Evidence map›Paper›PMID 33707181›Full record

ArticleClinical journal of the American Society of Nephrology : CJASN2021

Identification of Patients with CKD in Medical Databases: A Comparison of Different Algorithms.

Søren Viborg Vestergaard, Christian Fynbo Christiansen, Reimar Wernich Thomsen, Henrik Birn, Uffe Heide-Jørgensen

Registry-linked trialAbstract readComparative Study
In one paragraph

Article in Clinical journal of the American Society of Nephrology : CJASN, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT07193056 (Chronic Kidney Disease -Mineral and Bone Disorder, The CPH-MBD Cohort), which is not on this map. Cited by 37 papers.

0numbers the graph read from it
0cells of the map it votes in
37citing papers in PubMed
–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.

NCT07193056 not yet recruitingnot on this mapstarted 2025, after this paper: background citation

Chronic Kidney Disease -Mineral and Bone Disorder, The CPH-MBD Cohort

Typeobservational_patient_registrySponsorHerlev HospitalRan2025 to 2055Enrolled1,000ConditionsChronic Kidney Disease Mineral and Bone Disorder, Chronic Kidney Disease (CKD), Bone Markers
3 · Its place in the literature

Who cites it

37 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Workforce Detachment in Persons with CKD.Clinical journal of the American Society of Nephrology : CJASN · 2026
    Observational
  7. Article
  8. Article
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  10. Article
  11. Article
  12. Article
  13. Article
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  15. Article
  16. Article
  17. Article
  18. Article
  19. Recovery of kidney function after acute kidney disease-a multi-cohort analysis.Nephrology, dialysis, transplantation : official publication of the European Dialysis and Transplant Association - European Renal Association · 2024
    Article
  20. Article
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

5 authors.

Søren Viborg VestergaardDepartment of Clinical Epidemiology, Aarhus University Hospital, Aarhus, Denmark.ORCID 0000-0002-8445-7758
Christian Fynbo ChristiansenDepartment of Clinical Epidemiology, Aarhus University Hospital, Aarhus, Denmark.ORCID 0000-0002-0727-953
Reimar Wernich ThomsenDepartment of Clinical Epidemiology, Aarhus University Hospital, Aarhus, Denmark.ORCID 0000-0001-9135-3474
Henrik BirnDepartment of Renal Medicine, Aarhus University Hospital, Aarhus, Denmark.
Uffe Heide-JørgensenDepartment of Clinical Epidemiology, Aarhus University Hospital, Aarhus, Denmark.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

BACKGROUND AND

objectivesDespite CKD consensus definitions, epidemiologic studies use multiple different algorithms to identify CKD. We aimed to elucidate if this affects the patient characteristics and the estimated prevalence and prognosis of CKD by applying six different algorithms to identify CKD in population-based medical databases and compare the cohorts. DESIGN, SETTING, PARTICIPANTS, & MEASUREMENTS: Patients with CKD in Northern Denmark (2009-2016) were identified using six different algorithms: five were laboratory based defined by (

resultsThe five different laboratory-based algorithms resulted in large differences in the estimated prevalence of CKD from 4637-8327 per 100,000 population. In contrast, 1-year mortality varied only slightly (7%-9%). Baseline eGFR levels at diagnosis were comparable (53-56 ml/min per 1.73 m

conclusionsPopulation prevalence of CKD identified in medical databases greatly depends on the applied algorithm to define CKD. Despite these differences, laboratory-based algorithms produce cohorts with similar prognosis. PODCAST: This article contains a podcast at https://www.asn-online.org/media/podcast/CJASN/2021_03_11_CJN15691020_final.mp3.

Indexed as

AlgorithmsDatabases, FactualAgedAged, 80 and overFemaleHumansMaleMiddle AgedPrevalencePrognosisRenal Insufficiency, Chronicalgorithmschronic kidney diseaseepidemiologyglomerular filtration ratehospital recordsincidencemortalityprevalenceprognosisregistries

Identifiers

PMID33707181
PMCPMC8092062

What OpenQuestion holds

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Registered trials

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.