Evidence map›Paper›PMID 34570204›Full record

ArticleJAMA network open2021

Trends in Chronic Kidney Disease Care in the US by Race and Ethnicity, 2012-2019.

Chi D Chu, Neil R Powe, Charles E McCulloch, Deidra C Crews, Yun Han, Jennifer L Bragg-Gresham, Rajiv Saran, Alain Koyama, Nilka R Burrows, Delphine S Tuot and 1 more

Open access · goldAbstract read
In one paragraph

Article in JAMA network open, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 53 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
53citing papers in PubMed, 1 pooled it
6.7field-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

53 citing papers in PubMed, 1 synthesis or guideline pooled it, 79 citations in OpenAlex.

  1. Pooled it
  2. Comparative Patterns in CKD among Native Israeli and Immigrant Ethnic Populations.Clinical journal of the American Society of Nephrology : CJASN · 2026
    Article
  3. A Microsimulation-Based Approach for Mitigating Societal Bias in Chronic Kidney Disease Data.Medical decision making : an international journal of the Society for Medical Decision Making · 2026
    Article
  4. Review
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. A microsimulation-based framework for mitigating societal bias in primary care data.medRxiv : the preprint server for health sciences · 2025
    Article
  14. Article
  15. Tirzepatide and Kidney Protection in Obesity: Unanswered Questions.Journal of the American Society of Nephrology : JASN · 2025
    Article
  16. Article
  17. Review
  18. Article
  19. Article
  20. Population Health Management for Improving Kidney Health Outcomes.American journal of kidney diseases : the official journal of the National Kidney Foundation · 2025
    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

11 authors at 6 institutions in 1 country.

Chi D ChuDivision of Nephrology, University of California, San Francisco.
Neil R PoweDepartment of Medicine, University of California, San Francisco.
Charles E McCullochDepartment of Epidemiology and Biostatistics, University of California, San Francisco.
Deidra C CrewsDivision of Nephrology, Johns Hopkins University School of Medicine, Baltimore, Maryland.
Yun HanDivision of Nephrology, Department of Medicine, University of Michigan, Ann Arbor.
Jennifer L Bragg-GreshamKidney Epidemiology and Cost Center, University of Michigan, Ann Arbor.
Rajiv SaranDivision of Nephrology, Department of Medicine, University of Michigan, Ann Arbor.
Alain KoyamaDivision of Diabetes Translation, Centers for Disease Control and Prevention, Atlanta, Georgia.
Nilka R BurrowsDivision of Diabetes Translation, Centers for Disease Control and Prevention, Atlanta, Georgia.
Delphine S TuotDivision of Nephrology, University of California, San Francisco.
Centers for Disease Control and Prevention Chronic Kidney Disease Surveillance Team
The Centers · USUniversity of Michigan · USCenters for Disease Control and Prevention · USSan Francisco General Hospital · USUniversity of California, San Francisco · USJohns Hopkins University · US

Funding

Evaluating the Impact of Guidelines on Physician Prescription Practices in Chronic Kidney DiseaseF32DK122629 · NIDDK · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI CHU, CHI · 2019 to 2020
$157k
NIDDK NIH HHS F32 DK122629
6 · The paper itself

Abstract

Importance: Significant racial and ethnic disparities in chronic kidney disease (CKD) progression and outcomes are well documented, as is low use of guideline-recommended CKD care. Objective: To examine guideline-recommended CKD care delivery by race and ethnicity in a large, diverse population. Design, Setting, and Participants: In this serial cross-sectional study, adult patients with CKD that did not require dialysis, defined as a persistent estimated glomerular filtration rate less than 60 mL/min/1.73 m2 or a urine albumin-creatinine ratio of 30 mg/g or higher for at least 90 days, were identified in 2-year cross-sections from January 1, 2012, to December 31, 2019. Data from the OptumLabs Data Warehouse, a national data set of administrative and electronic health record data for commercially insured and Medicare Advantage patients, were used. Exposures: The independent variables were race and ethnicity, as reported in linked electronic health records. Main Outcomes and Measures: On the basis of guideline-recommended CKD care, the study examined care delivery process measures (angiotensin-converting enzyme inhibitor or angiotensin II receptor blocker prescription for albuminuria, statin prescription, albuminuria testing, nephrology care for CKD stage 4 or higher, and avoidance of chronic nonsteroidal anti-inflammatory drug prescription) and care delivery outcome measures (blood pressure and diabetes control). Results: A total of 452 238 patients met the inclusion criteria (mean [SD] age, 74.0 [10.2] years; 262 089 [58.0%] female; a total of 7573 [1.7%] Asian, 49 970 [11.0%] Black, 15 540 [3.4%] Hispanic, and 379 155 [83.8%] White). Performance on process measures was higher among Asian, Black, and Hispanic patients compared with White patients for angiotensin-converting enzyme inhibitor and angiotensin II receptor blocker use (79.8% for Asian patients, 76.7% for Black patients, and 79.9% for Hispanic patients compared with 72.3% for White patients in 2018-2019), statin use (72.6% for Asian patients, 69.1% for Black patients, and 74.1% for Hispanic patients compared with 61.5% for White patients), nephrology care (64.8% for Asian patients, 72.9% for Black patients, and 69.4% for Hispanic patients compared with 58.3% for White patients), and albuminuria testing (53.9% for Asian patients, 41.0% for Black patients, and 52.6% for Hispanic patients compared with 30.7% for White patients). Achievement of blood pressure control to less than 140/90 mm Hg was similar or lower among Asian (71.8%), Black (63.3%), and Hispanic (69.8%) patients compared with White patients (72.9%). Achievement of diabetes control with hemoglobin A1c less than 7.0% was 50.1% in Asian patients, 49.3% in Black patients, and 46.0% in Hispanic patients compared with 50.3% for White patients. Conclusions and Relevance: Higher performance on CKD care process measures among Asian, Black, and Hispanic patients suggests that differences in medication prescription and diagnostic testing are unlikely to fully explain known disparities in CKD progression and kidney failure. Improving care delivery processes alone may be inadequate for reducing these disparities.

Indexed as

AgedAged, 80 and overCross-Sectional StudiesEthnicityFemaleHealthcare DisparitiesHumansMaleMedicareMiddle AgedPatient Acceptance of Health CareRacial GroupsRenal Insufficiency, ChronicUnited States

Identifiers

PMID34570204
PMCPMC8477264
OpenAlexW3202055205

What OpenQuestion holds

Textmetadata
LicenceCC BY
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Registered trials

None linked

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.