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Enregistrement W3005957464 · doi:10.1016/s0140-6736(20)30045-3

Global, regional, and national burden of chronic kidney disease, 1990–2017: a systematic analysis for the Global Burden of Disease Study 2017

2020· article· en· W3005957464 sur OpenAlexfundno aff
Boris Bikbov, Caroline Purcell, Andrew S. Levey, Mari Smith, Amir Abdoli, Molla Abebe, Oladimeji Adebayo, Mohsen Afarideh, Sanjay Kumar Agarwal, Marcela Agudelo‐Botero, Elham Ahmadian, Ziyad Al‐Aly, Vahid Alipour, Amir Almasi‐Hashiani, Rajaa Al‐Raddadi, Nelson Alvis‐Guzmán, Tudorel Andrei, Cătălina Liliana Andrei, Zewudu Andualem, Mina Anjomshoa, Jalal Arabloo, Alebachew Fasil Ashagre, Daniel Asmelash, Zerihun Ataro, Maha Atout, Martin Amogre Ayanore, Alaa Badawi, Ahad Bakhtiari, Shoshana H. Ballew, Abbas Balouchi, Maciej Banach, Sı́món Barquera, Sanjay Basu, Mulat Tirfie Bayih, Neeraj Bedi, Aminu K. Bello, Isabela M. Benseñor, Ali Bijani, Archith Boloor, Antonio Maria Borzì, Luis Alberto Cámera, Juan Jesús Carrero, Félix Carvalho, Franz Castro, Ferrán Catalá-López, Alex R. Chang, Ken Lee Chin, Sheng‐Chia Chung, Massimo Círillo, Ewerton Cousin, Lalit Dandona, Rakhi Dandona, Ahmad Daryani, Rajat Das Gupta, Feleke Mekonnen Demeke, Gebre Teklemariam Demoz, Desilu Mahari Desta, Huyen Phuc, Bruce Bartholow Duncan, Aziz Eftekhari, Alireza Esteghamati, Syeda Sadia Fatima, João Carlos Fernandes, Eduarda Fernandes, Florian Fischer, Marisa Freitas, Mohamed M. Gad, Gebreamlak Gebremedhn Gebremeskel, Begashaw Melaku Gebresillassie, Birhanu Geta, Mansour Ghafourifard, Alireza Ghajar, Nermin Ghith, Paramjit Gill, Ibrahim Ginawi, Nima Hafezi‐Nejad, Arvin Haj‐Mirzaian, Arya Haj‐Mirzaian, Ninuk Hariyani, Mehedi Hasan, Milad Hasankhani, Amir Hasanzadeh, Hamid Yimam Hassen, Simon I Hay, Behnam Heidari, Claudiu Herţeliu, Chi Linh Hoang, Mostafa Hosseini, Mihaela Hostiuc, Seyed Sina Naghibi Irvani, Sheikh Mohammed Shariful Islam, Nader Jafari Balalami, Spencer L James, Simerjot K Jassal, Vivekanand Jha, Jost B Jonas, Farahnaz Joukar, Jacek Jerzy Jozwiak, Ali Kabir, Amaha Kahsay, Amir Kasaeian, Tesfaye Kassa, Hagazi Gebremedhin Kassaye, Yousef Khader, Rovshan Khalilov, Ejaz Ahmad Khan, Mohammad Saud Khan, Young‐Ho Khang, Adnan Kısa, Csaba P. Kövesdy, Barthélémy Kuate Defo, G Anil Kumar, Anders Larsson, Lee‐Ling Lim, Alan D Lopez, Paulo A. Lotufo, Azeem Majeed, Reza Malekzadeh, Winfried März, Anthony Masaka, Hailemariam Abiy Alemu Meheretu, Tomasz Miazgowski, Andreea Mirică, Erkin М Мirrakhimov, Prasanna Mithra, Babak Moazen, Dara K. Mohammad, Reza Mohammadpourhodki, Shafiu Mohammed, Ali H. Mokdad, Linda Morales, Ilais Moreno Velásquez, Seyyed Meysam Mousavi, Satinath Mukhopadhyay, Jean B. Nachega, Girish N. Nadkarni, Jobert Richie Nansseu, Javad Nazari, Bruce Neal, Ruxandra Irina Negoi, Cuong Tat Nguyen, Rajan Nikbakhsh, Jean Jacques Noubiap, Christoph Nowak, Andrew T Olagunju, Alberto Ortíz, Mayowa Owolabi, Raffaele Palladino, Mona Pathak, Hossein Poustchi, Swayam Prakash, Narayan Prasad, Alireza Rafiei, Sree Bhushan Raju, Kiana Ramezanzadeh, Salman Rawaf, David Laith Rawaf, Lal Rawal, Robert C. Reiner, Aziz Rezapour, Daniel Cury Ribeiro, Leonardo Roever, Dietrich Rothenbacher, Godfrey Mutashambara Rwegerera, Seyedmohammad Saadatagah, Saeed Safari, Berhe W. Sahle, Hosni A Salem, Juan Sanabria, Itamar S Santos, Arash Sarveazad, Monika Sawhney, Elke Schäeffner, María Inês Schmidt, Aletta E. Schutte, Sadaf G Sepanlou, Masood Ali Shaikh, Zeinab Sharafi, Mehdi Sharif, Amrollah Sharifi, Diego Augusto Santos Silva, Jasvinder A. Singh, Narinder Pal Singh, Malede Mequanent Sisay, Amin Soheili, Ipsita Sutradhar, Berhane Fseha Teklehaimanot, Berhe Etsay Tesfay, Getnet Teshome, Jarnail Singh Thakur, Marcello Tonelli, Khanh Bao Tran, Bach Xuan Tran, Candide Tran Ngoc, Irfan Ullah, Pascual Valdéz, Santosh Varughese, Theo Vos, Linh Gia Vu, Yasir Waheed, Andrea Werdecker, Haileab Fekadu Wolde, Adam Wondmieneh, Sarah Wulf Hanson, Tomohide Yamada, Yigizie Yeshaw, Naohiro Yonemoto, Hasan Yusefzadeh, Zoubida Zaidi, Leila Zaki, Sojib Bin Zaman, Afshin Zarghi, Kaleab Alemayehu Zewdie, Johan Ärnlöv, Josef Coresh, Norberto Perico, Giuseppe Remuzzi, Chris Murray, Theo Vos

Notice bibliographique

RevueThe Lancet · 2020
Typearticle
Langueen
DomaineMedicine
ThématiqueChronic Kidney Disease and Diabetes
Établissements canadiensnon disponible
Organismes subventionnairesNational Institute of Diabetes and Digestive and Kidney DiseasesMedicinska Fakulteten, Lunds UniversitetSanofi PasteurNovartis PharmaJohns Hopkins Bloomberg School of Public HealthMedical Research CouncilTufts University School of MedicineArnold School of Public Health, University of South CarolinaUniwersytet OpolskiGeorge Institute for Global HealthAbbott DiagnosticsUniversitair Ziekenhuis AntwerpenLaboratório Associado para a Química VerdeKfH-Stiftung PräventivmedizinJahrom University of Medical SciencesFrankfurt University of Applied SciencesLorestan University of Medical SciencesServierSiemens HealthineersMekelle UniversityPomorski Uniwersytet Medyczny W SzczecinieUniversitas AirlanggaAddis Ababa UniversityResearch Institute for Endocrine Sciences, Shahid Beheshti University of Medical SciencesUniversity of GondarUniversity of Health and Allied SciencesUniversitatea de Medicină şi Farmacie "Carol Davila" BucureştiUniversität UlmUrmia UniversityInstituto de Salud Carlos IIIArak University of Medical SciencesUniversity of Cape TownSemnan UniversityUniversità degli Studi di SalernoUppsala UniversitetBabol Noshirvani University of TechnologyMedizinische Universität GrazBahir Dar UniversityShahid Beheshti University of Medical SciencesUniversidad Nacional Autónoma de MéxicoUniversidade de São PauloGuilan University of Medical SciencesWestern Sydney UniversityDanmarks Tekniske UniversitetImperial College LondonShiraz UniversityAkademiska SjukhusetKarl-Franzens-Universität GrazUniversidade Federal do Rio Grande do SulBayer VitalFresenius Medical Care North AmericaHaramaya UniversityGolestan University of Medical SciencesNational Research FoundationUniversità di CataniaUniversiti MalayaNovo NordiskVetenskapsrådetShiraz University of Medical SciencesShahroud University of Medical SciencesUniwersytet ŁódzkiKing Abdulaziz UniversityLunds UniversitetAmarin CorporationIslamic Azad UniversityUniversity of HailUniversidade do PortoUniversity of South CarolinaSeoul National UniversityCairo UniversityUniversity of WashingtonHögskolan DalarnaInternational Centre for Diarrhoeal Disease Research, BangladeshWashington University in St. LouisMonash UniversityAdigrat UniversityNorth-West UniversityPublic Health AgencyDebre Markos UniversityUniversität BielefeldPublic Health EnglandPublic Health Foundation of IndiaSouth African Medical Research CouncilComunidad de MadridIstituto di Ricerche Farmacologiche Mario Negri - IRCCSNational Heart Foundation of AustraliaMassachusetts General HospitalUniversity College LondonUniversity of TabrizAhmadu Bello UniversityEuropean CommissionBaki Dövlət UniversitetiSydney Medical SchoolAstraZenecaDeakin UniversityAlnylam PharmaceuticalsUniversidade Federal de Santa CatarinaBaqiyatallah University of Medical SciencesSanjay Gandhi Postgraduate Institute of Medical SciencesUniversity of TorontoUniversità degli Studi di Napoli Federico IIMinistry of Health and Medical EducationMazandaran University of Medical SciencesUniversity of AlbertaKarolinska InstitutetSalahaddin University-ErbilMaragheh University of Medical SciencesFogarty International CenterTrường Đại học Nguyễn Tất ThànhTarbiat Modares UniversityBrown UniversityNational Center of Neurology and PsychiatryOmron HealthcareTehran University of Medical Sciences and Health ServicesFundação para a Ciência e a TecnologiaRede de Química e TecnologiaAksum UniversityCase Western Reserve UniversityInstitute for Health Metrics and EvaluationMinistério da Ciência, Tecnologia e Ensino SuperiorTrường Đại học Duy TânApplied Molecular Biosciences UnitIran University of Medical SciencesAmgenPublic Health Agency of CanadaMahatma Gandhi UniversityRafsanjan University of Medical SciencesU.S. Department of Veterans AffairsJazan UniversityUniversity of OtagoUniversity of New South WalesUniversity of PittsburghNational Institutes of HealthChinese University of Hong KongBabol University of Medical SciencesCleveland ClinicJohns Hopkins UniversityBill and Melinda Gates FoundationHandokPfizerSanofiUniversity of WarwickTabriz University of Medical SciencesAlexion PharmaceuticalsJordan University of Science and TechnologyUniversity of OxfordMcMaster UniversityOttawa Hospital Research InstituteTufts Medical Center
Mots-clésKidney diseaseMedicineEpidemiologyRenal functionDiseaseDisease burdenMortality rateGoutIncidence (geometry)Intensive care medicineEnvironmental healthInternal medicine

Résumé

récupéré en direct d'OpenAlex

BACKGROUND: Health system planning requires careful assessment of chronic kidney disease (CKD) epidemiology, but data for morbidity and mortality of this disease are scarce or non-existent in many countries. We estimated the global, regional, and national burden of CKD, as well as the burden of cardiovascular disease and gout attributable to impaired kidney function, for the Global Burden of Diseases, Injuries, and Risk Factors Study 2017. We use the term CKD to refer to the morbidity and mortality that can be directly attributed to all stages of CKD, and we use the term impaired kidney function to refer to the additional risk of CKD from cardiovascular disease and gout. METHODS: The main data sources we used were published literature, vital registration systems, end-stage kidney disease registries, and household surveys. Estimates of CKD burden were produced using a Cause of Death Ensemble model and a Bayesian meta-regression analytical tool, and included incidence, prevalence, years lived with disability, mortality, years of life lost, and disability-adjusted life-years (DALYs). A comparative risk assessment approach was used to estimate the proportion of cardiovascular diseases and gout burden attributable to impaired kidney function. FINDINGS: Globally, in 2017, 1·2 million (95% uncertainty interval [UI] 1·2 to 1·3) people died from CKD. The global all-age mortality rate from CKD increased 41·5% (95% UI 35·2 to 46·5) between 1990 and 2017, although there was no significant change in the age-standardised mortality rate (2·8%, -1·5 to 6·3). In 2017, 697·5 million (95% UI 649·2 to 752·0) cases of all-stage CKD were recorded, for a global prevalence of 9·1% (8·5 to 9·8). The global all-age prevalence of CKD increased 29·3% (95% UI 26·4 to 32·6) since 1990, whereas the age-standardised prevalence remained stable (1·2%, -1·1 to 3·5). CKD resulted in 35·8 million (95% UI 33·7 to 38·0) DALYs in 2017, with diabetic nephropathy accounting for almost a third of DALYs. Most of the burden of CKD was concentrated in the three lowest quintiles of Socio-demographic Index (SDI). In several regions, particularly Oceania, sub-Saharan Africa, and Latin America, the burden of CKD was much higher than expected for the level of development, whereas the disease burden in western, eastern, and central sub-Saharan Africa, east Asia, south Asia, central and eastern Europe, Australasia, and western Europe was lower than expected. 1·4 million (95% UI 1·2 to 1·6) cardiovascular disease-related deaths and 25·3 million (22·2 to 28·9) cardiovascular disease DALYs were attributable to impaired kidney function. INTERPRETATION: Kidney disease has a major effect on global health, both as a direct cause of global morbidity and mortality and as an important risk factor for cardiovascular disease. CKD is largely preventable and treatable and deserves greater attention in global health policy decision making, particularly in locations with low and middle SDI. FUNDING: Bill & Melinda Gates Foundation.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction machine sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.

score de la tête « metaresearch » (Codex)0,017
score de la tête « metaresearch » (Gemma)0,032
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Revue systématique · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: aucune
Score de désaccord entre enseignants0,045
Score d'incertitude au seuil0,091

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0170,032
Méta-épidémiologie (sens strict)0,0010,001
Méta-épidémiologie (sens large)0,0050,017
Bibliométrie0,0100,017
Études des sciences et des technologies0,0000,001
Communication savante0,0010,001
Science ouverte0,0010,002
Intégrité de la recherche0,0010,001
Charge utile insuffisante (le modèle a refusé de juger)0,0020,000

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,050
Tête enseignante GPT0,327
Écart entre enseignants0,277 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeRevue systématique
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations6 588
Publié2020
Routes d'admission1
Résumé présentoui

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