Evidence map›Paper›PMID 25610846›Full record

ReviewWorld journal of clinical cases2015

Evaluation of chronic kidney disease in chronic heart failure: From biomarkers to arterial renal resistances.

Massimo Iacoviello, Marta Leone, Valeria Antoncecchi, Marco Matteo Ciccone

Open access · hybridAbstract readReview
In one paragraph

Review in World journal of clinical cases, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
1.9field-weighted citation impact, top 13% 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, 21 citations in OpenAlex.

  1. Trial
  2. Trial
  3. Review
  4. Review
  5. Article
  6. Article
  7. Article
  8. Biomarkers in Cardiorenal Syndromes.BioMed research international · 2018
    Review
  9. Article
  10. 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

4 authors at 1 institution in 1 country.

Massimo IacovielloMassimo Iacoviello, Cardiology Unit, Cardiothoracic Department, University Hospital Policlinico Consorziale of Bari, 70124 Bari, Italy.
Marta LeoneMassimo Iacoviello, Cardiology Unit, Cardiothoracic Department, University Hospital Policlinico Consorziale of Bari, 70124 Bari, Italy.
Valeria AntoncecchiMassimo Iacoviello, Cardiology Unit, Cardiothoracic Department, University Hospital Policlinico Consorziale of Bari, 70124 Bari, Italy.
Marco Matteo CicconeMassimo Iacoviello, Cardiology Unit, Cardiothoracic Department, University Hospital Policlinico Consorziale of Bari, 70124 Bari, Italy.
Azienda Universitaria Ospedaliera Consorziale - Policlinico Bari · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Chronic kidney disease and its worsening are recurring conditions in chronic heart failure (CHF) which are independently associated with poor patient outcome. The heart and kidney share many pathophysiological mechanisms which can determine dysfunction in each organ. Cardiorenal syndrome is the condition in which these two organs negatively affect each other, therefore an accurate evaluation of renal function in the clinical setting of CHF is essential. This review aims to revise the parameters currently used to evaluate renal dysfunction in CHF with particular reference to the usefulness and the limitations of biomarkers in evaluating glomerular dysfunction and tubular damage. Moreover, it is reported the possible utility of renal arterial resistance index (a parameter associated with abnormalities in renal vascular bed) for a better assesment of kidney disfunction.

Indexed as

BiomarkersChronic kidney diseaseDopplerHeart failureRenal resistance index

Identifiers

PMID25610846
PMCPMC4295215
OpenAlexW2001725046

What OpenQuestion holds

Textmetadata
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.