Evidence map›Paper›PMID 28410646›Full record

ReviewSeminars in nephrology2017

Evolution of Cardiovascular Disease During the Transition to End-Stage Renal Disease.

Nisha Bansal

Open access · greenAbstract readReview
In one paragraph

Review in Seminars in nephrology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
24citing papers in PubMed, 1 pooled it
3.0field-weighted citation impact, top 8% 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

24 citing papers in PubMed, 1 synthesis or guideline pooled it, 49 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Review
  4. Article
  5. SerumLife (Basel, Switzerland) · 2025
    Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Observational
  13. Article
  14. Article
  15. Review
  16. Kidney international reports · 2021
    Article
  17. Article
  18. Article
  19. 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

1 author at 1 institution in 1 country.

Nisha BansalDivision of Nephrology, Kidney Research Institute, University of Washington, Seattle, WA. Electronic address: nbansal@nephrology.washington.edu.
University of Washington · US

Funding

Heart failure and atrial arrhythmias in CKDR01DK103612 · NIDDK · UNIVERSITY OF WASHINGTON · PI BANSAL, NISHA · 2015 to 2018
$1.9M
Blood Pressure in Advanced Chronic Kidney DiseaseK23DK088865 · NIDDK · UNIVERSITY OF WASHINGTON · PI BANSAL, NISHA · 2010 to 2014
$848k
NIDDK NIH HHS K23 DK088865NIDDK NIH HHS R01 DK103612
6 · The paper itself

Abstract

Cardiovascular disease (CVD) remains the leading cause of morbidity and mortality in patients with chronic kidney disease (CKD) and end-stage renal disease (ESRD). The rate of death in incident dialysis patients remains high. This has led to interest in the study of the evolution of CVD during the critical transition period from CKD to ESRD. Understanding the natural history and risk factors of clinical and subclinical CVD during this transition may help guide the timing of appropriate CVD therapies to improve outcomes in patients with kidney disease. This review provides an overview of the epidemiology of subclinical and clinical CVD during the transition from CKD to ESRD and discusses clinical trials of CVD therapies to mitigate risk of CVD in CKD and ESRD patients.

Indexed as

Cardiovascular DiseasesGlomerular Filtration RateHumansKidney Failure, ChronicRenal DialysisRenal Insufficiency, ChronicVascular CalcificationVascular StiffnessVentricular Function, LeftCardiovascular diseaseCKDESRDtransition

Identifiers

PMID28410646
PMCPMC5407373
OpenAlexW2607164125

What OpenQuestion 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 OpenQuestion graph.