Notice bibliographique
Résumé
Chronic kidney disease (CKD) is an increasingly important global public health issue that affects more than 10% of the worldwide population [1] The incidence and prevalence of CKD has increased exponentially worldwide in recent decades and it is now estimated that 850 million people are living with CKD around the globe. The World Health Organization ranked CKD as the 10th leading cause of death in 2020, and it is forecast to become the 5th leading cause of death by 2040 [2]. Kidney replacement therapy (KRT) is a life-sustaining treatment for patients with kidney failure, of which there are estimated to be between 5 and 7 million worldwide [3]. While the CKD epidemic is a global issue, the burden of this disease falls disproportionately on low-income countries (LICs) and lower-middle-income countries (LMICs). It is expected that by 2030, >70% of people with kidney failure will live in LICs, where <10% of patients with kidney failure are able to access KRT [4]. Therefore, it is important to have reliable data on the current status of kidney care services across countries, which can be used to guide policies and strategies to improve care in LICs and LMICs. The International Society of Nephrology Global Kidney Health Atlas (ISN-GKHA) is a multinational survey that collects information on the current capacity for kidney care across all world regions. The previous iterations of the survey reported in 2017 [5] and 2019 [6] identified low recognition of CKD as a health priority as well as important gaps in the availability, accessibility and affordability of KRT between countries. This supplement of Nephrology Dialysis Transplantation (NDT) presents results from the third iteration of the ISN-GKHA [7], which has expanded to include additional countries. In this supplement… Yeung et al. [8] evaluate funding models for provision of KRT, services for management of CKD and reimbursement of medications. Oversight structures and delivery of kidney care are also considered. Htay et al. [9] and Cho et al. [10] assess the availability, accessibility, affordability and quality of hemodialysis and peritoneal dialysis, respectively, across ISN regions and World Bank income groups. Viecelli et al. [11] present an update on the global incidence and prevalence of kidney transplantation, as well as the availability, accessibility, affordability and quality of kidney transplantation. Hole et al. [12] provide a more detailed examination of non-dialytic management of kidney failure (conservative kidney management) than in previous iterations of the ISN-GKHA, considering the global availability, infrastructure, guidelines, medications and training. Okpechi et al. [13] discuss the global kidney care workforce, including the availability of nephrologists and nephrology trainees, and shortages in the workforce required for optimal delivery of kidney care. Finally, Irish et al. [14] assess the global capacity for data monitoring and surveillance which are essential for governance, regulation, planning and policy development for chronic disease care. We hope that the readers of NDT appreciate this article collection summarizing key findings from the most recent iteration of the ISN-GKHA, which highlights the persisting disparities in kidney care services across countries. The Clinical Trial Service Unit and Epidemiological Studies Unit (Oxford, UK) has a staff policy of not accepting honoraria or other payments from the pharmaceutical industry, except for the reimbursement of costs to participate in scientific meetings (see https://www.ctsu.ox.ac.uk/about/ctsu_honoraria_25june14-1.pdf). N.S. reports grant funding paid to their institution (the University of Oxford) from Boehringer Ingelheim, Eli Lilly and Novo Nordick, and funding from the United Kingdom Medical Research Council (MRC) (to the Clinical Trial Service Unit and Epidemiological Studies Unit; reference no. MC_UU_00017/3), the British Heart Foundation, National Institute for Health and Care Research Biomedical Research Council, and Health Data Research (UK). This supplement was supported by the International Society of Nephrology (Grant RES0033080 to the University of Alberta). The International Society of Nephrology provided administrative support for the design and implementation of the survey and data collection activities and the Alberta Kidney Disease Network staff aided with data analysis.
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 enseignantsNi 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.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,020 | 0,063 |
| Méta-épidémiologie (sens strict) | 0,006 | 0,002 |
| Méta-épidémiologie (sens large) | 0,007 | 0,005 |
| Bibliométrie | 0,007 | 0,004 |
| Études des sciences et des technologies | 0,007 | 0,006 |
| Communication savante | 0,018 | 0,012 |
| Science ouverte | 0,005 | 0,006 |
| Intégrité de la recherche | 0,043 | 0,048 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,031 | 0,017 |
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.
score_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 découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».