Prognostic imaging biomarkers for diabetic kidney disease (iBEAt): study protocol.
Обработка статьи · этапы, ошибки и управление
Ошибки и ограничения
История · было → стало
Состояние обновляется каждые 5 секунд, пока блок открыт. Процент показывается только там, где известен объём работы. Пауза останавливает продолжение этапа; текущий запрос к источнику может завершиться.
Gooding Kim M, Lienczewski Chrysta, Papale Massimo, Koivuviita Niina, Maziarz Marlena, Dutius Andersson Anna-Maria, Sharma Kanishka, Pontrelli Paola, Garcia Hernandez Alberto, Bailey Julie, Tobin Kay, Saunavaara Virva, Zetterqvist Anna, Shelley David, Teh Irvin, Ball Claire, Puppala Sapna, Ibberson Mark, Karihaloo Anil, Metsärinne Kaj, Banks Rosamonde E, Gilmour Peter S, Mansfield Michael, Gilchrist Mark, de Zeeuw Dick, Heerspink Hiddo J L, Nuutila Pirjo, Kretzler Matthias, Welberry Smith Matthew, Gesualdo Loreto, Andress Dennis, Grenier Nicolas, Shore Angela C, Gomez Maria F, Sourbron Steven, BEAt-DKD consortium
Аннотация
METHODS: iBEAt is a prospective multi-centre observational cohort study recruiting 500 patients with type 2 diabetes (T2D) and eGFR ≥30 ml/min/1.73m2. At baseline, blood and urine will be collected, clinical examinations will be performed, and medical history will be obtained. These assessments will be repeated annually for 3 years. At baseline each participant will also undergo quantitative renal MRI and US with central processing of MRI images. Biological samples will be stored in a central laboratory for biomarker and validation studies, and data in a central data depository. Data analysis will explore the potential associations between imaging biomarkers and renal function, and whether the imaging biomarkers improve the prediction of DKD progression. Ancillary substudies will: (1) validate imaging biomarkers against renal histopathology; (2) validate MRI based renal blood flow measurements against H2O15 positron-emission tomography (PET); (3) validate methods for (semi-)automated processing of renal MRI; (4) examine longitudinal changes in imaging biomarkers; (5) examine whether glycocalyx and microvascular measures are associated with imaging biomarkers and eGFR decline; (6) explore whether the findings in T2D can be extrapolated to type 1 diabetes.
DISCUSSION: iBEAt is the largest DKD imaging study to date and will provide valuable insights into the progression and heterogeneity of DKD. The results may contribute to a more personalised approach to DKD management in patients with T2D.
TRIAL REGISTRATION: Clinicaltrials.gov ( NCT03716401 ).