Evidence map›Paper›PMID 32589369›Full record

ArticleESC heart failure2020

Growth differentiation factor 15 as mortality predictor in heart failure patients with non-reduced ejection fraction.

Ana Belen Mendez Fernandez, Andreu Ferrero-Gregori, Alvaro Garcia-Osuna, Sonia Mirabet-Perez, Maria Jose Pirla-Buxo, Juan Cinca-Cuscullola, Jordi Ordonez-Llanos, Eulàlia Roig Minguell

Open access · goldAbstract read
In one paragraph

Article in ESC heart failure, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers, 4 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
26citing papers in PubMed, 4 pooled it
3.5field-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

26 citing papers in PubMed, 4 syntheses or guidelines pooled it, 35 citations in OpenAlex.

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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 at 3 institutions in 1 country.

Ana Belen Mendez FernandezDepartment of Cardiology, CIBERCV, Hospital Santa Creu i Sant Pau, Barcelona, Spain.
Andreu Ferrero-GregoriDepartment of Cardiology, CIBERCV, Hospital Santa Creu i Sant Pau, Barcelona, Spain.
Alvaro Garcia-OsunaDepartment of Biochemistry, IIB-Sant Pau, Barcelona, Spain.
Sonia Mirabet-PerezDepartment of Cardiology, CIBERCV, Hospital Santa Creu i Sant Pau, Barcelona, Spain.
Maria Jose Pirla-BuxoDepartment of Cardiology, CIBERCV, Hospital Santa Creu i Sant Pau, Barcelona, Spain.
Juan Cinca-CuscullolaDepartment of Cardiology, CIBERCV, Hospital Santa Creu i Sant Pau, Barcelona, Spain.
Jordi Ordonez-LlanosDepartment of Biochemistry, IIB-Sant Pau, Barcelona, Spain.
Eulàlia Roig MinguellDepartment of Cardiology, CIBERCV, Hospital Santa Creu i Sant Pau, Barcelona, Spain.
Hospital de Sant Pau · ESCentro de Investigación en Red en Enfermedades Cardiovasculares · ESUniversitat Autònoma de Barcelona · ES

Funding

Fundació d'Investigació Sant Pau G-60136934
6 · The paper itself

Abstract

aimsThe prognostic value of biomarkers in patients with heart failure (HF) and mid-range (HFmrEF) or preserved ejection fraction (HFpEF) has not been widely addressed. The aim of this study was to assess whether the prognostic value of growth differentiation factor 15 (GDF-15) is superior to that of N-terminal pro-brain natriuretic peptide (NT-proBNP) in patients with HFmrEF or HFpEF. METHODS AND

resultsHeart failure patients with either HFpEF or HFmrEF were included in the study. During their first visit to the HF unit, serum samples were obtained and stored for later assessment of GDF-15 and NT-proBNP concentrations. Patients were followed up by the HF unit. The main endpoint was all-cause mortality. A total of 311 patients, 90 (29%) HFmrEF and 221 (71%) HFpEF, were included. Mean age was 72 ± 13 years, and 136 (44%) were women. No differences were found in GDF-15 or NT-proBNP concentrations between both HF groups. During a median follow-up of 15 months (Q1-Q3: 9-30 months), 98 patients (32%) died, most (71%) of cardiovascular causes. Patients who died had higher median concentrations of GDF-15 (4085 vs. 2270 ng/L, P < 0.0001) and NT-proBNP (1984 vs. 1095 ng/L, P < 0.0001). A Cox multivariable model identified New York Heart Association Functional Class III (P = 0.04), systolic blood pressure (P = 0.01), left atrial diameter (P = 0.03), age >65 years (P < 0.0001), and GDF-15 concentrations (P = 0.01) but not NT-proBNP as independent predictors of all-cause mortality. The area under the curve was 0.797 for the basic model including NT-proBNP, and the area under the curve comparing the overall model was 0.819, P = 0.016 (DeLong's test). Integrated discrimination improvement index after the inclusion of GDF-15 in the model with the mortality risk factors was 0.033; that is, the ability to predict death increased by 3.3% (P = 0.004). Net reclassification improvement was 0.548 (P < 0.001); that is, the capacity to improve the classification of the event (mortality) was 54.8%. GDF-15 concentrations were divided in tertiles (<1625, 1625-4330, and >4330 ng/L), and survival curves were evaluated using the Kaplan-Meier technique. Patients in the highest tertile had the poorest 5 year survival, at 16%, whereas the lowest tertile had the best survival, of 78% (P < 0.001).

conclusionsGrowth differentiation factor 15 was superior to NT-proBNP for assessing prognosis in patients with HFpEF and HFmrEF. GDF-15 emerges as a strong, independent biomarker for identifying HFmrEF and HFpEF patients with worse prognosis.

Indexed as

Growth Differentiation Factor 15Heart FailureAgedAged, 80 and overBiomarkersFemaleHumansMaleMiddle AgedPrognosisStroke VolumeBiomarkersGDF15 protein, humanGrowth Differentiation Factor 15BiomarkersChronic heart failureGDF-15HFmrEFHFpEF

Identifiers

PMID32589369
PMCPMC7524215
OpenAlexW3037673454

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.