MI USA. Corporal Michael J. Crescenz VA Medical Center Philadelphia PA USA. Department of Systems Pharmacology and Translational Therapeutics University of Pennsylvania Perelman School of Medicine Philadelphia PA USA. Department of Genetics University of Pennsylvania Perelman School of Medicine Philadelphia PA USA. Programs in Metabolism and Medical and Population Genetics Broad Institute of Harvard and MIT Cambridge MA USA. Diabetes Unit and Center for Genomic Medicine Massachusetts General Hospital Boston MA USA. TIMI Study Group Division of Cardiovascular Medicine Brigham and Women's Hospital Harvard Medical School Boston MA USA. William Harvey Research Institute Barts and the London School of Medicine and Dentistry Queen Mary University of London L

Type 2 diabetes (T2D) is a heterogeneous disease that develops through diverse pathophysiological processes and molecular mechanisms that are often specific to cell type. Here, to characterize the genetic contribution to these processes across ancestry groups, we aggregate genome-wide association study data from 2,535,601 individuals (39.7% not of European ancestry), including 428,452 cases of T2D. We identify 1,289 independent association signals at genome-wide significance (P < 5 × 10) that map to 611 loci, of which 145 loci are, to our knowledge, previously unreported. We define eight non-overlapping clusters of T2D signals that are characterized by distinct profiles of cardiometabolic trait associations. These clusters are differentially enriched for cell-type-specific regions of open chromatin, including pancreatic islets, adipocytes, endothelial cells and enteroendocrine cells. We build cluster-specific partitioned polygenic scores in a further 279,552 individuals of diverse ancestry, including 30,288 cases of T2D, and test their association with T2D-related vascular outcomes. Cluster-specific partitioned polygenic scores are associated with coronary artery disease, peripheral artery disease and end-stage diabetic nephropathy across ancestry groups, highlighting the importance of obesity-related processes in the development of vascular outcomes. Our findings show the value of integrating multi-ancestry genome-wide association study data with single-cell epigenomics to disentangle the aetiological heterogeneity that drives the development and progression of T2D. This might offer a route to optimize global access to genetically informed diabetes care.

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Geographic information discipline development: Demands, Strategy and challenges

Information Geography

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Information Geography 2025年第1期1卷

作者： Guonian Lü Juhua Xiong Mingguang Wu Linwang Yuan Jonathan Li Min Chen Zhaoyuan Yu Liangchen Zhou Songshan Yue Xueying Zhang Xudong Li Xin Li Fahu Chen Chenghu Zhou Zhonghao Zhang Yang Gao Key Laboratory of Virtual Geographic Environment of Ministry of Education Nanjing Normal University Nanjing Jiangsu 210023 China School of Geography Nanjing Normal University Nanjing Jiangsu 210023 China State Key Laboratory Cultivation Base of Geographic Environment Evolution (Jiangsu Province) Nanjing Jiangsu 210023 China Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application Nanjing Jiangsu 210023 China Department of Earth Sciences National Natural Science Foundation of China Beijing 100085 China Department of Geography of Environmental Management University of Waterloo 100 University Avenue Waterloo N2L3G1 Ontario Canada Lishui Construction Technology Management Center Lishui 323050 China Institute of Tibetan Plateau Research Chinese Academy of Sciences Key Laboratory of Tibetan Plateau Earth System and Resources Environment National Tibetan Plateau Data Center Beijing 100101 China College of Earth and Environmental Sciences Lanzhou University Key Laboratory of Western China's Environmental Systems Ministry of Education Lanzhou Gansu 730000 China Institute of Tibetan Plateau Research Chinese Academy of Sciences Key Laboratory of Tibetan Plateau Earth System and Resources Environment Paleoecology and Human Adaptation Research Group Beijing 100101 China State Key Laboratory of Resources and Environmental Information System Institute of Geographic Sciences and Natural Resources Research Chinese Academy of Sciences Beijing 100101 China College of Geography and Remote Sensing Hohai University Nanjing Jiangsu 210098 China

Geographic Information Discipline serves as a critical pillar driving continuous innovation in Earth system science, geography, smart cities, and ecological conservation. Against the backdrop of intensified global environmental changes and diversified societal demands, this discipline faces a dual-challenge of theoretical innovation and technological breakthrough. This paper analyzes geographic information discipline from three perspectives: disciplinary demands, development strategies, and frontier challenges. In terms of disciplinary demands, we explores the requirements of Earth system science for multi-source data integration, dynamic model construction, and cross-scale analysis, as well as the evolving trends of geography within the framework of the ternary world (i.e., physical, human, and information). Regarding development strategies, we proposes strategic pathways from a multidisciplinary perspective encompassing information science, information geography, and geolinguistics. These include advancing the discipline through geographic language development, multi-modal representation, virtual-real integration, and the establishment of a universal language framework. Meanwhile, the paper addresses current theoretical and technical bottlenecks, such as insufficient modeling of information world, limited capacity for high-dimensional dynamic data processing, and the technical demand for real-time 3D scene representation. We emphasizes that under the globalization and digital transformation, geoinformatics is undergoing a comprehensive leap from the physical-human duality to the physical-human-information triad by integrating theories from information science, geography, and cognitive science. Moving forward, the discipline must focus on intelligent systems, multidimensional dynamic analysis, and multidisciplinary collaborative innovation to better address complex geographic phenomena and provide scientific and technological support for global environmental manage

关键词： Geographic information discipline Geographic information system Geographic information science Information geography Geolinguistics Geographic scene Ternary world

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Ontologizing Health systems data at Scale: Making Translational Discovery a Reality

arXiv

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arXiv 2022年

作者： Callahan, Tiffany J. Stefanski, Adrianne L. Wyrwa, Jordan M. Zeng, Chenjie Ostropolets, Anna Banda, Juan M. Baumgartner, William A. Boyce, Richard D. Casiraghi, Elena Coleman, Ben D. Collins, Janine H. Deakyne-Davies, Sara J. Feinstein, James A. Haendel, Melissa A. Lin, Asiyah Y. Martin, Blake Matentzoglu, Nicolas A. Meeker, Daniella Reese, Justin Sinclair, Jessica Taneja, Sanya B. Trinkley, Katy E. Vasilevsky, Nicole A. Williams, Andrew Zhang, Xingman A. Denny, Joshua C. Robinson, Peter N. Ryan, Patrick Hripcsak, George Bennett, Tellen D. Hunter, Lawrence E. Kahn, Michael G. Computational Bioscience Program University of Colorado Anschutz Medical Campus AuroraCO80045 United States Department of Biomedical Informatics Columbia University Irving Medical Center New YorkNY10032 United States Department of Physical Medicine and Rehabilitation School of Medicine University of Colorado Anschutz Medical Campus AuroraCO80045 United States National Human Genome Research Institute National Institutes of Health BethesdaMD20892 United States Department of Computer Science Georgia State University AtlantaGA30303 United States Department of Biomedical Informatics University of Pittsburgh School of Medicine PittsburghPA15260 United States Computer Science Università degli Studi di Milano Milan20122 Italy Division of Environmental Genomics and Systems Biology Lawrence Berkeley National Laboratory BerkeleyCA94720 United States The Jackson Laboratory for Genomic Medicine FarmingtonCT06032 United States Department of Haematology University of Cambridge Cambridge United Kingdom Department of Research Informatics & Data Science Analytics Resource Center Children’s Hospital Colorado AuroraCO80045 United States University of Colorado Anschutz School of Medicine AuroraCO80045 United States Center for Health AI University of Colorado Anschutz Medical Campus AuroraCO80045 United States Departments of Biomedical Informatics and Pediatrics University of Colorado School of Medicine AuroraCO80045 United States Semanticly Athens Greece Yale School of Medicine New HavenCT06510 United States HealthLinc ValparaisoIN46383 United States Intelligent Systems Program University of Pittsburgh PittsburghPA15260 United States Department of Family Medicine University of Colorado Anschutz School of Medicine AuroraCO80045 United States Translational and Integrative Sciences Lab University of Colorado Anschutz Medical Campus AuroraCO80045 United States Tufts Institute for Clinical Research and Health Policy Studies Tufts University Bos

Background: Common data models solve many challenges of standardizing electronic health record (EHR) data, but are unable to semantically integrate all the resources needed for deep phenotyping. Open Biological and Biomedical Ontology (OBO) Foundry ontologies provide computable representations of biological knowledge and enable the integration of heterogeneous data. However, mapping EHR data to OBO ontologies requires significant manual curation and domain expertise. Objective: We introduce OMOP2OBO, an algorithm for mapping Observational Medical Outcomes Partnership (OMOP) vocabularies to OBO ontologies. Results: Using OMOP2OBO, we produced mappings for 92,367 conditions, 8611 drug ingredients, and 10,673 measurement results, which covered 68-99% of concepts used in clinical practice when examined across 24 hospitals. When used to phenotype rare disease patients, the mappings helped systematically identify undiagnosed patients who might benefit from genetic testing. Conclusions: By aligning OMOP vocabularies to OBO ontologies our algorithm presents new opportunities to advance EHR-based deep phenotyping. © 2022, CC BY.

关键词： Ontology

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Pressure sensitive shoe insoles and socks for rehabilitation applications

Pressure sensitive shoe insoles and socks for rehabilitation...

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International Conference on Application of Information and Communication Technologies (AICT)

作者： Josef Langer Florian Eibensteiner Jürgen Peterka Philipp Knaack Embedded Systems Lab Univ. of Applied Sciences of Upper Austria Hagenberg Austria Research & Development CDE Communications Data Engineering GmbH Hagenberg Austria

ISBN: (纸本)9781538664698

The foot pressure distribution, while standing, walking, or running, is an important parameter for gait analysis and feet health status in the field of sports, rehabilitation, or medical applications. In this paper, we show a system for improving medical rehabilitation for patients after musculoskeletal operations. Postoperative surgery for knee surgery is usually due to excessive movement during the rehabilitation phase. Non-invasive and gentle surgical procedures mean that patients are less likely to experience pain and are using their musculoskeletal system too early. With the presented solution consisting of pressure-sensitive shoe insoles and socks, we show a system for detecting overload conditions. We discuss the construction, the hardware and software architecture of the proposed solution, and show first measurement results.

关键词： Footwear Hardware Position measurement Pressure measurement Smart textiles Textiles

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Transfer learning versus multi-agent learning regarding distributed decision-making in highway traffic

arXiv

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arXiv 2018年

作者： Schutera, Mark Goby, Niklas Neumann, Dirk Reischl, Markus Institute for Automation and Applied Informatics Karlsruhe Institute of Technology Chair for Information Systems Research University of Freiburg IT Innovation Chapter Data Science ZF Friedrichshafen AG Research and Development ZF Friedrichshafen AG

Transportation and traffic are currently undergoing a rapid increase in terms of both scale and complexity. At the same time, an increasing share of traffic participants are being transformed into agents driven or supported by artificial intelligence resulting in mixed-intelligence traffic. This work explores the implications of distributed decision-making in mixed-intelligence traffic. The investigations are carried out on the basis of an online-simulated highway scenario, namely the MIT DeepTraffic simulation. In the first step traffic agents are trained by means of a deep reinforcement learning approach, being deployed inside an elitist evolutionary algorithm for hyperparameter search. The resulting architectures and training parameters are then utilized in order to either train a single autonomous traffic agent and transfer the learned weights onto a multi-agent scenario or else to conduct multi-agent learning directly. Both learning strategies are evaluated on different ratios of mixed-intelligence traffic. The strategies are assessed according to the average speed of all agents driven by artificial intelligence. Traffic patterns that provoke a reduction in traffic flow are analyzed with respect to the different strategies. Copyright © 2018, The Authors. All rights reserved.

关键词： Multi agent systems

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Author Correction: CRISPR screens reveal convergent targeting strategies against evolutionarily distinct chemoresistance in cancer

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Nature communications 2025年第1期16卷 1569页

作者： Chunge Zhong Wen-Jie Jiang Yingjia Yao Zexu Li You Li Shengnan Wang Xiaofeng Wang Wenjuan Zhu Siqi Wu Jing Wang Shuangshuang Fan Shixin Ma Yeshu Liu Han Zhang Wenchang Zhao Lu Zhao Yi Feng Zihan Li Ruifang Guo Li Yu Fengyun Pei Jun Hu Xingzhi Feng Zihuan Yang Zhengjia Yang Xueying Yang Yue Hou Danni Zhang Dake Xu Ren Sheng Yihao Li Lijun Liu Hua-Jun Wu Jun Huang Teng Fei Key Laboratory of Bioresource Research and Development of Liaoning Province College of Life and Health Sciences Northeastern University Shenyang 110819 China. National Frontiers Science Center for Industrial Intelligence and Systems Optimization Northeastern University Shenyang 110819 China. Key Laboratory of Data Analytics and Optimization for Smart Industry (Northeastern University) Ministry of Education Shenyang 110819 China. Foshan Graduate School of Innovation Northeastern University Foshan 528311 China. Peking University Third Hospital Beijing 100191 China. Department of Colorectal Surgery the Sixth Affiliated Hospital Sun Yat-sen University Guangzhou China. Clinical Research Center the Sixth Affiliated Hospital Sun Yat-sen University Guangzhou China. Guangdong Provincial Key Laboratory of Colorectal and Pelvic Floor Diseases the Sixth Affiliated Hospital Sun Yat-sen University Guangzhou China. Guangdong Institute of Gastroenterology Guangzhou China. Department of Cardiothoracic Surgery Jinqiu Hospital of Liaoning Province Shenyang China. Department of Thoracic Surgery The Fourth Affiliated Hospital of China Medical University Shenyang China. Key Laboratory for Anisotropy and Texture of Materials (Ministry of Education) School of Materials Science and Engineering Northeastern University Shenyang China. BeiGene Institute BeiGene (Shanghai) Research & Development Co. Ltd 200131 Shanghai China. Key laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing) Peking University Cancer Hospital & Institute Beijing 100142 China. hjwu@***. Department of Biomedical Informatics School of Basic Medical Sciences Peking University Health Science Center Beijing 100191 China. hjwu@***. Center for Precision Medicine Multi-Omics Research Institute of Advanced Clinical Medicine Peking University Beijing 100191 China. hjwu@***. Department of Colorectal Surgery the Sixth Affiliated Hospital Sun Yat-sen University Guangzhou China. huan

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Correction: Biosimilar recombinant follitropin alfa preparations versus the reference product (Gonal-F®) in couples undergoing assisted reproductive technology treatment: a systematic review and meta-analysis

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Reproductive biology and endocrinology : RB&E 2023年第1期21卷 68页

作者： Christos A Venetis Christoph Helwig Ben W Mol Su Jen Chua Salvatore Longobardi Raoul Orvieto Monica Lispi Ashleigh Storr Thomas D'Hooghe Unit for Human Reproduction 1st Dept of OB/Gyn Faculty of Medicine School of Health Sciences Aristotle University of Thessaloniki Thessaloniki Greece. Centre for Big Data Research in Health University of New South Wales Kensington Campus New South Wales Australia. IVF Australia Sydney NSW 2000 Australia. Global Biostatistics Merck KGaA Darmstadt Germany. Department of Obstetrics and Gynecology University of Monash Monash Clayton Victoria 3168 Australia. ben.mol@monash.edu. Alfred Health Melbourne VIC 3004 Australia. Global Clinical Development Merck Serono S.p.A (an affiliate of Merck KGaA Darmstadt 64293 Germany) Rome 00176 Italy. Department of Obstetrics and Gynecology Chaim Sheba Medical Center Tel-Hashomer Ramat Gan 52621 Israel. The Tarnesby-Tarnowski Chair for Family Planning and Fertility Regulation Sackler Faculty of Medicine Tel-Aviv University Tel Aviv-Yafo 6997801 Israel. University of Modena and Reggio Emilia Modena MO 41121 Italy. GlobalMedical Affairs Fertility Research and Development Merck KGaA F135/002 Darmstadt 64293 Germany. Flinders Fertility Adelaide South Australia 5045 Australia. College of Medicine and Public Health Flinders University Adelaide South Australia 5042 Australia. Research Group Reproductive Medicine Department of Development and Regeneration Organ Systems Group Biomedical Sciences KU Leuven (University of Leuven) Leuven 3000 Belgium. Department of Obstetrics and Gynecology Yale University New Haven CT 06510 USA.

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A phenome-wide association study of uterine fibroids reveals a marked burden of comorbidities

Communications Medicine

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Communications Medicine 2025年第1期5卷 1-15页

作者： Jasper, Elizabeth A. Mautz, Brian S. Hellwege, Jacklyn N. Piekos, Jacqueline A. Jones, Sarah H. Zhang, Yanfei Torstenson, Eric S. Pendergrass, Sarah A. Lee, Ming Ta Michael Edwards, Todd L. Velez Edwards, Digna R. Division of Quantitative and Clinical Sciences Department of Obstetrics and Gynecology Vanderbilt University Medical Center Nashville TN United States Center for Precision Medicine Vanderbilt University Medical Center Nashville TN United States Institute for Medicine and Public Health Vanderbilt University Medical Center Nashville TN United States Vanderbilt Epidemiology Center Vanderbilt University Nashville TN United States Vanderbilt Genetics Institute Vanderbilt University Nashville TN United States Population Analytics Analytics & Insights Data Sciences Janssen Research & Development Spring House PA United States Division of Genetic Medicine Department of Medicine Vanderbilt University Medical Center Nashville TN United States Genomic Medicine Institute Geisinger Health Systems Danville PA United States Department of Biomedical Informatics Vanderbilt University Medical Center Nashville TN United States Division of Epidemiology Department of Medicine Vanderbilt University Medical Center Nashville TN United States Genentech South San Francisco CA United States Department of Biomedical and Translational Informatics Geisinger Rockville MD United States

Background: The burden of comorbidities in those with uterine fibroids compared to those without fibroids is understudied. We performed a phenome-wide association study to systematically assess the association between fibroids and other conditions. Methods: Vanderbilt University Medical Center’s Synthetic Derivative and Geisinger Health System database, two electronic health record databases, were used for discovery and validation. Non-Hispanic Black and White females were included. Fibroid cases were identified through a previously validated algorithm. Race-stratified and multi-population phenome-wide association analyses, adjusting for age and body mass index, were performed before statistically significant, validated results were meta-analyzed. Results: There were 52,295 and 26,918 (9022 and 10,232 fibroid cases) females included in discovery and validation analyses. In multi-population meta-analysis, 389 conditions were associated with fibroid risk, with evidence of enrichment of circulatory, dermatologic, genitourinary, musculoskeletal, and sense organ conditions. The strongest associations within and across racial groups included conditions previously associated with fibroids. Numerous novel diagnoses, including cancers in female genital organs, were tied to fibroid status. Conclusions: Overall, individuals with fibroids have a marked increase in comorbidities compared to those without fibroids. This approach to evaluate the health context of fibroids highlights the potential to understand fibroid etiology through studying the common biology of comorbid diagnoses and through disease networks. © The Author(s) 2025.

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Global, regional, and national burden of neck pain, 1990–2020, and projections to 2050: a systematic analysis of the Global Burden of Disease Study 2021

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The Lancet Rheumatology 2024年第3期6卷 e142-e155页

作者： Wu, Ai-Min Cross, Marita Elliott, James M. Culbreth, Garland T. Cousin, Ewerton Haile, Lydia M. Steinmetz, Jaimie D. Hagins, Hailey Kopec, Jacek A. Brooks, Peter M. Woolf, Anthony D. Kopansky-Giles, Deborah R. Walton, David M. Treleaven, Julia M. Dreinhoefer, Karsten E. Betteridge, Neil Abbasifard, Mitra Abbasi-Kangevari, Zeinab Addo, Isaac Yeboah Adesina, Miracle Ayomikun Adnani, Qorinah Estiningtyas Sakilah Aithala, Janardhana P. Alhalaiqa, Fadwa Alhalaiqa Naji Alimohamadi, Yousef Amiri, Sohrab Amu, Hubert Antony, Benny Arabloo, Jalal Aravkin, Aleksandr Y. Asghari-Jafarabadi, Mohammad Atomsa, Gamechu Hunde Azadnajafabad, Sina Azzam, Ahmed Y. Baghdadi, Soroush Balogun, Saliu A. Balta, Asaminew Birhanu Banach, Maciej Banakar, Morteza Barrow, Amadou Bashiri, Azadeh Bekele, Alehegn Bensenor, Isabela M. Bhardwaj, Pankaj Bhat, Ajay Nagesh Bilchut, Awraris Hailu Briggs, Andrew M. Buchbinder, Rachelle Cao, Chao Chaurasia, Akhilanand Chirinos-Caceres, Jesus Lorenzo Christensen, Steffan Wittrup McPhee Coberly, Kaleb Dadras, Omid Dai, Xiaochen de Luca, Katie Dehghan, Azizallah Dong, Huan-Ji Ekholuenetale, Michael Elhadi, Muhammed Eshetu, Habitu Birhan Eskandarieh, Sharareh Etaee, Farshid Fagbamigbe, Adeniyi Francis Fares, Jawad Fatehizadeh, Ali Feizkhah, Alireza Ferreira, Manuela L. Ferreira, Nuno Fischer, Florian Franklin, Richard Charles Ganesan, Balasankar Gebremichael, Mathewos Alemu Gerema, Urge Gholami, Ali Ghozy, Sherief Gill, Tiffany K. Golechha, Mahaveer Goleij, Pouya Golinelli, Davide Graham, Simon Matthew Haj-Mirzaian, Arvin Harlianto, Netanja I. Hartvigsen, Jan Hasanian, Mohammad Hassen, Mohammed Bheser Hay, Simon I. Hebert, Jeffrey J. Heidari, Golnaz Hoveidaei, Amir Human Hsiao, Alexander Kevin Ibitoye, Segun Emmanuel Iwu, Chidozie C.D. Jacob, Louis Janodia, Manthan Dilipkumar Jin, Yingzhao Jonas, Jost B. Joshua, Charity Ehimwenma Kandel, Himal Khader, Yousef Saleh Khajuria, Himanshu Khan, Ejaz Ahmad Khan, Moien A.B. Khatatbeh, Moawiah Mohammad Khateri, Sorour Khayat Kashani, Hamid Reza Khonji, Mohammad Saeid Department of Orthopaedics The Second Affiliated Hospital of Wenzhou Medical University Wenzhou China Faculty of Medicine and Health University of Sydney Sydney NSW Australia Global Alliance for Musculoskeletal Health Sydney NSW Australia Kolling Institute of Medical Research University of Sydney Northern Sydney Local Health District St Leonards NSW Australia Department of Physical Therapy and Human Movement Sciences Northwestern University Chicago IL United States Institute for Health Metrics and Evaluation University of Washington Seattle WA United States School of Population and Public Health University of British Columbia Vancouver BC Canada Arthritis Research Canada Richmond BC Canada US Department of Veterans Affairs (VA) Birmingham AL United States Centre for Health Policy University of Melbourne Melbourne VIC Australia Bone and Joint Research Group Royal Cornwall Hospital Truro United Kingdom Department of Family and Community Medicine University of Toronto Toronto ON Canada Department of Research and Innovation Canadian Memorial Chiropractic College Toronto ON Canada Department of Physical Therapy University of Sydney Sydney NSW Australia School of Physical Therapy Western University London ON Canada School of Health and Rehabilitation Sciences The University of Queensland Brisbane Australia Center of Musculoskeletal Surgery Charité Universitätsmedizin Berlin (Charité Medical University Berlin) Berlin Germany London United Kingdom Department of Internal Medicine Rafsanjan University of Medical Sciences Rafsanjan Iran Clinical Research Development Unit Rafsanjan University of Medical Sciences Rafsanjan Iran Social Determinants of Health Research Center Shahid Beheshti University of Medical Sciences Tehran Iran Non-communicable Diseases Research Center Tehran University of Medical Sciences Tehran Iran Tehran University of Medical Sciences Tehran Iran Centre for Social Research in Health University of New South Wales Sydney NSW

Background: Neck pain is a highly prevalent condition that leads to considerable pain, disability, and economic cost. We present the most current estimates of neck pain prevalence and years lived with disability (YLDs) from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) by age, sex, and location, with forecasted prevalence to 2050. Methods: Systematic reviews identified population-representative surveys used to estimate the prevalence of and YLDs from neck pain in 204 countries and territories, spanning from 1990 to 2020, with additional data from opportunistic review. Medical claims data from Taiwan (province of China) were also included. Input data were pooled using DisMod-MR 2.1, a Bayesian meta-regression tool. Prevalence was forecast to 2050 using a mixed-effects model using Socio-demographic Index as a predictor and multiplying by projected population estimates. We present 95% UIs for every metric based on the 2·5th and 97·5th percentiles of 100 draws of the posterior distribution. Findings: Globally, in 2020, neck pain affected 203 million (95% uncertainty interval [UI] 163–253) people. The global age-standardised prevalence rate of neck pain was estimated to be 2450 (1960–3040) per 100 000 population and global age-standardised YLD rate was estimated to be 244 (165–346) per 100 000. The age-standardised prevalence rate remained stable between 1990 and 2020 (percentage change 0·2% [–1·3 to 1·7]). Globally, females had a higher age-standardised prevalence rate (2890 [2330–3620] per 100 000) than males (2000 [1600–2480] per 100 000), with the prevalence peaking between 45 years and 74 years in male and female sexes. By 2050, the estimated global number of neck pain cases is projected to be 269 million (219–322), with an increase of 32·5% (23·9–42·3) from 2020 to 2050. Decomposition analysis of the projections showed population growth was the primary contributing factor, followed by population ageing. Interpretation: Although age-standardi

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