Evidence map›Paper›PMID 29681522›Full record

ArticleJournal of the American Society of Hypertension : JASH2018

Epidemiologic observations guiding clinical application of a urinary peptidomic marker of diastolic left ventricular dysfunction.

Zhen-Yu Zhang, Esther Nkuipou-Kenfack, Wen-Yi Yang, Fang-Fei Wei, Nicholas Cauwenberghs, Lutgarde Thijs, Qi-Fang Huang, Ying-Mei Feng, Joost P Schanstra, Tatiana Kuznetsova and 4 more

Open access · hybridAbstract read
In one paragraph

Article in Journal of the American Society of Hypertension : JASH, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
2.4field-weighted citation impact, top 10% 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

8 citing papers in PubMed, 22 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

14 authors at 6 institutions in 6 countries.

Zhen-Yu ZhangStudies Coordinating Centre, Research Unit Hypertension and Cardiovascular Epidemiology, KU Leuven Department of Cardiovascular Diseases, University of Leuven, Leuven, Belgium; Department of Cardiovascular Diseases, Shanghai General Hospital, Shanghai, China.
Esther Nkuipou-KenfackMosaiques Diagnostic and Therapeutics AG, Hannover, Germany.
Wen-Yi YangStudies Coordinating Centre, Research Unit Hypertension and Cardiovascular Epidemiology, KU Leuven Department of Cardiovascular Diseases, University of Leuven, Leuven, Belgium; Department of Cardiovascular Diseases, Shanghai General Hospital, Shanghai, China.
Fang-Fei WeiStudies Coordinating Centre, Research Unit Hypertension and Cardiovascular Epidemiology, KU Leuven Department of Cardiovascular Diseases, University of Leuven, Leuven, Belgium.
Nicholas CauwenberghsStudies Coordinating Centre, Research Unit Hypertension and Cardiovascular Epidemiology, KU Leuven Department of Cardiovascular Diseases, University of Leuven, Leuven, Belgium.
Lutgarde ThijsStudies Coordinating Centre, Research Unit Hypertension and Cardiovascular Epidemiology, KU Leuven Department of Cardiovascular Diseases, University of Leuven, Leuven, Belgium.
Qi-Fang HuangStudies Coordinating Centre, Research Unit Hypertension and Cardiovascular Epidemiology, KU Leuven Department of Cardiovascular Diseases, University of Leuven, Leuven, Belgium.
Ying-Mei FengBeijing Key Laboratory of Diabetes Prevention and Research, Department of Endocrinology, Lu He Hospital, Capital Medical University, Beijing, China.
Joost P SchanstraInstitute of Cardiovascular and Metabolic Disease, French Institute of Health and Medical Research U1048, Toulouse, France.
Tatiana KuznetsovaStudies Coordinating Centre, Research Unit Hypertension and Cardiovascular Epidemiology, KU Leuven Department of Cardiovascular Diseases, University of Leuven, Leuven, Belgium.
Jens-Uwe VoigtResearch Unit Cardiology, KU Leuven Department of Cardiovascular Diseases, University of Leuven, Leuven, Belgium.
Peter VerhammeCenter for Molecular and Vascular Biology, KU Leuven Department of Cardiovascular Diseases, University of Leuven, Leuven, Belgium.
Harald MischakMosaiques Diagnostic and Therapeutics AG, Hannover, Germany; BHF Glasgow Cardiovascular Research Centre, University of Glasgow, United Kingdom.
Jan A StaessenStudies Coordinating Centre, Research Unit Hypertension and Cardiovascular Epidemiology, KU Leuven Department of Cardiovascular Diseases, University of Leuven, Leuven, Belgium; R&D Group VitaK, Maastricht University, Maastricht, The Netherlands. Electronic address: jan.staessen@med.kuleuven.be.
KU Leuven · BEMosaiques Diagnostics and Therapeutics (Germany) · DEShanghai First People's Hospital · CNBeijing Luhe Hospital Affiliated to Capital Medical University · CNInserm · FRMaastricht University · NL

Funding

European Research Council 294713
6 · The paper itself

Abstract

Hypertension, obesity, and old age are major risk factors for left ventricular (LV) diastolic dysfunction (LVDD), but easily applicable screening tools for people at risk are lacking. We investigated whether HF1, a urinary biomarker consisting of 85 peptides, can predict over a 5-year time span mildly impaired diastolic LV function as assessed by echocardiography. In 645 white Flemish (50.5% women; 50.9 years [mean]), we measured HF1 by capillary electrophoresis coupled with mass spectrometry in 2005-2010. We measured early (E) and late (A) peak velocities of the transmitral blood flow and early (e') and late (a') mitral annular peak velocities and their ratios in 2009-2013. In multivariable-adjusted analyses, per 1-standard deviation increment in HF1, e' was -0.193 cm/s lower (95% confidence interval: -0.352 to -0.033; P = .018) and E/e' 0.174 units higher (0.005-0.342; P = .043). Of 645 participants, 179 (27.8%) had LVDD at follow-up, based on impaired relaxation in 69 patients (38.5%) or an elevated filling pressure in the presence of a normal (74 [43.8%]) or low (36 [20.1%]) age-specific E/A ratio. For a 1-standard deviation increment in HF1, the adjusted odds ratio was 1.37 (confidence interval, 1.07-1.76; P = .013). The integrated discrimination (+1.14%) and net reclassification (+31.7%) improvement of the optimized HF1 threshold (-0.350) in discriminating normal from abnormal diastolic LV function at follow-up over and beyond other risk factors was significant (P ≤ .024). In conclusion, HF1 may allow screening for LVDD over a 5-year horizon in asymptomatic people.

Indexed as

Diastolic left ventricular functionpopulation sciencescreeningurinary proteomics

Identifiers

PMID29681522
PMCPMC5990703
OpenAlexW2792876169

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

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.