Evidence map›Paper›PMID 37301501›Full record

ArticleAmerican journal of kidney diseases : the official journal of the National Kidney Foundation2023

Utility of the Kidney Failure Risk Equation and Estimated GFR for Estimating Time to Kidney Failure in Advanced CKD.

Chi D Chu, Charles E McCulloch, Raymond K Hsu, Neil R Powe, Brian Bieber, Bruce M Robinson, Rupesh Raina, Roberto Pecoits-Filho, Delphine S Tuot

Open access · hybridAbstract read
In one paragraph

Article in American journal of kidney diseases : the official journal of the National Kidney Foundation, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed, 2 pooled it
4.0field-weighted citation impact, top 6% 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

10 citing papers in PubMed, 2 syntheses or guidelines pooled it, 20 citations in OpenAlex.

  1. Guideline
  2. Pooled it
  3. Review
  4. Article
  5. Dynamic Risk Prediction of Graft Failure after Deceased Donor Kidney Transplant.Clinical journal of the American Society of Nephrology : CJASN · 2026
    Article
  6. Article
  7. Article
  8. Review
  9. Clinical impact of the Kidney Failure Risk Equation for vascular access planning.Nephrology, dialysis, transplantation : official publication of the European Dialysis and Transplant Association - European Renal Association · 2024
    Article
  10. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

9 authors at 3 institutions in 1 country.

Chi D ChuDepartment of Medicine, University of California-San Francisco, San Francisco, California. Electronic address: chi.chu@ucsf.edu.
Charles E McCullochDepartment of Epidemiology and Biostatistics, University of California-San Francisco, San Francisco, California.
Raymond K HsuDepartment of Medicine, University of California-San Francisco, San Francisco, California.
Neil R PoweDepartment of Medicine, University of California-San Francisco, San Francisco, California.
Brian BieberArbor Research Collaborative for Health, Ann Arbor, Michigan.
Bruce M RobinsonArbor Research Collaborative for Health, Ann Arbor, Michigan.
Rupesh RainaDepartment of Pediatric Nephrology, Akron Children's Hospital, Akron, Ohio; Department of Nephrology, Akron Nephrology Associates/Cleveland Clinic Akron General Medical Center, Akron, Ohio.
Roberto Pecoits-FilhoArbor Research Collaborative for Health, Ann Arbor, Michigan.
Delphine S TuotDepartment of Medicine, University of California-San Francisco, San Francisco, California.
University of California, San Francisco · USArbor Research Collaborative for Health · USAkron Children's Hospital · US

Funding

Targeted Automated Nephrology e-Consultation for Diabetic Kidney DiseaseK23DK131316 · NIDDK · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI CHU, CHI · 2023 to 2024
$277k
AHRQ HHS K12 HS026383NIDDK NIH HHS K23 DK131316
6 · The paper itself

Abstract

RATIONALE &

objectiveThe Kidney Failure Risk Equation (KFRE) predicts the 2-year risk of kidney failure for patients with chronic kidney disease (CKD). Translating KFRE-predicted risk or estimated glomerular filtration rate (eGFR) into time to kidney failure could inform decision making for patients approaching kidney failure. STUDY

designRetrospective cohort. SETTING &

participantsCKD Outcomes and Practice Patterns Study (CKDOPPS) cohort of patients with an eGFR<60mL/min/1.73m EXPOSURE: 2-year KFRE risk or eGFR. OUTCOME: Kidney failure defined as initiation of dialysis or kidney transplantation. ANALYTICAL APPROACH: Accelerated failure time (Weibull) models used to estimate the median, 25th, and 75th percentile times to kidney failure starting from KFRE values of 20%, 40%, and 50%, and from eGFR values of 20, 15, and 10mL/min/1.73m

resultsOverall, 1,641 participants were included (mean age 69±13 years; median eGFR of 28mL/min/1.73m LIMITATIONS: Inability to account for competing risks when estimating time to kidney failure.

conclusionsAmong those with eGFR<15mL/min/1.73m PLAIN-LANGUAGE SUMMARY: Clinicians often talk to patients with advanced chronic kidney disease about the level of kidney function expressed as the estimated glomerular filtration rate (eGFR) and about the risk of developing kidney failure, which can be estimated using the Kidney Failure Risk Equation (KFRE). In a cohort of patients with advanced chronic kidney disease, we examined how eGFR and KFRE risk predictions corresponded to the time patients had until reaching kidney failure. Among those with eGFR<15mL/min/1.73m

Indexed as

Renal InsufficiencyRenal Insufficiency, ChronicAgedAged, 80 and overAlbuminuriaGlomerular Filtration RateHumansMaleMiddle AgedRetrospective StudiesChronic kidney diseaseend-stage kidney diseaseKFREkidney failurekidney failure risk equation

Identifiers

PMID37301501
PMCPMC10588536
OpenAlexW4379931704

What Socratic holds

Textmetadata
LicenceTDM
Read underepoch 390

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 Socratic graph.