Evidence map›Paper›PMID 34249352›Full record

ArticleClinical kidney journal2021

Methods and rationale of the DISCOVER CKD global observational study.

Roberto Pecoits-Filho, Glen James, Juan Jesus Carrero, Eric Wittbrodt, Steven Fishbane, Alyshah Abdul Sultan, Hiddo J L Heerspink, Katarina Hedman, Eiichiro Kanda, Hungta Tony Chen and 13 more

Abstract read
In one paragraph

Article in Clinical kidney journal, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
20citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

20 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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  3. "Kidney international reports · 2025
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  5. Observational
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  12. Frontiers in nephrology · 2024
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

23 authors.

Roberto Pecoits-FilhoSchool of Medicine, Pontifícia Universidade Católica do Paraná, Curitiba, Brazil.ORCID https://orcid.org/0000-0002-0255-6710
Glen JamesAstraZeneca, Cambridge, UK.
Juan Jesus CarreroDepartment of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden.ORCID https://orcid.org/0000-0003-4763-2024
Eric WittbrodtAstraZeneca, Gaithersburg, MD, USA.
Steven FishbaneDivision of Nephrology, Zucker School of Medicine at Hofstra/Northwell, Hempstead, NY, USA.
Alyshah Abdul SultanAstraZeneca, Cambridge, UK.
Hiddo J L HeerspinkDepartment of Clinical Pharmacy and Pharmacology, University of Groningen, Groningen, the Netherlands.
Katarina HedmanAstraZeneca, Gothenburg, Sweden.
Eiichiro KandaMedical Science, Kawasaki Medical School, Kurashiki, Japan.
Hungta Tony ChenAstraZeneca, Gaithersburg, MD, USA.
Naoki KashiharaDepartment of Nephrology and Hypertension, Kawasaki Medical School, Kurashiki, Japan.
James SloandAstraZeneca, Gaithersburg, MD, USA.
Mikhail KosiborodSaint Luke's Mid America Heart Institute, University of Missouri-Kansas City, Kansas City, MO, USA.
Supriya KumarAstraZeneca, Gaithersburg, MD, USA.
Mitja LainscakDivision of Cardiology, General Hospital Murska Sobota, Murska Sobota, Slovenia.
Matthew ArnoldAstraZeneca, Cambridge, UK.
Carolyn S P LamNational Heart Centre, Singapore.
Björn HolmqvistAstraZeneca, Gothenburg, Sweden.
Carol PollockKolling Institute, Royal North Shore Hospital, University of Sydney, Sydney, NSW, Australia.
Peter FeniciAstraZeneca, Cambridge, UK.
Peter StenvinkelDivision of Renal Medicine, Karolinska University Hospital, Karolinska Institutet, Stockholm, Sweden.
Jennie MedinAstraZeneca, Gothenburg, Sweden.
David C WheelerDepartment of Renal Medicine, University College London, London, UK.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundReal-world data for patients with chronic kidney disease (CKD), specifically pertaining to clinical management, metabolic control, treatment patterns, quality of life (QoL) and dietary patterns, are limited. Understanding these gaps using real-world, routine care data will improve our understanding of the challenges and consequences faced by patients with CKD, and will facilitate the long-term goal of improving their management and prognosis.

methodsDISCOVER CKD follows an enriched hybrid study design, with both retrospective and prospective patient cohorts, integrating primary and secondary data from patients with CKD from China, Italy, Japan, Sweden, the UK and the USA. Data will be prospectively captured over a 3-year period from >1000 patients with CKD who will be followed up for at least 1 year via electronic case report form entry during routine clinical visits and also via a mobile/tablet-based application, enabling the capture of patient-reported outcomes (PROs). In-depth interviews will be conducted in a subset of ∼100 patients. Separately, secondary data will be retrospectively captured from >2 000 000 patients with CKD, extracted from existing datasets and registries.

resultsThe DISCOVER CKD program captures and will report on patient demographics, biomarker and laboratory measurements, medical histories, clinical outcomes, healthcare resource utilization, medications, dietary patterns, physical activity and PROs (including QoL and qualitative interviews).

conclusionsThe DISCOVER CKD program will provide contemporary real-world insight to inform clinical practice and improve our understanding of the epidemiology and clinical and economic burden of CKD, as well as determinants of clinical outcomes and PROs from a range of geographical regions in a real-world CKD setting.

Indexed as

chronic kidney diseasemethods and rationalepatient-reported outcomesquality of lifereal-world evidence

Identifiers

PMID34249352
PMCPMC8264307

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.