Evidence map›Paper›PMID 26209739›Full record

SynthesisNephrology, dialysis, transplantation : official publication of the European Dialysis and Transplant Association - European Renal Association2015

Methodology used in studies reporting chronic kidney disease prevalence: a systematic literature review.

Katharina Brück, Kitty J Jager, Evangelia Dounousi, Alexander Kainz, Dorothea Nitsch, Johan Ärnlöv, Dietrich Rothenbacher, Gemma Browne, Vincenzo Capuano, Pietro Manuel Ferraro and 23 more

Open access · bronzeAbstract readSystematic Review
PubMed Full text at PMC Publisher
In one paragraph

Synthesis in Nephrology, dialysis, transplantation : official publication of the European Dialysis and Transplant Association - European Renal Association, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 34 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
34citing papers in PubMed, 2 pooled it
8.2field-weighted citation impact, top 2% of its field
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

34 citing papers in PubMed, 2 syntheses or guidelines pooled it, 88 citations in OpenAlex.

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  19. Where to look for the most frequent biases?Nephrology (Carlton, Vic.) · 2020
    Review
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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

33 authors at 20 institutions in 16 countries.

Katharina BrückERA-EDTA Registry, Amsterdam Medical Center, Amsterdam, The Netherlands.
Kitty J JagerERA-EDTA Registry, Amsterdam Medical Center, Amsterdam, The Netherlands.
Evangelia DounousiDepartment of Nephrology, Medical School, University of Ioannina, Ioannina, Greece.
Alexander KainzDepartment of Internal Medicine III/Nephrology, Medical University, Vienna, Austria.
Dorothea NitschEpidemiology and Population Health, LSHTM and UCL Centre for Nephrology, London, UK.
Johan ÄrnlövDepartment of Medical Sciences/Molecular Epidemiology, Uppsala University, Uppsala, Sweden.
Dietrich RothenbacherInstitute of Epidemiology and Medical Biometry, Ulm University, Ulm, Germany.
Gemma BrowneDepartment of Epidemiology & Public Health, University College Cork, Ireland.
Vincenzo CapuanoUnità Opaerativa di Cardiologia ed UTIC, Mercato S. Severino Hospital, Mercato S. Severino, Italy.
Pietro Manuel FerraroNephrology and Dialysis, Columbus-Gemelli University Hospital, Catholic University of the Sacred Heart, Rome, Italy.
Jean FerrieresDepartment of Cardiology, Toulouse University School of Medicine, Rangueil Hospital, Toulouse, France.
Giovanni GambaroNephrology and Dialysis, Columbus-Gemelli University Hospital, Catholic University of the Sacred Heart, Rome, Italy.
Idris GuessousUnit of Population Epidemiology, Division of primary care medicine, Department of Community Medicine, Primary Care and Emergency Medicine, Geneva University Hospital, Geneva, Switzerland.
Stein HallanDepartment of Nephrology, St Olav Hospital, Norway/Faculty of Medicine, The Norwegian University of Science and Technology (NTNU), Trondheim, Norway.
Mika KastarinenFinnish Medicines Agency, Kuopio/National Institute for Health and Welfare, Helsinki, Finland.
Gerjan NavisDivision of Nephrology, Department of Internal Medicine, University Medical Center Groningen, Groningen, The Netherlands.
Alfonso Otero GonzalezDepartment of Nephrology, University Hospital of Ourense, Ourense, Spain.
Luigi PalmieriIstituto Superiore di Sanità, Rome, Italy.
Solfrid RomundstadDepartment of Nephrology, Levanger Hospital, Health Trust Nord-Trøndelag/The Norwegian University of Science and Technology (NTNU), Trondheim, Norway.
Belinda SpotoDepartment of Nephrology, Dialysis and Transplantation Unit, CNR-IFC, Clinical Epidemiology and Pathophysiology of Renal Diseases and Hypertension, Reggio Calabria, Italy.
Benedicte StengelResearch Centre in Epidemiology and Population Health, Inserm Unit 1018, Villejuif, France.
Charles TomsonDepartment of Nephrology, Freeman Hospital, Newcastle upon Tyne, UK.
Giovanni TripepiDepartment of Nephrology, Dialysis and Transplantation Unit, CNR-IFC, Clinical Epidemiology and Pathophysiology of Renal Diseases and Hypertension, Reggio Calabria, Italy.
Henry VölzkeInstitute for Community Medicine, University Medicine Greifswald, Greifswald, Germany.
Andrzej WiȩcekDepartement of Nephrology, Transplantology and Internal Diseases, Faculty of Medicine in Katowice, Medical University of Silesia in Katowice, Poland.
Ron GansevoortDepartment of Nephrology/Graduate School of Medical Sciences, University Medical Center Groningen, Groningen, The Netherlands.
Ben SchöttkerDivision of Clinical Epidemiology and Ageing Research, German Cancer Research, Heidelberg, Germany.
Christoph WannerDepartment of Nephrology, University Hospital Würzburg, Würzburg, Germany.
Jose VinhasDepartment of Nephrology, Setubal Hospital Centre, Setubal, Portugal.
Carmine ZoccaliDepartment of Nephrology, Dialysis and Transplantation Unit, CNR-IFC, Clinical Epidemiology and Pathophysiology of Renal Diseases and Hypertension, Reggio Calabria, Italy.
Wim Van BiesenDepartment of Nephrology, Ghent University Hospital, Ghent, Belgium.
Vianda S StelERA-EDTA Registry, Amsterdam Medical Center, Amsterdam, The Netherlands.
European CKD Burden Consortium
Istituto di Fisiologia Clinica · ITNorwegian University of Science and Technology · NOUniversità Cattolica del Sacro Cuore · ITUniversity Medical Center Groningen · NLCentre de recherche en Epidémiologie et Santé des Populations · FRComplejo Hospitalario de Ourense · ESFinnish Medicines Agency Fimea · FIFreeman Hospital · GBGerman Cancer Research Center · DEGhent University Hospital · BEHôpital Rangueil · FRHospital de São Bernardo · PTIstituto Superiore di Sanità · ITLondon School of Hygiene & Tropical Medicine · GBMedical University of Silesia · PLMedical University of Vienna · ATUniversitätsklinikum Würzburg · DEUniversitätsmedizin Greifswald · DEUniversität Ulm · DEUniversity College Cork · IE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundMany publications report the prevalence of chronic kidney disease (CKD) in the general population. Comparisons across studies are hampered as CKD prevalence estimations are influenced by study population characteristics and laboratory methods.

methodsFor this systematic review, two researchers independently searched PubMed, MEDLINE and EMBASE to identify all original research articles that were published between 1 January 2003 and 1 November 2014 reporting the prevalence of CKD in the European adult general population. Data on study methodology and reporting of CKD prevalence results were independently extracted by two researchers.

resultsWe identified 82 eligible publications and included 48 publications of individual studies for the data extraction. There was considerable variation in population sample selection. The majority of studies did not report the sampling frame used, and the response ranged from 10 to 87%. With regard to the assessment of kidney function, 67% used a Jaffe assay, whereas 13% used the enzymatic assay for creatinine determination. Isotope dilution mass spectrometry calibration was used in 29%. The CKD-EPI (52%) and MDRD (75%) equations were most often used to estimate glomerular filtration rate (GFR). CKD was defined as estimated GFR (eGFR) <60 mL/min/1.73 m(2) in 92% of studies. Urinary markers of CKD were assessed in 60% of the studies. CKD prevalence was reported by sex and age strata in 54 and 50% of the studies, respectively. In publications with a primary objective of reporting CKD prevalence, 39% reported a 95% confidence interval.

conclusionsThe findings from this systematic review showed considerable variation in methods for sampling the general population and assessment of kidney function across studies reporting CKD prevalence. These results are utilized to provide recommendations to help optimize both the design and the reporting of future CKD prevalence studies, which will enhance comparability of study results.

Indexed as

Glomerular Filtration RateSampling StudiesAdultBiomarkersCalibrationEuropeHumansPrevalenceRenal Insufficiency, ChronicBiomarkersCKDCKD-EPI equationepidemiologyMDRDsystematic review

Identifiers

PMID26209739
PMCPMC4514069
OpenAlexW2171252939

What OpenQuestion holds

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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.