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JACC: Advances 2024年第7P2期3卷 101051页

作者： Heo, Rachel H. Foroutan, Farid De Luca, Enza Albertini, Lisa Rac, Valeria E. Cafazzo, Joseph A. Hershman, Steve G. Duero Posada, Juan G. Ross, Heather J. Moayedi, Yasbanoo University of Toronto Ted Rogers Centre for Heart Research University of Toronto Program for Health System and Technology Evaluation Toronto General Hospital Research Institute University Health Network Institute of Health Policy Management and Evaluation Dalla Lana School of Public Health University of Toronto Centre for Digital Therapeutics Biomedical Engineering University Health Network Institute of Health Policy Management and Evaluation Institute of Biomedical Engineering University of Toronto School of Information The University of Texas at Austin

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Experiences and perceptions of patients and providers participating in remote titration of heart failure medication facilitated by telemonitoring: Qualitative study

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JMIR Cardio 2021年第2期5卷 e28259页

作者： Artanian, Veronica Ware, Patrick Rac, Valeria E. Ross, Heather J. Seto, Emily Institute of Health Policy. Management and Evaluation Dalla Lana School of Public Health University of Toronto Toronto ON Canada Centre for Global eHealth Innovation Techna Institute University Health Network Toronto ON Canada Program for Health System and Technology Evaluation Toronto General Hospital Research Institute University Health Network Toronto ON Canada Ted Rogers Centre for Heart Research Peter Munk Cardiac Centre University Health Network Toronto ON Canada Toronto General Hospital Research Institute University Health Network Toronto ON Canada Department of Medicine University of Toronto Toronto ON Canada

Background: Guideline-directed medical therapy (GDMT), optimized to target doses, improves health outcomes in patients with heart failure. However, GDMT remains underused, with <25% of patients receiving target doses in clinical practice. A randomized controlled trial was conducted at the Peter Munk Cardiac Centre in Toronto to compare a remote GDMT titration intervention with standard in-office titration. This randomized controlled trial found that remote titration increased the proportion of patients who achieved optimal GDMT doses, decreased the time to dose optimization, and reduced the number of essential clinic visits. This paper presents findings from the qualitative component of the mixed methods study, which evaluated the implementation of the remote titration intervention. Objective: The objective of the qualitative component is to assess the perceptions and experiences of clinicians and patients with heart failure who participated in the remote titration intervention to identify factors that affected the implementation of the intervention. Methods: We conducted semistructured interviews with clinicians (n=5) and patients (n=11) who participated in the remote titration intervention. Questions probed the experiences of the participants to identify factors that can serve as barriers and facilitators to its implementation. Conventional content analysis was first used to analyze the interviews and gain direct information based on the participants' unique perspectives. Subsequently, the generated themes were delineated and mapped following a multilevel framework. Results: Patients and clinicians indicated that the intervention was easy to use, integrated well into their routines, and removed practical barriers to titration. Key implementation facilitators from the patients' perspective included the reduction in clinic visits and daily monitoring of their condition, whereas clinicians emphasized the benefits of rapid drug titration and efficient patient manageme

关键词： Heart failure Mhealth Mobile phone Monitoring Qualitative Remote Telemonitoring Titration

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Question-Answering system Extracts Information on Injection Drug Use from Clinical Notes

arXiv

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arXiv 2023年

作者： Mahbub, Maria Goethert, Ian Danciu, Ioana Knight, Kathryn Srinivasan, Sudarshan Tamang, Suzanne Rozenberg-Ben-Dror, Karine Solares, Hugo Martins, Susana Trafton, Jodie Begoli, Edmon Peterson, Gregory D. Cyber Resilience and Intelligence Division Oak Ridge National Laboratory Oak RidgeTN United States Information Technology Services Division Oak Ridge National Laboratory Oak RidgeTN United States Computational Sciences and Engineering Division Oak Ridge National Laboratory Oak RidgeTN United States Department of Biomedical Informatics Vanderbilt University NashvilleTN United States Program Evaluation and Resource Center Office of Mental Health and Suicide Prevention Department of Veterans Affairs United States Department of Medicine Stanford University School of Medicine StanfordCA United States Veterans Affairs Great Lakes Health Care System WestchesterIL United States Department of Electrical Engineering and Computer Science University of Tennessee Knoxville KnoxvilleTN United States

Background: Injection drug use (IDU) is a dangerous health behavior that increases mortality and morbidity. Identifying IDU early and initiating harm reduction interventions can benefit individuals at risk. However, extracting IDU behaviors from patients’ electronic health records (EHR) is difficult because there is no International Classification of Disease (ICD) code and the only place IDU information can be indicated is unstructured free-text clinical notes. Although natural language processing can efficiently extract this information from unstructured data, there are no validated tools. Methods: To address this gap in clinical information, we design and demonstrate a question-answering (QA) framework to extract information on IDU from clinical notes. Our framework involves two main steps: (1) generating a gold-standard QA dataset and (2) developing and testing the QA model. We utilize 2323 clinical notes of 1145 patients sourced from the VA Corporate Data Warehouse to construct the gold-standard dataset for developing and evaluating the QA model. We also demonstrate the QA model’s ability to extract IDU-related information on temporally out-of-distribution data. Results: Here we show that for a strict match between gold-standard and predicted answers, the QA model achieves 51.65% F1 score. For a relaxed match between the gold-standard and predicted answers, the QA model obtains 78.03% F1 score, along with 85.38% Precision and 79.02% Recall scores. Moreover, the QA model demonstrates consistent performance when subjected to temporally out-of-distribution data. Conclusions: Our study introduces a QA framework designed to extract IDU information from clinical notes, aiming to enhance the accurate and efficient detection of people who inject drugs, extract relevant information, and ultimately facilitate informed patient care. © 2023, CC BY-NC-ND.

关键词： Data warehouses

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Global, regional, and national burden of diabetes from 1990 to 2021, with projections of prevalence to 2050: a systematic analysis for the Global Burden of Disease Study 2021

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The Lancet 2023年第10397期402卷 203-234页

作者： Ong, Kanyin Liane Stafford, Lauryn K. McLaughlin, Susan A. Boyko, Edward J. Vollset, Stein Emil Smith, Amanda E. Dalton, Bronte E. Duprey, Joe Cruz, Jessica A. Hagins, Hailey Lindstedt, Paulina A. Aali, Amirali Abate, Yohannes Habtegiorgis Abate, Melsew Dagne Abbasian, Mohammadreza Abbasi-Kangevari, Zeinab Abbasi-Kangevari, Mohsen ElHafeez, Samar Abd Abd-Rabu, Rami Abdulah, Deldar Morad Abdullah, Abu Yousuf Md Abedi, Vida Abidi, Hassan Aboagye, Richard Gyan Abolhassani, Hassan Abu-Gharbieh, Eman Abu-Zaid, Ahmed Adane, Tigist Demssew Adane, Denberu Eshetie Addo, Isaac Yeboah Adegboye, Oyelola A. Adekanmbi, Victor Adepoju, Abiola Victor Adnani, Qorinah Estiningtyas Sakilah Afolabi, Rotimi Felix Agarwal, Gina Aghdam, Zahra Babaei Agudelo-Botero, Marcela Arriagada, Constanza Elizabeth Aguilera Agyemang-Duah, Williams Ahinkorah, Bright Opoku Ahmad, Danish Ahmad, Rizwan Ahmad, Sajjad Ahmad, Aqeel Ahmadi, Ali Ahmadi, Keivan Ahmed, Ali Ahmed, Luai A. Ahmed, Syed Anees Ajami, Marjan Akinyemi, Rufus Olusola Al Hamad, Hanadi Al Hasan, Syed Mahfuz AL-Ahdal, Tareq Mohammed Ali Alalwan, Tariq A. Al-Aly, Ziyad AlBataineh, Mohammad T. Alcalde-Rabanal, Jacqueline Elizabeth Alemi, Sharifullah Ali, Hassam Alinia, Tahereh Aljunid, Syed Mohamed Almustanyir, Sami Al-Raddadi, Rajaa M. Alvis-Guzman, Nelson Amare, Firehiwot Ameyaw, Edward Kwabena Amiri, Sohrab Amusa, Ganiyu Adeniyi Andrei, Catalina Liliana Anjana, Ranjit Mohan Ansar, Adnan Ansari, Golnoosh Ansari-Moghaddam, Alireza Anyasodor, Anayochukwu Edward Arabloo, Jalal Aravkin, Aleksandr Y. Areda, Demelash Arifin, Hidayat Arkew, Mesay Armocida, Benedetta Arnlov, Johan Artamonov, Anton A. Arulappan, Judie Aruleba, Raphael Taiwo Arumugam, Ashokan Aryan, Zahra Asemu, Mulu Tiruneh Asghari-Jafarabadi, Mohammad Askari, Elaheh Asmelash, Daniel Astell-Burt, Thomas Athar, Mohammad Athari, Seyyed Shamsadin Atout, Maha Moh'd Wahbi Avila-Burgos, Leticia Awaisu, Ahmed Azadnajafabad, Sina Darshan, B.B. Babamohamadi, Hassan Badar, Muhammad Badawi, Alaa Badiye, Ashish D. Baghcheghi, Nayereh Baghe Institute for Health Metrics and Evaluation School of Medicine General Medicine Service Department of Veterans Affairs Seattle WA United States Department of Health Metrics Sciences School of Medicine Faculty of Medicine France Department of Clinical Governance and Quality Improvement Aleta Wondo Hospital Aleta Wondo Ethiopia Department of Nursing Woldia University Woldia Ethiopia Department of Nursing Department of Orthopedic Surgery Orthopaedic Surgery Social Determinants of Health Research Center Non-communicable Diseases Research Center Epidemiology Department Evidence-Based Practice Center Community and Maternity Nursing Unit University of Duhok Duhok Iraq School of Planning Faculty of Environment Department of Public Health Sciences Penn State College of Medicine Pennsylvania State University Hershey PA United States Biocomplexity Institute Virginia Tech Blacksburg VA United States College of Medicine Department of Public Health Laboratory Technology Sciences Department Department of Family and Community Health University of Health and Allied Sciences Ho Ghana Research Center for Immunodeficiencies Department of Biosciences and Nutrition Karolinska University Hospital Huddinge Sweden Clinical Sciences Department Department of Surgery Department of Surgery Department of Obstetrics & Gynecology College of Graduate Health Sciences University of Tennessee Memphis TN United States Department of Obstetrics & Gynecology Department of Clinical and Psychosocial Epidemiology Department of Anesthesia and Critical Care Centre for Social Research in Health Quality and Systems Performance Unit Cancer Institute NSW Sydney NSW Australia Department of Public Health and Tropical Medicine HIV and Infectious Diseases Department Jhpiego Abuja Nigeria Adolescent Research and Care Department Adolescent Friendly Research Initiative and Care Ado Ekiti Nigeria Department of Epidemiology Department of Epidemiology and Medical Statistics Department of Family Medicine McMaster University

Background: Diabetes is one of the leading causes of death and disability worldwide, and affects people regardless of country, age group, or sex. Using the most recent evidentiary and analytical framework from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD), we produced location-specific, age-specific, and sex-specific estimates of diabetes prevalence and burden from 1990 to 2021, the proportion of type 1 and type 2 diabetes in 2021, the proportion of the type 2 diabetes burden attributable to selected risk factors, and projections of diabetes prevalence through 2050. Methods: Estimates of diabetes prevalence and burden were computed in 204 countries and territories, across 25 age groups, for males and females separately and combined;these estimates comprised lost years of healthy life, measured in disability-adjusted life-years (DALYs;defined as the sum of years of life lost [YLLs] and years lived with disability [YLDs]). We used the Cause of Death Ensemble model (CODEm) approach to estimate deaths due to diabetes, incorporating 25 666 location-years of data from vital registration and verbal autopsy reports in separate total (including both type 1 and type 2 diabetes) and type-specific models. Other forms of diabetes, including gestational and monogenic diabetes, were not explicitly modelled. Total and type 1 diabetes prevalence was estimated by use of a Bayesian meta-regression modelling tool, DisMod-MR 2.1, to analyse 1527 location-years of data from the scientific literature, survey microdata, and insurance claims;type 2 diabetes estimates were computed by subtracting type 1 diabetes from total estimates. Mortality and prevalence estimates, along with standard life expectancy and disability weights, were used to calculate YLLs, YLDs, and DALYs. When appropriate, we extrapolated estimates to a hypothetical population with a standardised age structure to allow comparison in populations with different age structures. We used the comparative r

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Regional trends in ophthalmic surgical wait times in Ontario, Canada

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Canadian journal of ophthalmology. Journal canadien d'ophtalmologie 2023年第3期58卷 e104-e106页

作者： Tina Felfeli Michael Balas Gener Austria Reeza Menalo Diana Vasiliu Claudia Zanchetta Department of Ophthalmology and Vision Sciences University of Toronto Toronto ON Institute of Health Policy Management and Evaluation (IHPME) University of Toronto Toronto ON Toronto Health Economics and Technology Assessment (THETA) Collaborative University Health Network Toronto ON. Electronic address: tina.felfeli@mail.utoronto.ca. Temerty Faculty of Medicine University of Toronto Toronto ON. Access to Care Program Health System Performance and Support Portfolio Ontario Health Toronto ON.

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Fatal police violence by race and state in the USA, 1980–2019: a network meta-regression

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The Lancet 2021年第10307期398卷 1239-1255页

作者： Sharara, Fablina Wool, Eve E. Bertolacci, Gregory J. Weaver, Nicole Davis Balassyano, Shelly Watson, Alexandrea Dippenaar, Ilse N. Cunningham, Matthew Fuller, John E. Marczak, Laurie B. Johnson, Catherine Owens Roth, Gregory A. Abedi, Aidin Acuna, Juan Manuel Advani, Shailesh M. Agasthi, Pradyumna Alahdab, Fares Al-Aly, Ziyad Antony, Catherine M. Assari, Shervin Awan, Asma Tahir Basu, Sanjay Bell, Arielle Wilder Braithwaite, Dejana Burkart, Katrin Chew, Adrienne Cho, Daniel Youngwhan Chowdhury, Mohiuddin Ahsanul Kabir Dai, Xiaochen Daoud, Farah Dharmaratne, Samath Dhamminda Dwyer-Lindgren, Laura Elgendy, Islam Y. Fares, Jawad Farwati, Medhat Fisher, James L. Gholamrezanezhad, Ali Gopalani, Sameer Vali Grada, Ayman Guha, Avirup Hafezi-Nejad, Nima Haider, Mohammad Rifat Hay, Simon I. Hossain, Md Mahbub Ikuta, Kevin S. Islam, Jessica Y. Jabbarinejad, Roxana Khatab, Khaled Khubchandani, Jagdish Kim, Daniel Kimokoti, Ruth W. Kisa, Adnan Krishnamoorthy, Vijay Krohn, Kris J. Lawrence, Wayne R. LeGrand, Kate E. Lim, Stephen S. Lin, Ziqiang Liu, Xuefeng Mahmoudi, Morteza Martinez-Piedra, Ramon Mehta, Kala M. Miller, Ted R. Moitra, Modhurima Mokdad, Ali H. Morrison, Shane Douglas Murray, Christopher J.L. Nápoles, Anna María Nsoesie, Elaine Okanyene Odell, Christopher M. Pawar, Shrikant Perez-Stable, Eliseo J. Pilz, Tessa M. Ram, Pradhum Reiner, Robert C. Roberts, Nicholas L.S. Salehi, Sana Sanabria, Juan Schwebel, David C. Sheikh, Aziz Sigfusdottir, Inga Dora Singh, Jasvinder A. Spurlock, Emma Elizabeth Sykes, Bryan L. Tadbiri, Hooman Tleyjeh, Imad I. Tsai, Alexander C. Vos, Theo Wu, Chenkai Yandrapalli, Srikanth Yunusa, Ismaeel Zand, Ramin Zhang, Wangjian Naghavi, Mohsen Institute for Health Metrics and Evaluation University of Washington Seattle WA United States Division of Cardiology University of Washington Seattle WA United States Department of Health Metrics Sciences School of Medicine University of Washington Seattle WA United States Division of Plastic Surgery University of Washington Seattle WA United States Division of Allergy and Infectious Diseases University of Washington Seattle WA United States Department of Anesthesiology & Pain Medicine University of Washington Seattle WA United States Department of Orthopaedic Surgery University of Southern California Los Angeles CA United States Department of Radiology University of Southern California Los Angeles CA United States Department of Epidemiology and Population Health Khalifa University Abu Dhabi United Arab Emirates FIU Robert Stempel College of Public Health & Social Work Florida International University Miami FL United States Terasaki Institute for Biomedical Innovation Los Angeles CA United States School of Medicine Georgetown University Washington DC United States Department of Cardiovascular Medicine Mayo Clinic Scottsdale AZ United States Mayo Evidence-based Practice Center Mayo Clinic Foundation for Medical Education and Research Rochester MN United States John T Milliken Department of Internal Medicine Washington University in St Louis St Louis MO United States Clinical Epidemiology Center Department of Veterans Affairs St Louis MO United States Department of Family Medicine Charles R Drew University of Medicine and Science Los Angeles CA United States School of Nursing and Health Sciences Capella University Minneapolis MN United States Continuing Education Grant Writing Academy University of Nevada Las Vegas NV United States Center for Primary Care Harvard University Boston MA United States Department of Global Health and Social Medicine Harvard University Boston MA United States Division of Cardiology Harvard University Bos

Background: The burden of fatal police violence is an urgent public health crisis in the USA. Mounting evidence shows that deaths at the hands of the police disproportionately impact people of certain races and ethnicities, pointing to systemic racism in policing. Recent high-profile killings by police in the USA have prompted calls for more extensive and public data reporting on police violence. This study examines the presence and extent of under-reporting of police violence in US Government-run vital registration data, offers a method for correcting under-reporting in these datasets, and presents revised estimates of deaths due to police violence in the USA. Methods: We compared data from the USA National Vital Statistics system (NVSS) to three non-governmental, open-source databases on police violence: Fatal Encounters, Mapping Police Violence, and The Counted. We extracted and standardised the age, sex, US state of death registration, year of death, and race and ethnicity (non-Hispanic White, non-Hispanic Black, non-Hispanic of other races, and Hispanic of any race) of each decedent for all data sources and used a network meta-regression to quantify the rate of under-reporting within the NVSS. Using these rates to inform correction factors, we provide adjusted estimates of deaths due to police violence for all states, ages, sexes, and racial and ethnic groups from 1980 to 2019 across the USA. Findings: Across all races and states in the USA, we estimate 30 800 deaths (95% uncertainty interval [UI] 30 300–31 300) from police violence between 1980 and 2018;this represents 17 100 more deaths (16 600–17 600) than reported by the NVSS. Over this time period, the age-standardised mortality rate due to police violence was highest in non-Hispanic Black people (0·69 [95% UI 0·67–0·71] per 100 000), followed by Hispanic people of any race (0·35 [0·34–0·36]), non-Hispanic White people (0·20 [0·19–0·20]), and non-Hispanic people of other races (0·15 [0·14– 0·16]). This var

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Hearing loss prevalence and years lived with disability, 1990-2019: Findings from the Global Burden of Disease Study 2019

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The Lancet 2021年第10278期397卷 996-1009页

作者： Haile, Lydia M. Kamenov, Kaloyan Briant, Paul Svitil Orji, Aislyn U. Steinmetz, Jaimie D. Abdoli, Amir Abdollahi, Mohammad Abu-Gharbieh, Eman Afshin, Ashkan Ahmed, Haroon Rashid, Tarik Ahmed Akalu, Yonas Alahdab, Fares Alanezi, Fahad Mashhour Alanzi, Turki M. Al Hamad, Hanadi Ali, Liaqat Alipour, Vahid Al-Raddadi, Rajaa M. Amu, Hubert Arabloo, Jalal Arab-Zozani, Morteza Arulappan, Judie Ashbaugh, Charlie Atnafu, Desta Debalkie Babar, Zaheer-Ud-Din Baig, Atif Amin Banik, Palash Chandra Bärnighausen, Till Winfried Barrow, Amadou Bender, Rose G. Bhagavathula, Akshaya Srikanth Bhardwaj, Nikha Bhardwaj, Pankaj Bibi, Sadia Bijani, Ali Burkart, Katrin Cederroth, Christopher R. Charan, Jaykaran Choudhari, Sonali Gajanan Chu, Dinh-Toi Couto, Rosa A.S. Dagnew, Amare Belachew Dagnew, Baye Dahlawi, Saad M.A. Dai, Xiaochen Dandona, Lalit Dandona, Rakhi Desalew, Assefa Dhamnetiya, Deepak Dhimal, Mandira Lamichhane Dhimal, Meghnath Doyle, Kerrie E. Duncan, Bruce B. Ekholuenetale, Michael Filip, Irina Fischer, Florian Franklin, Richard Charles Gaidhane, Abhay Motiramji Gaidhane, Shilpa Gallus, Silvano Ghamari, Farhad Ghashghaee, Ahmad Ghozali, Ghozali Gilani, Syed Amir Glǎvan, Ionela-Roxana Golechha, Mahaveer Goulart, Barbara Niegia Garcia Gupta, Veer Bala Gupta, Vivek Kumar Hamidi, Samer Hammond, Billy Randall Hay, Simon I. Hayat, Khezar Heidari, Golnaz Hoffman, Howard J. Hopf, Kathleen Pillsbury Hosseinzadeh, Mehdi Househ, Mowafa Hussain, Rabia Hwang, Bing-Fang Iavicoli, Ivo Ibitoye, Segun Emmanuel Ilesanmi, Olayinka Stephen Irvani, Seyed Sina Naghibi Islam, Sheikh Mohammed Shariful Iwagami, Masao Jacob, Louis Jayapal, Sathish Kumar Jha, Ravi Prakash Jonas, Jost B. Kalhor, Rohollah Al-Salihi, Nawzad Kameran Kandel, Himal Kasa, Ayele Semachew Kayode, Gbenga A. Khalilov, Rovshan Khan, Ejaz Ahmad Khatib, Mahalaqua Nazli Kosen, Soewarta Koyanagi, Ai Kumar, G. Anil Landires, Ivan Lasrado, Savita Lim, Stephen S. Liu, Xuefeng Lobo, Stany W. Lugo, Alessandra Makki, Alaa Mendoza, Walter Mersha, Amanual Getnet Mihretie, Kebadnew Mulatu Institute for Health Metrics and Evaluation University of Washington Seattle WA United States Department of Noncommunicable Diseases World Health Organization (WHO) Geneva Switzerland Department of Parasitology and Mycology Jahrom University of Medical Sciences Jahrom Iran The Institute of Pharmaceutical Sciences (TIPS) Tehran University of Medical Sciences Tehran Iran School of Pharmacy Tehran University of Medical Sciences Tehran Iran Clinical Sciences Department University of Sharjah Sharjah United Arab Emirates Department of Health Metrics Sciences School of Medicine University of Washington Seattle WA United States Department of Biosciences COMSATS Institute of Information Technology Islamabad Pakistan Department of Computer Science and Engineering University of Kurdistan Hewler Erbil Iraq Department of Medical Physiology University of Gondar Gondar Ethiopia Mayo Evidence-based Practice Center Mayo Clinic Foundation for Medical Education and Research Rochester MN United States Imam Abdulrahman Bin Faisal University Dammam Saudi Arabia Health Information Management and Technology Department Dammam Saudi Arabia Geriatric and Long Term Care Department Hamad Medical Corporation Doha Qatar Rumailah Hospital Hamad Medical Corporation Doha Qatar Department of Biological Sciences National University of Medical Sciences (NUMS) Rawalpindi Pakistan Health Management and Economics Research Center Tehran Iran Department of Community Medicine King Abdulaziz University Jeddah Saudi Arabia Department of Population and Behavioural Sciences University of Health and Allied Sciences Ho Ghana Social Determinants of Health Research Center Birjand University of Medical Sciences Birjand Iran Department of Maternal and Child Health Sultan Qaboos University Muscat Oman Department of Health System and Health Economics Bahir Dar University Bahir Dar Ethiopia Department of Pharmacy University of Huddersfield Huddersfield United Kingdom Unit of Biochemistry Universiti

Background: Hearing loss affects access to spoken language, which can affect cognition and development, and can negatively affect social wellbeing. We present updated estimates from the Global Burden of Disease (GBD) study on the prevalence of hearing loss in 2019, as well as the condition's associated disability. Methods: We did systematic reviews of population-representative surveys on hearing loss prevalence from 1990 to 2019. We fitted nested meta-regression models for severity-specific prevalence, accounting for hearing aid coverage, cause, and the presence of tinnitus. We also forecasted the prevalence of hearing loss until 2050. Findings: An estimated 1·57 billion (95% uncertainty interval 1·51–1·64) people globally had hearing loss in 2019, accounting for one in five people (20·3% [19·5–21·1]). Of these, 403·3 million (357·3–449·5) people had hearing loss that was moderate or higher in severity after adjusting for hearing aid use, and 430·4 million (381·7–479·6) without adjustment. The largest number of people with moderate-to-complete hearing loss resided in the Western Pacific region (127·1 million people [112·3–142·6]). Of all people with a hearing impairment, 62·1% (60·2–63·9) were older than 50 years. The healthcare Access and Quality (HAQ) Index explained 65·8% of the variation in national age-standardised rates of years lived with disability, because countries with a low HAQ Index had higher rates of years lived with disability. By 2050, a projected 2·45 billion (2·35–2·56) people will have hearing loss, a 56·1% (47·3–65·2) increase from 2019, despite stable age-standardised prevalence. Interpretation: As populations age, the number of people with hearing loss will increase. Interventions such as childhood screening, hearing aids, effective management of otitis media and meningitis, and cochlear implants have the potential to ameliorate this burden. Because the burden of moderate-to-complete hearing loss is concentrated in countries with low health-ca

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Publisher Correction: Global estimates on the number of people blind or visually impaired by cataract: a meta-analysis from 2000 to 2020

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Eye (London, England) 2024年第11期38卷 2229-2231页

作者： Konrad Pesudovs Hugh R. Taylor Tabassom Sedighi Rupert R. A. Bourne Shahina Pardhan Van Charles Lansingh John H. Kempen Ian Tapply Arthur G. Fernandes Maria Vittoria Cicinelli Alessandro Arrigo Nicolas Leveziel Serge Resnikoff Seth Flaxman Mukkharram M. Bikbov Tasanee Braithwaite Alain Bron Ching-Yu Cheng Monte A. Del Monte Joshua R. Ehrlich Leon B. Ellwein David Friedman João M. Furtado Gus Gazzard Ronnie George M. Elizabeth Hartnett Jost B. Jonas Rim Kahloun Moncef Khairallah Rohit C. Khanna Janet Leasher Julie-Anne Little Vinay Nangia Michal Nowak Tunde Peto Pradeep Ramulu Fotis Topouzis Mitiadis Tsilimbaris Ya Xing Wang Ningli Wang Paul Svitil Briant Theo Vos Katrin Burkart Kaleb Coberly Xiaochen Dai Stephen S. Lim Tomislav Mestrovic Ali H. Mokdad Christopher J. L. Murray Jaimie D. Steinmetz Awoke Misganaw Yohannes Habtegiorgis Abate Mohammad Abdollahi Mozhan Abdollahi Ayele Mamo Abebe Olumide Abiodun Richard Gyan Aboagye Woldu Aberhe Abrha Hasan Abualruz Hiwa Abubaker Ali Eman Abu-Gharbieh Salahdein Aburuz Tadele Girum Girum Adal Mesafint Molla Adane Isaac Yeboah Addo Qorinah Estiningtyas Sakilah Adnani Muhammad Sohail Afzal Muhammad Umair Shahin Aghamiri Bright Opoku Ahinkorah Aqeel Ahmad Sajjad Ahmad Ali Ahmadi Siamak Sabour Ayman Ahmed Haroon Ahmed Ahmad Samir Alfaar Abid Ali Syed Shujait Shujait Ali Awais Altaf Hubert Amu Emmanuel Manu Sofia Androudi Rodrigo Anguita Abhishek Anil Rimple Jeet Kaur Muhammad Aaqib Shamim Saeid Anvari Anayochukwu Edward Anyasodor Francis Appiah Jalal Arabloo Haleh Ayatollahi Mosab Arafat Damelash Areda Reza Arefnezhad Brhane Berhe Aregawi Akeza Awealom Asgedom Tahira Ashraf Seyyed Shamsadin Athari Bantalem Tilaye Tilaye Atinafu Birhan Tsegaw Taye Maha Moh’d Wahbi Atout Alok Atreya Ahmed Y. Azzam Hassan Babamohamadi Sara Bagherieh Yogesh Bahurupi Atif Amin Baig Shumaila Nargus Biswajit Banik Mainak Bardhan Saurav Basu Kavita Batra Nebiyou Simegnew Bayileyegn Fatemeh Bazvand Addisu Shunu Beyene Awoke Masrie Asrat Derese Devidas S. Bhagat Akshaya Srikanth Bhagavathula Pankaj Bh Medicine & Health University of New South Wales Sydney NSW Australia School of Optometry and Vision Science University of New South Wales Sydney NSW Australia School of Population and Global Health University of Melbourne Carlton VIC Australia Vision and Eye Research Institute Anglia Ruskin University Cambridge UK HelpMeSee Instituto Mexicano de Oftalmologia Santiago de Querétaro Mexico University of Miami Gables FL USA University of Utah Salt Lake City UT USA Chief Medical Office HelpMeSee New York NY USA Mexican Institute of Ophthalmology Queretaro Mexico Department of Ophthalmology Massachusetts Eye and Ear/Shepens Eye Research Institute/Harvard Medical School Boston MA USA Eye Unit MyungSung Christian Medical Center (MCM) Comprehensive Specialized Hospital and MyungSun Medical College Addis Ababa Ethiopia Department of Ophthalmology Addis Ababa University Addis Ababa Ethiopia Sight for Souls Bellevue WA USA Department of Ophthalmology Harvard University Boston MA USA Eye Unit MyungSung Medical College Addis Ababa Ethiopia Addenbrooke’s Hospital Cambridge UK Department of Ophthalmology Cambridge University Hospitals Cambridge UK Federal University of Sao Paolo Sao Paolo SP Brazil University of Calgary Calgary AB Canada Department of Ophthalmology and Visual Sciences Federal University of São Paulo Sao Paulo Brazil School of Medicine Vita-Salute San Raffaele University Milan Italy Department of Ophthalmology IRCCS San Raffaele Scientific Institute Milan Italy Department of Ophthalmology San Raffaele Scientific Institute Milano Italy IRCCS San Raffaele Scientific Institute Vita-Salute University Milan Italy Scientific Institute San Raffaele Hospital Vita-Salute University Milan Italy University of Poitiers Poitiers France CHU de Poitiers Poitiers France Ophthalmology Department CHU de Poitiers (Poitiers University Hospital) Poitiers France Unité 1084 National Institute of Health and Medical Research (INSERM) Poitiers France

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Global investments in pandemic preparedness and COVID-19: development assistance and domestic spending on health between 1990 and 2026

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The Lancet Global health 2023年第3期11卷 e385-e413页

作者： Micah, Angela E. Bhangdia, Kayleigh Cogswell, Ian E. Lasher, Dylan Lidral-Porter, Brendan Maddison, Emilie R. Nguyen, Trang Nhu Ngoc Patel, Nishali Pedroza, Paola Solorio, Juan Stutzman, Hayley Tsakalos, Golsum Wang, Yifeng Warriner, Wesley Zhao, Yingxi Zlavog, Bianca S. Abbafati, Cristiana Abbas, Jaffar Abbasi-Kangevari, Mohsen Abbasi-Kangevari, Zeinab Abdelmasseh, Michael Abdulah, Deldar Morad Abedi, Aidin Abegaz, Kedir Hussein Abhilash, E.S. Aboagye, Richard Gyan Abolhassani, Hassan Abrigo, Michael R.M. Abubaker Ali, Hiwa Abu-Gharbieh, Eman Adem, Mohammed Hussien Afzal, Muhammad Sohail Ahmadi, Ali Ahmed, Haroon Ahmed Rashid, Tarik Aji, Budi Akbarialiabad, Hossein Akelew, Yibeltal Al Hamad, Hanadi Alam, Khurshid Alanezi, Fahad Mashhour Alanzi, Turki M. Al-Hanawi, Mohammed Khaled Alhassan, Robert Kaba Aljunid, Syed Mohamed Almustanyir, Sami Al-Raddadi, Rajaa M. Alvis-Guzman, Nelson Alvis-Zakzuk, Nelson J. Amare, Azmeraw T. Ameyaw, Edward Kwabena Amini-Rarani, Mostafa Amu, Hubert Ancuceanu, Robert Andrei, Tudorel Anwar, Sumadi Lukman Appiah, Francis Aqeel, Muhammad Arabloo, Jalal Arab-Zozani, Morteza Aravkin, Aleksandr Y. Aremu, Olatunde Aruleba, Raphael Taiwo Athari, Seyyed Shamsadin Avila-Burgos, Leticia Ayanore, Martin Amogre Azari, Samad Baig, Atif Amin Bantie, Abere Tilahun Barrow, Amadou Baskaran, Pritish Basu, Sanjay Batiha, Abdul-Monim Mohammad Baune, Bernhard T. Berezvai, Zombor Bhardwaj, Nikha Bhardwaj, Pankaj Bhaskar, Sonu Boachie, Micheal Kofi Bodolica, Virginia Botelho, João Silva Botelho Braithwaite, Dejana Breitborde, Nicholas J.K. Busse, Reinhard Cahuana-Hurtado, Lucero Catalá-López, Ferrán Chansa, Collins Charan, Jaykaran Chattu, Vijay Kumar Chen, Simiao Chukwu, Isaac Sunday Dadras, Omid Dandona, Lalit Dandona, Rakhi Dargahi, Abdollah Debela, Sisay Abebe Denova-Gutiérrez, Edgar Desye, Belay Dharmaratne, Samath Dhamminda Diao, Nancy Doan, Linh Phuong Dodangeh, Milad dos Santos, Wendel Mombaque Doshmangir, Leila Dube, John Eini, Ebrahim El Sayed Zaki, Maysaa El Tantawi, Maha Enyew, Daniel Berhanie Institute for Health Metrics and Evaluation University of Washington Seattle WA United States Department of Applied Mathematics University of Washington Seattle WA United States Department of Health Metrics Sciences School of Medicine University of Washington Seattle WA United States Nuffield Department of Medicine University of Oxford Oxford United Kingdom Department of Juridical and Economic Studies La Sapienza University Rome Italy Antai College of Economics Shanghai Jiao Tong University Shanghai China Non-communicable Diseases Research Center Tehran University of Medical Sciences Tehran Iran Research Center for Immunodeficiencies Tehran University of Medical Sciences Tehran Iran Multiple Sclerosis Research Center Tehran University of Medical Sciences Tehran Iran Children’s Medical Center Tehran University of Medical Sciences Tehran Iran Department of Epidemiology and Biostatistics Tehran University of Medical Sciences Tehran Iran Tehran Heart Center Tehran University of Medical Sciences Tehran Iran Faculty of Medicine Tehran University of Medical Sciences Tehran Iran National Institute for Health Research Tehran University of Medical Sciences Tehran Iran Department of Pharmacology Tehran University of Medical Sciences Tehran Iran Department of Cardiology Tehran University of Medical Sciences Tehran Iran Sina Trauma and Surgery Research Center Tehran University of Medical Sciences Tehran Iran Digestive Diseases Research Institute Tehran University of Medical Sciences Tehran Iran Department of Neurology Tehran University of Medical Sciences Tehran Iran Social Determinants of Health Research Center Shahid Beheshti University of Medical Sciences Tehran Iran Department of Epidemiology Shahid Beheshti University of Medical Sciences Tehran Iran Department of Health Economics and Statistics Shahid Beheshti University of Medical Sciences Tehran Iran Department of Neurosurgery Shahid Beheshti University of Medical Sciences Tehran Iran Ophthalmic R

Background: The COVID-19 pandemic highlighted gaps in health surveillance systems, disease prevention, and treatment globally. Among the many factors that might have led to these gaps is the issue of the financing of national health systems, especially in low-income and middle-income countries (LMICs), as well as a robust global system for pandemic preparedness. We aimed to provide a comparative assessment of global health spending at the onset of the pandemic;characterise the amount of development assistance for pandemic preparedness and response disbursed in the first 2 years of the COVID-19 pandemic;and examine expectations for future health spending and put into context the expected need for investment in pandemic preparedness. Methods: In this analysis of global health spending between 1990 and 2021, and prediction from 2021 to 2026, we estimated four sources of health spending: development assistance for health (DAH), government spending, out-of-pocket spending, and prepaid private spending across 204 countries and territories. We used the Organisation for Economic Co-operation and Development (OECD)'s Creditor Reporting system (CRS) and the WHO Global health Expenditure Database (GHED) to estimate spending. We estimated development assistance for general health, COVID-19 response, and pandemic preparedness and response using a keyword search. health spending estimates were combined with estimates of resources needed for pandemic prevention and preparedness to analyse future health spending patterns, relative to need. Findings: In 2019, at the onset of the COVID-19 pandemic, US$9·2 trillion (95% uncertainty interval [UI] 9·1–9·3) was spent on health worldwide. We found great disparities in the amount of resources devoted to health, with high-income countries spending $7·3 trillion (95% UI 7·2–7·4) in 2019;293·7 times the $24·8 billion (95% UI 24·3–25·3) spent by low-income countries in 2019. That same year, $43·1 billion in development assistance was provided

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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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