Evidence map›Paper›PMID 26770427›Full record

ArticleInternational journal of clinical and experimental medicine2015

The utility of biomarker risk prediction score in patients with chronic heart failure.

Alexander E Berezin, Alexander A Kremzer, Yulia V Martovitskaya, Tatyana A Samura, Tatyana A Berezina, Anthony Zulli, Jan Klimas, Peter Kruzliak

Abstract read
In one paragraph

Article in International journal of clinical and experimental medicine, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed, 1 pooled it
–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

15 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Association between elevated adiponectin level and adverse outcomes in patients with heart failure: a systematic review and meta-analysis.Brazilian journal of medical and biological research = Revista brasileira de pesquisas medicas e biologica · 2019
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  4. Prediction of new-onset atrial fibrillation in patients with hypertrophic cardiomyopathy using plasma proteomics profiling.Europace : European pacing, arrhythmias, and cardiac electrophysiology : journal of the working groups on cardiac pacing, arrhythmias, and cardiac cellular electrophysiology of the European Society of Cardiology · 2024
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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

8 authors.

Alexander E BerezinDepartment of Internal Medicine, State Medical University Zaporozhye, Ukraine.
Alexander A KremzerDepartment of Clinical Pharmacology, State Medical University Zaporozhye, Ukraine.
Yulia V MartovitskayaDepartment of Pathology, State Medical University Zaporozhye, Ukraine.
Tatyana A SamuraDepartment of Clinical Pharmacology, State Medical University Zaporozhye, Ukraine.
Tatyana A BerezinaPrivate Medical Center "Vita-Center" Zaporozhye, Ukraine.
Anthony ZulliThe Centre for Chronic Disease Prevention & Management (CCDPM), Western CHRE, Victoria University St. Albans, Australia.
Jan KlimasDepartment of Pharmacology and Toxicology, Facultyof Pharmacy, Comenius University Bratislava, Slovak Republic.
Peter Kruzliak2nd Department of Internal Medicine, St. Anne's University Hospital and Masaryk UniversityBrno, Czech Republic; Laboratory of Structural Biology and Proteomics, Faculty of Pharmacy, University of Veterinary and Pharmaceutical SciencesBrno, Czech Republic.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

unlabelledChronic heart failure (CHF) remains a leading cause of cardiovascular death worldwide. Current risk models allow better prognosis, however further tools for assessing risk are needed. Thus, this study was aimed to evaluate whether biomarker risk prediction score is powerful tool for risk assessment of three-year fatal and non-fatal cardiovascular events in CHF patients.

methodsA prospective study on the incidence of fatal and non-fatal cardiovascular events, as well as the frequency of occurrence of death from any cause in a cohort of 388 patients with CHF during 3 years of observation was performed. Circulating levels of NT-pro brain natriuretic peptide (NT-pro-BNP), galectin-3, high-sensitivity C-reactive protein (hs-CRP), osteoprotegerin and its soluble receptor sRANKL, osteopontin, osteonectin, adiponectin, endothelial apoptotic microparticles (EMPs) and mononuclear progenitor cells (MPCs) were measured at baseline.

resultsMedian follow-up of patients included in the study was 2.76 years. There were 285 cardiovascular events determined, including 43 deaths and 242 readmissions. Independent predictors of clinical outcomes in patients with CHF were NT-pro-BNP, galectin-3, hs-CRP, osteoprotegerin, CD31(+)/annexin V(+) EMPs and EMPs/CD14(+)CD309(+) MPCs ratio. Index of cardiovascular risk was calculated by mathematical summation of all ranks of independent predictors, which occurred in the patients included in the study. The findings showed that the average value of the index of cardiovascular risk in patients with CHF was 3.17 points (95% CI = 1.65-5.10 points). Kaplan-Meier analysis showed that patients with CHF and the magnitude of the risk of less than 4 units have an advantage in survival when compared with patients for whom obtained higher values of ranks cardiovascular risk score.

conclusionBiomarker risk score for cumulative cardiovascular events, constructed by measurement of circulating NT-pro-BNP, galectin-3, hs-CRP, osteoprotegerin, CD31(+)/annexin V(+) EMPs and EMPs/CD14(+)CD309(+) MPCs ratio, reliably predicts the probability survival of patients with CHF, regardless of age, gender, state of the contractile function of the left ventricle and the number of comorbidities.

Indexed as

biomarkerscardiovascular outcomesChronic heart failurepredictive value

Identifiers

PMID26770427
PMCPMC4694327

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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.