Literature DB >> 33707181

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

Søren Viborg Vestergaard1, Christian Fynbo Christiansen2, Reimar Wernich Thomsen2, Henrik Birn3,4, Uffe Heide-Jørgensen2.   

Abstract

BACKGROUND AND OBJECTIVES: Despite 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 (1) one measured outpatient eGFR <60 ml/min per 1.73 m2 (single test, n=103,435), (2) two such findings ≥90 days apart (Kidney Disease Improving Global Outcomes, n=84,688), (3) two such findings ≥90 days apart with no eGFR >60 ml/min per 1.73 m2 observed in-between (Kidney Disease Improving Global Outcomes, persistent, n=68,994), (4) two such findings ≥90 and <365 days apart (Kidney Disease Improving Global Outcomes, time limited, n=75,031), and (5) two eGFRs <60 ml/min per 1.73 m2 or two urine albumin-creatinine ratios >30 mg/g ≥90 days apart (Kidney Disease Improving Global Outcomes, eGFR/albuminuria, n=100,957). The sixth included patients identified by reported in- and outpatient hospital International Classification of Diseases diagnoses of CKD (hospital-diagnosed, n=27,947). For each cohort, we estimated baseline eGFR, CKD prevalence, and 1-year mortality using the Kaplan-Meier method.
RESULTS: The 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 m2), whereas median time since first recorded eGFR <60 ml/min per 1.73 m2 varied from 0 months (single-test) to 17 months (Kidney Disease Improving Global Outcomes, persistent). The hospital-diagnosed algorithm yielded markedly lower CKD prevalence (775 per 100,000 population), a lower baseline eGFR (47 ml/min per 1.73 m2), longer time since first eGFR <60 ml/min per 1.73 m2 (median 70 months), and much higher 1-year mortality (22%).
CONCLUSIONS: Population 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.
Copyright © 2021 by the American Society of Nephrology.

Entities:  

Keywords:  algorithms; chronic kidney disease; epidemiology; glomerular filtration rate; hospital records; incidence; mortality; prevalence; prognosis; registries

Mesh:

Year:  2021        PMID: 33707181      PMCID: PMC8092062          DOI: 10.2215/CJN.15691020

Source DB:  PubMed          Journal:  Clin J Am Soc Nephrol        ISSN: 1555-9041            Impact factor:   8.237


  30 in total

1.  Validating a case definition for chronic kidney disease using administrative data.

Authors:  Paul E Ronksley; Marcello Tonelli; Hude Quan; Braden J Manns; Matthew T James; Fiona M Clement; Susan Samuel; Robert R Quinn; Pietro Ravani; Sony S Brar; Brenda R Hemmelgarn
Journal:  Nephrol Dial Transplant       Date:  2011-10-19       Impact factor: 5.992

2.  Chronic kidney disease, hypertension, diabetes, and obesity in the adult population of Morocco: how to avoid "over"- and "under"-diagnosis of CKD.

Authors:  Mohammed Benghanem Gharbi; Monique Elseviers; Mohamed Zamd; Abdelali Belghiti Alaoui; Naïma Benahadi; El Hassane Trabelssi; Rabia Bayahia; Benyounès Ramdani; Marc E De Broe
Journal:  Kidney Int       Date:  2016-04-13       Impact factor: 10.612

Review 3.  Chronic kidney disease and mortality risk: a systematic review.

Authors:  Marcello Tonelli; Natasha Wiebe; Bruce Culleton; Andrew House; Chris Rabbat; Mei Fok; Finlay McAlister; Amit X Garg
Journal:  J Am Soc Nephrol       Date:  2006-05-31       Impact factor: 10.121

4.  Prevalence and recognition of chronic kidney disease in Stockholm healthcare.

Authors:  Alessandro Gasparini; Marie Evans; Josef Coresh; Morgan E Grams; Olof Norin; Abdul R Qureshi; Björn Runesson; Peter Barany; Johan Ärnlöv; Tomas Jernberg; Björn Wettermark; Carl G Elinder; Juan-Jesüs Carrero
Journal:  Nephrol Dial Transplant       Date:  2016-10-13       Impact factor: 5.992

5.  Elevated potassium levels in patients with chronic kidney disease: occurrence, risk factors and clinical outcomes-a Danish population-based cohort study.

Authors:  Reimar W Thomsen; Sia K Nicolaisen; Pål Hasvold; Ricardo Garcia Sanchez; Lars Pedersen; Kasper Adelborg; Kenneth Egstrup; Martin Egfjord; Henrik Toft Sørensen
Journal:  Nephrol Dial Transplant       Date:  2018-09-01       Impact factor: 5.992

6.  Sixteen years of creatinine measurements among 460 000 individuals-The Funen Laboratory Cohort (FLaC), a population-based pharmacoepidemiological resource to study drug-induced kidney disease.

Authors:  Daniel Pilsgaard Henriksen; Per Damkier; Jesper Hallas; Mads Nybo
Journal:  Basic Clin Pharmacol Toxicol       Date:  2018-12-18       Impact factor: 4.080

7.  A population-based study on the prevalence and incidence of chronic kidney disease in the Netherlands.

Authors:  Jan C van Blijderveen; Sabine M Straus; Robert Zietse; Bruno H Stricker; Miriam C Sturkenboom; Katia M Verhamme
Journal:  Int Urol Nephrol       Date:  2013-09-27       Impact factor: 2.370

8.  Validation of The Health Improvement Network (THIN) database for epidemiologic studies of chronic kidney disease.

Authors:  Michelle R Denburg; Kevin Haynes; Justine Shults; James D Lewis; Mary B Leonard
Journal:  Pharmacoepidemiol Drug Saf       Date:  2011-08-24       Impact factor: 2.890

9.  Epidemiology of chronic kidney disease: think (at least) twice!

Authors:  Pierre Delanaye; Richard J Glassock; Marc E De Broe
Journal:  Clin Kidney J       Date:  2017-02-27

Review 10.  Existing Data Sources in Clinical Epidemiology: Laboratory Information System Databases in Denmark.

Authors:  Johan Frederik Håkonsen Arendt; Anette Tarp Hansen; Søren Andreas Ladefoged; Henrik Toft Sørensen; Lars Pedersen; Kasper Adelborg
Journal:  Clin Epidemiol       Date:  2020-05-18       Impact factor: 4.790

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  10 in total

1.  Effect of the Refitted Race-Free eGFR Formula on the CKD Prevalence and Mortality in the Danish Population.

Authors:  Søren Viborg Vestergaard; Uffe Heide-Jørgensen; Henrik Birn; Christian Fynbo Christiansen
Journal:  Clin J Am Soc Nephrol       Date:  2022-01-11       Impact factor: 8.237

2.  Accuracy of identifying diagnosis of moderate to severe chronic kidney disease in administrative claims data.

Authors:  Julie M Paik; Elisabetta Patorno; Min Zhuo; Lily G Bessette; Cassandra York; Nileesa Gautam; Dae Hyun Kim; Seoyoung C Kim
Journal:  Pharmacoepidemiol Drug Saf       Date:  2021-12-23       Impact factor: 2.890

Review 3.  Epidemiology of chronic kidney disease: an update 2022.

Authors:  Csaba P Kovesdy
Journal:  Kidney Int Suppl (2011)       Date:  2022-03-18

4.  Adverse outcomes after partner bereavement in people with reduced kidney function: Parallel cohort studies in England and Denmark.

Authors:  Patrick Bidulka; Søren Viborg Vestergaard; Admire Hlupeni; Anders Kjærsgaard; Angel Y S Wong; Sinéad M Langan; Sigrun Alba Johannesdottir Schmidt; Susan Lyon; Christian Fynbo Christiansen; Dorothea Nitsch
Journal:  PLoS One       Date:  2021-09-23       Impact factor: 3.240

5.  Sex-Specific Differences in Mortality and Incident Dialysis in the Chronic Kidney Disease Outcomes and Practice Patterns Study.

Authors:  Manfred Hecking; Charlotte Tu; Jarcy Zee; Brian Bieber; Sebastian Hödlmoser; Helmut Reichel; Ricardo Sesso; Friedrich K Port; Bruce M Robinson; Juan Jesus Carrero; Allison Tong; Christian Combe; Bénédicte Stengel; Roberto Pecoits-Filho
Journal:  Kidney Int Rep       Date:  2021-12-01

6.  Soluble urokinase plasminogen activator receptor and decline in kidney function among patients without kidney disease.

Authors:  Esben Iversen; Thomas Kallemose; Mads Hornum; Anne Kathrine Bengaard; Jan Olof Nehlin; Line Jee Hartmann Rasmussen; Haakon Sandholdt; Juliette Tavenier; Bo Feldt-Rasmussen; Ove Andersen; Jesper Eugen-Olsen; Morten Baltzer Houlind
Journal:  Clin Kidney J       Date:  2022-02-21

7.  The Intake of Ultra-Processed Foods and Prevalence of Chronic Kidney Disease: The Health Examinees Study.

Authors:  Anthony Kityo; Sang-Ah Lee
Journal:  Nutrients       Date:  2022-08-28       Impact factor: 6.706

8.  Childhood body mass index trajectories and associations with adult-onset chronic kidney disease in Denmark: A population-based cohort study.

Authors:  Julie Aarestrup; Kim Blond; Dorte Vistisen; Marit E Jørgensen; Marie Frimodt-Møller; Britt W Jensen; Jennifer L Baker
Journal:  PLoS Med       Date:  2022-09-21       Impact factor: 11.613

9.  Prevalence, outcomes, and cost of chronic kidney disease in a contemporary population of 2·4 million patients from 11 countries: The CaReMe CKD study.

Authors:  Johan Sundström; Johan Bodegard; Andreas Bollmann; Marc G Vervloet; Patrick B Mark; Avraham Karasik; Tiago Taveira-Gomes; Manuel Botana; Kåre I Birkeland; Marcus Thuresson; Levy Jäger; Manish M Sood; Gijs VanPottelbergh; Navdeep Tangri
Journal:  Lancet Reg Health Eur       Date:  2022-06-30

10.  Lithium and the risk of chronic kidney disease: A population-based case-control study.

Authors:  Mikkel Højlund; Jane Sterndorff Winkel; Mads Nybo; Jesper Hallas; Daniel Pilsgaard Henriksen; Per Damkier
Journal:  Basic Clin Pharmacol Toxicol       Date:  2022-06-06       Impact factor: 3.688

  10 in total

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