Evidence map›Paper›PMID 30192769›Full record

ArticlePloS one2018

Routinely measured hematological parameters and prediction of recurrent vascular events in patients with clinically manifest vascular disease.

Daniel Kofink, Steven A Muller, Riyaz S Patel, Jannick A N Dorresteijn, Gijs F N Berkelmans, Mark C H de Groot, Wouter W van Solinge, Saskia Haitjema, Tim Leiner, Frank L J Visseren and 3 more

Abstract read
In one paragraph

Article in PloS one, 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.

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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

13 authors.

Daniel KofinkDepartment of Cardiology, University Medical Utrecht, University of Utrecht, Utrecht, the Netherlands.ORCID 0000-0002-0223-8608
Steven A MullerDepartment of Cardiology, University Medical Utrecht, University of Utrecht, Utrecht, the Netherlands.ORCID 0000-0002-2674-8709
Riyaz S PatelInstitute of Cardiovascular Science, Faculty of Population Health Sciences, University College London, London, United Kingdom.
Jannick A N DorresteijnDepartment of Vascular Medicine, University Medical Center Utrecht, University of Utrecht, Utrecht, the Netherlands.
Gijs F N BerkelmansDepartment of Vascular Medicine, University Medical Center Utrecht, University of Utrecht, Utrecht, the Netherlands.
Mark C H de GrootDivision of Pharmacoepidemiology and Clinical Pharmacology, Utrecht University, Utrecht, the Netherlands.ORCID 0000-0002-5764-5788
Wouter W van SolingeDepartment of Clinical Chemistry and Hematology, University Medical Center Utrecht, University of Utrecht, Utrecht, the Netherlands.
Saskia HaitjemaDepartment of Clinical Chemistry and Hematology, University Medical Center Utrecht, University of Utrecht, Utrecht, the Netherlands.
Tim LeinerDepartment of Radiology, University Medical Center Utrecht, University of Utrecht, Utrecht, the Netherlands.
Frank L J VisserenDepartment of Vascular Medicine, University Medical Center Utrecht, University of Utrecht, Utrecht, the Netherlands.
Imo E HoeferDepartment of Clinical Chemistry and Hematology, University Medical Center Utrecht, University of Utrecht, Utrecht, the Netherlands.
Folkert W AsselbergsDepartment of Cardiology, University Medical Utrecht, University of Utrecht, Utrecht, the Netherlands.
SMART Study Group

Funding

British Heart Foundation FS/14/76/30933
6 · The paper itself

Abstract

BACKGROUND AND

aimsThe predictive value of traditional risk factors for vascular events in patients with manifest vascular disease is limited, underscoring the need for novel biomarkers to improve risk stratification. Since hematological parameters are routinely assessed in clinical practice, they are readily available candidates.

methodsWe used data from 3,922 vascular patients, who participated in the Second Manifestations of ARTerial Disease (SMART) study. We first investigated associations between recurrent vascular events and 22 hematological parameters, obtained from the Utrecht Patient Oriented Database (UPOD), and then assessed whether parameters associated with outcome improved risk prediction.

resultsAfter adjustment for all SMART risk score (SRS) variables, lymphocyte %, neutrophil count, neutrophil % and red cell distribution width (RDW) were significantly associated with vascular events. When individually added to the SRS, lymphocyte % improved prediction of recurrent vascular events with a continuous net reclassification improvement (cNRI) of 17.4% [95% CI: 2.1, 32.1%] and an increase in c-statistic of 0.011 [0.000, 0.022]. The combination of lymphocyte % and neutrophil count resulted in a cNRI of 22.2% [3.2, 33.4%] and improved c-statistic by 0.011 [95% CI: 0.000, 0.022]. Lymphocyte % and RDW yielded a cNRI of 18.7% [3.3, 31.9%] and improved c-statistic by 0.016 [0.004, 0.028]. However, the addition of hematological parameters only modestly increased risk estimates for patients with an event during follow-up.

conclusionsSeveral hematological parameters were independently associated with recurrent vascular events. Lymphocyte % alone and in combination with other parameters enhanced discrimination and reclassification. However, the incremental value for patients with a recurrent event was limited.

Indexed as

Hematologic TestsAgedFemaleHumansMaleMiddle AgedPredictive Value of TestsPrognosisRecurrenceRisk AssessmentVascular Diseases

Identifiers

PMID30192769
PMCPMC6128486

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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.