Evidence map›Paper›PMID 29404976›Full record

SynthesisCurrent heart failure reports2018

An Appraisal of Biomarker-Based Risk-Scoring Models in Chronic Heart Failure: Which One Is Best?

Barbara S Doumouras, Douglas S Lee, Wayne C Levy, Ana C Alba

Abstract readSystematic Review
PubMed Publisher
In one paragraph

Synthesis in Current heart failure reports, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
–field-weighted citation impact
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

7 citing papers in PubMed.

  1. Trial
  2. Article
  3. Article
  4. Article
  5. Review
  6. Interleukin-6 and adhesion molecules VCAM-1 and ICAM-1 as biomarkers of post-acute myocardial infarction heart failure.Brazilian journal of medical and biological research = Revista brasileira de pesquisas medicas e biologica · 2019
    Article
  7. Review
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.

Barbara S DoumourasHeart Failure and Transplant Program, Toronto General Hospital, University Health Network, University of Toronto, Toronto, Ontario, Canada. barbara.doumouras@mail.utoronto.ca.
Douglas S LeeInstitute for Clinical Evaluative Sciences, Peter Munk Cardiac Centre and Joint Department of Medical Imaging, University Health Network, University of Toronto, Toronto, ON, Canada.
Wayne C LevyUniversity of Washington, Seattle, WA, USA.
Ana C AlbaHeart Failure and Transplant Program, Toronto General Hospital, University Health Network, University of Toronto, Toronto, Ontario, Canada.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purpose of reviewWhile prediction models incorporating biomarkers are used in heart failure, these have shown wide-ranging discrimination and calibration. This review will discuss externally validated biomarker-based risk models in chronic heart failure patients assessing their quality and relevance to clinical practice. RECENT

findingsBiomarkers may help in determining prognosis in chronic heart failure patients as they reflect early pathologic processes, even before symptoms or worsening disease. We present the characteristics and describe the performance of 10 externally validated prediction models including at least one biomarker among their predictive factors. Very few models report adequate discrimination and calibration. Some studies evaluated the additional predictive value of adding a biomarker to a model. However, these have not been routinely assessed in subsequent validation studies. New and existing prediction models should include biomarkers, which improve model performance. Ongoing research is needed to assess the performance of models in contemporary patients.

Indexed as

BiomarkersHeart FailureHumansPrognosisRisk AssessmentSeverity of Illness IndexBiomarkersBiomarkerChronic heart failureOutpatientPrediction modelRisk score

Identifiers

PMID29404976

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.