International Network of Chronic Kidney Disease cohort studies (iNET-CKD): a global network of chronic kidney disease cohorts

Dienemann, Thomas; Fujii, Naohiko; Orlandi, Paula; Nessel, Lisa; Furth, Susan L.; Hoy, Wendy E.; Matsuo, Seiichi; Mayer, Gert; Methven, Shona; Schaefer, Franz; Schaeffner, Elke; Solá, Laura; Stengel, Bénédicte; Wanner, Christoph; Zhang, Luxia; Levin, Adeera; Eckardt, Kai Uwe; Feldman, Harold I.

doi:10.1186/s12882-016-0335-2

Cited by 51 publications

(48 citation statements)

References 33 publications

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“…In addition to these databases in the United States, other countries worldwide also have big data within nephrology for researchers, such as the National Kidney Disease Surveillance Program in Ireland [53], the surveillance project on CKD management in Canada [54], and the China Kidney Disease Network (CK-NET), a comprehensive CKD surveillance system for China [55]. Numerous networks of international collaboration, like the International Network of CKD cohorts [56], the Therapeutic Evaluation of Steroids in IgA Nephropathy Global study [57], and the Chronic Kidney Disease Prognosis Consortium [58] have grown immensely within the last few years. There are possible advantages of introducing a traditional data element that are linked to kidney infections, like escalating the overall power of the groups which are under-represented [59].…”

Section: Introductionmentioning

confidence: 99%

Promises of Big Data and Artificial Intelligence in Nephrology and Transplantation

Thongprayoon

Kaewput

Kovvuru

et al. 2020

JCM

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Kidney diseases form part of the major health burdens experienced all over the world. Kidney diseases are linked to high economic burden, deaths, and morbidity rates. The great importance of collecting a large quantity of health-related data among human cohorts, what scholars refer to as “big data”, has increasingly been identified, with the establishment of a large group of cohorts and the usage of electronic health records (EHRs) in nephrology and transplantation. These data are valuable, and can potentially be utilized by researchers to advance knowledge in the field. Furthermore, progress in big data is stimulating the flourishing of artificial intelligence (AI), which is an excellent tool for handling, and subsequently processing, a great amount of data and may be applied to highlight more information on the effectiveness of medicine in kidney-related complications for the purpose of more precise phenotype and outcome prediction. In this article, we discuss the advances and challenges in big data, the use of EHRs and AI, with great emphasis on the usage of nephrology and transplantation.

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Section: Introductionmentioning

confidence: 99%

Promises of Big Data and Artificial Intelligence in Nephrology and Transplantation

Thongprayoon

Kaewput

Kovvuru

et al. 2020

JCM

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“…Chronic kidney disease (CKD) is on rise in both developed and developing nations with an estimated prevalence of 10% to 16% globally (Dienemann et al, 2016;WHO, 2015). In Vietnam, the incidence of CKD is increasing rapidly due to the growing burden of diabetes and hypertension (Hyodo et al, 2017).…”

Section: Introductionmentioning

confidence: 99%

Psychometric evaluation of the culturally and linguistically translated Vietnamese chronic kidney disease self‐management instrument

Nguyen

Douglas

Bonner

2019

Int J of Nursing Practice

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Aims To translate and psychometrically test the modified chronic kidney disease self‐management instrument in Vietnamese language. Background Research on chronic kidney disease self‐management is increasing although few patient‐reported outcome measures are available in other languages. Design This study involved instrument modification, translation, and cultural adaptation into Vietnamese followed by psychometric evaluation in a target population. Methods Following modification, the instrument was translated by bilingual independent translators, and then an expert panel assessed content face validity. Reliability of the instrument was assessed by internal consistency and test‐retest reliability in a sample of 293 people with chronic kidney disease. Then exploratory factor analysis was used to evaluate construct validity of the Vietnamese version. Results The Vietnamese chronic kidney disease self‐management instrument demonstrated excellent content face validity and internal consistency. The test‐retest indicated good stability of the instrument over a 2‐week period. Four factors were identified using exploratory factor analysis and were named understanding my kidney disease, taking action to manage my kidney disease, seeking social support, and adhering to a healthy diet. Conclusions The translated and modified version is a valid, reliable, and feasible patient‐reported outcome measure of self‐management behaviour in Vietnamese‐speaking populations.

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“…The global prevalence of CKD in all adults is estimated at between 10% to 16% (Dienemann et al, 2016), with the majority of people in stages 3-5 (10.6%) (Hill et al, 2016). The estimated prevalence of CKD varies considerably and this may be due to whether the disease has been diagnosed and also the methods for collecting national data for reporting in registries.…”

Section: Globalmentioning

confidence: 99%

Self-Management Program for People with Chronic Kidney Disease in Vietnam: A Pragmatic Randomised Controlled Trial

Nguyen¹

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International Network of Chronic Kidney Disease cohort studies (iNET-CKD): a global network of chronic kidney disease cohorts

Cited by 51 publications

References 33 publications

Promises of Big Data and Artificial Intelligence in Nephrology and Transplantation

Promises of Big Data and Artificial Intelligence in Nephrology and Transplantation

Psychometric evaluation of the culturally and linguistically translated Vietnamese chronic kidney disease self‐management instrument

Self-Management Program for People with Chronic Kidney Disease in Vietnam: A Pragmatic Randomised Controlled Trial

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